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Brian Scott Glassman

IMPROVING IDEA GENERATION AND IDEA MANAGEMENT IN-ORDER TO BETTERMANAGE THE FUZZY FRONT END OF INNOVATION

Doctor of Philosophy

Dr. Linda Naimi

Dr. Michael Menefee

Rodney Vandeveer

William Krug

Dr. Linda Naimi

Dr. Gary Bertoline 4/19/09

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IMPROVING IDEA GENERATION AND IDEA MANAGEMENTIN-ORDER TO BETTER MANAGE THE FUZZY FRONT END OF INNOVATION

Doctor of Philosophy

April-20-2009

Brian Glassman

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Received from: Glassman, Brian Scott Student ID No. 00168-37682

Major Professor: L. Naimi Department Head: G. Bertoline

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Subject Heading∗ Business Administration, Marketing; Business Administration, Management; Business Administration, General

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Pagination . xv; 329p.

Notes .

IMPROVING IDEA GENERATION AND IDEA MANAGEMENT IN ORDER TO BETTER MANAGE THE FUZZY FRONT END OF INNOVATION

A Dissertation

Submitted to the Faculty of

Purdue University by

Brian Scott Glassman

In Partial Fulfillment of the

Requirements for the Degree of

Doctor of Philosophy

May 2009

Purdue University

West Lafayette Indiana

ii

I dedicate my thesis to my mother and father, Linda and Andy whose patience,

nurturing and regard for education held me on a steady course. I want to

express my appreciation to my sister Stephanie whose antics always kept me

thinking of ways to outsmart her. I also want to thank my Grandmother Irene

and Grandma Sally for their unconditional love and emotional support. I want to

acknowledge my Aunt Nancy for her wise encouragement and advice. Finally, I

want to remember my Poppa Frank whose love and enthusiasm for engineering

was passed down to me with unending patience at his basement workbench.

iii

ACKNOWLEDGMENTS

I would like to thank my committee members - Linda Naimi, Michael Menefee,

Rodney Vandeveer and William Krug - for their help and support throughout the

dissertation process. And I would like to thank Kenneth Kahn for his advice and

encouragement.

I would especially like to thank my major advisor, Dr. Linda Naimi, for her

support, encouragement, and understanding. She truly is an inspiration to me!

Select Quotes

“In the hustle and bustle of everyday life, one can get caught up in life’s many

problems. When that happens, remember life is beautiful. Stop and take some

time to appreciate how beautiful and precious it is. It will surely make you feel

better.” - Dr. M.T. Naimi

“Life is not hard any more, it is just a whole lot more complicated.”

- Brian Glassman

“The brain is a wonderful organ. It starts working the moment you get up in the

morning and does not stop until you get to the office.” - Robert Frost

iv

PREFACE

During my management studies at Duke University, Dr. Jeff Glass, a great

leader, and always an inspiration to me, was the first to formally introduce me to

the topic of the fuzzy front end. I remember it vividly, because he said the fuzzy

front end was a major challenge for management because its inner workings

were relatively unknown. From that point on, I was hooked on the topic and the

major challenges associated with it, and I felt a compelling need to help solve this

vital piece of the innovation puzzle. Hopefully, I have shed some light on it with

this research and model.

v

TABLE OF CONTENTS

Page LIST OF TABLES ................................................................................................. x LIST OF FIGURES .............................................................................................. xi LIST OF ABBREVIATIONS ............................................................................... xiv ABSTRACT ......................................................................................................... xv CHAPTER 1. INTRODUCTION ............................................................................ 1 1.1. Statement of Research Problem, Background, and Context ....................... 1 1.2. Importance and Significant of the Study ..................................................... 4 1.3. Research Questions ................................................................................... 5 1.4. Assumptions ............................................................................................... 6 1.5. Delimitations and Limitations ...................................................................... 8

CHAPTER 2. A COMPREHENSIVE REVIEW OF THE LITERATURE................. 9 2.1. Literature Review of Ideas .......................................................................... 9 2.1.1. Why does the Innovation Process Need Ideas? ................................... 9 2.1.2. Value of Ideas ..................................................................................... 10 2.1.3. Defining an Idea .................................................................................. 11 2.1.4. Narrowing the Definition of Ideas ........................................................ 12 2.1.5. Terminology ........................................................................................ 14 2.1.6. New and Old Ideas ............................................................................. 16 2.1.7. Summary of Literature Review on Idea ............................................... 17

2.2. The Evolution of the Innovation Process ................................................... 18 2.2.1. The Importance of Innovation ............................................................. 18 2.2.2. A Quick History of Innovation and R&D: A Process Perspective ........ 19

2.3. Research on the Fuzzy Front End ............................................................ 26 2.3.1. Intro to Section on Fuzzy Front End .................................................... 26 2.3.2. Terminology for the Fuzzy Front End .................................................. 27 2.3.3. Activities in the Front End of Innovation .............................................. 29 2.3.4. Importance of the FFE ........................................................................ 30 2.3.5. Deliverable at the End of the Fuzzy Front End ................................... 32 2.3.6. Structured vs. Unstructured Fuzzy Front End ..................................... 33 2.3.7. Quick Review of Research on the Fuzzy Front End............................ 34 2.3.8. Summary of Research on the FFE...................................................... 36

2.4. Review of Process Models for the Fuzzy Front End ................................. 37 2.4.1. Intro to Section .................................................................................... 37 2.4.2. Review of FFE Process Models .......................................................... 37 2.4.3. Innovation Value Chain ....................................................................... 38

vi

Page 2.4.4. Cooper’s Stage-Gate Process Model .................................................. 40 2.4.5. Downsides of the Stage-Gate Model .................................................. 45 2.4.6. Khurana & Rosenthal FFE Model ....................................................... 46 2.4.7. Deloitte’s Spiral Model ........................................................................ 48 2.4.8. Downsides of the Deloitte Spiral Model .............................................. 51 2.4.9. Koen’s NCD Model ............................................................................. 52 2.4.10. Downsides and Conclusion on Koen’s Model ................................... 54 2.4.11. Husig, Kohn, and Poskela 2003 ........................................................ 55 2.4.12. Montoya-Weiss & O’Driscoll ............................................................. 56 2.4.13. General Problems and Issues with Fuzzy Front End Models ............ 57

2.5. Literature Review of Activities in the Fuzzy Front End .............................. 62 2.5.1. List of Activities in the Fuzzy Front End .............................................. 62 2.5.2. Quick Categorization of Activities in the Fuzzy Front End ................... 68 2.5.3. Proposed Organization of Activities for the Fuzzy Front End .............. 68 2.5.4. Summary of Section ............................................................................ 69

2.6. Literature Review of Idea Generation ....................................................... 69 2.6.1. Why is Idea Generation Important? .................................................... 70 2.6.2. What is Idea Generation? ................................................................... 71 2.6.3. A Review of Idea Generation Research .............................................. 72 2.6.4. Creativity and Idea Generation ........................................................... 74 2.6.5. Environmental Scanning and Idea Generation ................................... 75 2.6.6. Seeding Ideas ..................................................................................... 77 2.6.7. Opportunity Identifications .................................................................. 78 2.6.8. Issues and Problems with Idea Generation ........................................ 79 2.6.9. Summary of Section ............................................................................ 81

2.7. Highly Detailed Review of Sources of Ideas, and Idea Generation Techniques, Activities, and Processes ............................................................ 81 2.7.1. People are the Only Source of Ideas .................................................. 81 2.7.2. Techniques, Activities, and Full Processes for Idea Generation ......... 84 2.7.3. Review of top idea generation processes ........................................... 90 2.7.4. Detailed Examination of Sources of Ideas ........................................ 101 2.7.5. Issues with External Sources of Ideas .............................................. 112 2.7.6. Which Source of Ideas is the Best? .................................................. 112 2.7.7. Major Issue with Idea Generation (Lack of Control Models) ............. 113 2.7.8. Summary of Section 2.7 .................................................................... 113

2.8. Literature Review of Idea Management and Idea Banks ........................ 114 2.8.1. Introduction to Section ...................................................................... 114 2.8.2. What is Idea Management and What are Idea Banks? ..................... 114 2.8.3. Need for Idea Management and Idea Banks .................................... 115 2.8.4. Terminology for Idea Banks .............................................................. 116 2.8.5. A Review of the Literature on Idea Management and Idea Banks .... 117 2.8.6. Problems and Issues with Idea Management and Idea Banks ......... 126 2.8.7. Summary of Section .......................................................................... 127

vii

Page CHAPTER 3. DEVELOPMENT OF CONTROL MODELS ................................ 128 3.1. Review and Selection of a Control Theory .............................................. 128 3.2. Development of a Control Model for Idea Generation ............................. 132 3.2.1. Continuous Idea Generation vs. Event Based Idea Generation ........ 132 3.2.2. Supporting Evidence for Ideation Events .......................................... 133 3.2.3. Controlling External and Internal Events ........................................... 135 3.2.4. Controlling the Source ...................................................................... 138 3.2.5. Internal vs. External Source and Methods of Control ........................ 140 3.2.6. Controlling Idea Generation Activities ............................................... 141 3.2.7. Internal and External Idea Generation and Control ........................... 144 3.2.8. Screening and Filtering Before Being Captured ................................ 145 3.2.9. Quick Review on Areas of Control .................................................... 147 3.2.10. Strategy and Idea Generation ......................................................... 148 3.2.11. Idea Generation’s Process Check Analysis .................................... 153 3.2.12. Characteristics of Created Ideas ..................................................... 154 3.2.13. A Practical example of managing the idea generation process ...... 155 3.2.14. Summary of Section ........................................................................ 157

3.3. Development of a Control Model for Idea Banks and Idea Management 158 3.3.1. Major Functions of Idea Management ............................................... 158 3.3.2. Capturing Ideas................................................................................. 161 3.3.3. Tagging ............................................................................................. 166 3.3.4. Storage and Categorizing ................................................................. 173 3.3.5. Process Check and Feedback .......................................................... 182 3.3.6. Diffusing and Routing ........................................................................ 184 3.3.7. Routing ............................................................................................. 189

3.4. Linking Idea Banks to Portfolio Management .......................................... 190 CHAPTER 4. RESEARCH METHODOLOGY ................................................... 193 4.1. Purpose of Study .................................................................................... 193 4.2. Limitations Effecting the Selection of the Type of Study ......................... 193 4.2.1. Lack of Metrics for Success in Idea Generation ................................ 193

4.3. Study Type Which Will Not Be Used ....................................................... 195 4.3.1. Observational Based Support Studies .............................................. 195 4.3.2. Application Based Support Study...................................................... 195 4.3.3. Laboratory Testing Base Support Study ........................................... 196 4.3.4. Analysis of Secondary Research ...................................................... 196 4.3.5. Interview Based Support ................................................................... 196 4.3.6. Electronic Survey Study .................................................................... 197

4.4. Parts to the Study ................................................................................... 198 4.5. Study Part One ....................................................................................... 198 4.6. Study Part Two ....................................................................................... 199 4.6.1. Description of Part Two ..................................................................... 199 4.6.2. Description of Survey Tool ................................................................ 200 4.6.3. Description of the Respondent Pool.................................................. 202 4.6.4. Data Analysis .................................................................................... 202

viii

Page CHAPTER 5. RESEARCH RESULTS .............................................................. 204 5.1. Summary of Case Study Results ............................................................ 204 5.1.1. Benefits of the Case Studies ............................................................. 205 5.1.2. Analysis of the Company .................................................................. 205 5.1.3. Brief Summary of Each Case Study .................................................. 206

5.2. Case Study 1: Company Alpha ............................................................... 208 5.2.1. Background on the Company ........................................................... 208 5.2.2. Sources of Ideas for Idea Generation ............................................... 208 5.2.3. Events and Activities Used to Generate Ideas .................................. 209 5.2.4. Screening Ideas upon First Submission ............................................ 211 5.2.5. Capturing Ideas from Internal and External Sources ........................ 211 5.2.6. Sources Tapped for Ideas ................................................................. 213 5.2.7. Tagging Ideas during Capture .......................................................... 214 5.2.8. Storing and Categorizing Ideas ......................................................... 214 5.2.9. Process Check Used to Improve the Idea Generation Process ........ 215 5.2.10. Diffusing Ideas to Employees inside the Company ......................... 215 5.2.11. Comparison with Measures of Satisfaction ..................................... 216 5.2.12. Late Front End Activities at Company Alpha ................................... 217 5.2.13. Recommendations for Late Front End Activities ............................. 218

5.3. Case Study 2: Fairbanks Scales ............................................................. 218 5.3.1. Background on the Company ........................................................... 218 5.3.2. Overall Situation & Broader Strategic View ....................................... 219 5.3.3. Adopting a Broader View of Their Core Business ............................. 221 5.3.4. A Broader Understanding of How their Products Fit into the Job Process ....................................................................................................... 222 5.3.5. Idea Generation ................................................................................ 223 5.3.6. Recommendations for Idea Generation ............................................ 224 5.3.7. Screening of Ideas ............................................................................ 227 5.3.8. Capturing Ideas from Internal and External Sources ........................ 228 5.3.9. Tagging Ideas during Capture .......................................................... 228 5.3.10. Storage and Categorization ............................................................ 229 5.3.11. Process Check Used to Improve the Idea Generation Process ...... 229 5.3.12. Diffusing Ideas to Employees inside the Company ......................... 229 5.3.13. Late Front End Activities ................................................................. 230 5.3.14. Skunk Works Team ......................................................................... 232 5.3.15. Comparison with Measures of Satisfaction ..................................... 233

5.4. Case Study 3: CartêGraph ...................................................................... 235 5.4.1. Background on the Company ........................................................... 235 5.4.2. Idea Generation ................................................................................ 235 5.4.3. Technology Adoption ........................................................................ 236 5.4.4. Types of Idea Generation Activities .................................................. 238 5.4.5. Idea Management ............................................................................. 238 5.4.6. First Screen of ideas ......................................................................... 239 5.4.7. Capturing Ideas from Internal and External Sources ........................ 239

ix

Page 5.4.8. Recommendations for Capturing Ideas ............................................. 240 5.4.9. Tagging Ideas during Capture .......................................................... 241 5.4.10. Storage & Categorization ................................................................ 241 5.4.11. Process Check Used to Improve the Idea Generation Process ...... 242 5.4.12. Diffusing Ideas to Employees Inside the Company ......................... 242 5.4.13. Late Front End Activities ................................................................. 243 5.4.14. Comparison with Measures of Satisfaction ..................................... 244

5.5. Case Study: Discussion of 2nd Research Question Based on Case Study Evidence ........................................................................................................ 245 5.6. Case Study: Major Lessons Learned ...................................................... 247 5.6.1. Structure of Idea Management ......................................................... 248 5.6.2. Situational Dependence on Idea Generation or Idea Management .. 249 5.6.3. Assigned Idea Manager .................................................................... 249 5.6.4. Expertise is Needed .......................................................................... 249

5.7. Survey: Method of Cleaning the Data and Analysis ................................ 250 5.8. Survey: General Demographic Statistics for the Sample ........................ 252 5.8.1. Sample’s Relation to the Greater Population .................................... 255

5.9. Survey: Correlations between Satisfaction Variables.............................. 256 5.9.1. Idea Generation ................................................................................ 256 5.9.2. Idea Capture ..................................................................................... 258 5.9.3. Development Outcomes ................................................................... 260

5.10. Survey: Discussion of Correlations Between Satisfaction Variables and Measures of Activities .................................................................................... 261 5.10.1. Correlations for the Idea Management Process .............................. 264

5.11. Survey: Discussion of Support for Proposed Model .............................. 274 5.12. Survey: Discussion of Normative Results ............................................. 275 5.12.1. Normative Results for Satisfaction Questions ................................. 275 5.12.2. Normative Results for Activity Questions ........................................ 276

5.13. Survey: Major Lessons Learned ........................................................... 278 CHAPTER 6. UPDATED CONTROL MODELS ................................................ 279 6.1. Screening Moved into Idea Management ............................................... 279 6.2. Strategic Alignment Activities .................................................................. 280 6.3. Final Version of the Glassman Control Model ......................................... 283

BIBLIOGRAPHY ............................................................................................... 284 APPENDICES Appendix A. Concept Life Cycle .................................................................... 301 Appendix B. Details of Stage Gate Process ................................................... 302 Appendix C. Survey Instrument ..................................................................... 303 Appendix D. Normative Survey Results ......................................................... 311

VITA ................................................................................................................. 329

x

LIST OF TABLES

Table Page Table 2.1. Koen et al. Activities in the Front End of Innovation ........................... 28 Table 2.2. Koen et al. Factors and Characteristics of the Front End of Innovation

...................................................................................................................... 29 Table 2.3. Specific Activities and Decisions for Each Stage and Gate ............... 43 Table 2.4. List of Activities Which Can Occur in the Front End of Innovation ..... 62 Table 2.5. Categorization of Front End Activities ................................................ 68 Table 2.6. Techniques which Aid in Idea Generation .......................................... 86 Table 2.7. Activities which Specifically Trigger Creativity.................................... 87 Table 2.8. Activities which Seed Individuals with Ideas ...................................... 88 Table 2.9. Activities Which Use Analysis to Spawn Creativity and Ideas ............ 89 Table 2.10. Full Idea Generation Processes ....................................................... 90 Table 2.11. Major Categories for Source of Ideas ............................................ 102 Table 2.12. Employee Based Sources of Ideas ................................................ 103 Table 2.13. Customer Sources Which Can Result in Ideas .............................. 104 Table 2.14. Non-for-profit Organizational Based Sources of Ideas ................... 106 Table 2.15. Supplier Sources ............................................................................ 109 Table 2.16. Competitor sources ........................................................................ 110 Table 2.17. Sources of Ideas From Other Companies ...................................... 111 Table 3.1. Example of Idea from the Company’s First Attempt ......................... 156 Table 3.2. Example of Improved Set of Idea Resulting from Second Attempt .. 157 Table 3.3. Diffusion Methods, Forced, and Sought Diffusion ............................ 187 Table 5.1. Attributes of the Three Companies .................................................. 205 Table 5.2. Idea Generation Satisfaction Variable Results for Alpha ................. 216 Table 5.3. Idea Management Satisfaction Results Variables for Alpha ............ 217 Table 5.4. Recommended Idea Generation Techniques and Activities ............ 226 Table 5.5. Idea Generation Satisfaction Variable Results for Fairbanks ........... 233 Table 5.6. Idea Management Satisfaction Results Variables for Fairbanks ...... 234 Table 5.7. Correlation for Diffusion Activities .................................................... 271 Table 5.8. Correlations for Idea Management Software ................................... 272 Table 5.9. Support Found for the Author’s Proposed Model ............................. 274

xi

LIST OF FIGURES

Figure Page Figure 1.1. Koen’s breakup of the new product innovation processes .................. 2 Figure 2.1. Concept Life Cycle Model ................................................................. 16 Figure 2.2. Early R&D process ........................................................................... 20 Figure 2.3. R&D Funnel ...................................................................................... 21 Figure 2.4. R&D Funnel and New Product and Commercialization Processes ... 21 Figure 2.5. Addition of the Fuzzy Front End ........................................................ 22 Figure 2.6. State-Gate Process in the Overall Development Process and a Map

of Project Costs as the Project Progresses ................................................... 23 Figure 2.7. Innovation Value Chain ..................................................................... 25 Figure 2.8. Visual Depiction of the Innovation Value Chain Model ..................... 38 Figure 2.9. Visual Depiction of the a Stage in the Stage-Gate Model ................. 41 Figure 2.10. Full Stage-Gate Process Model ...................................................... 41 Figure 2.11. Options for Sage Gate Process ...................................................... 44 Figure 2.12. Pie Charts Depicting Activities in Each Stages ............................... 45 Figure 2.13. Khurana & Rosenthal FFE model ................................................... 47 Figure 2.14. Visual Depiction of the Delottie’s Spiral Model ................................ 49 Figure 2.15. Visual Depiction of Koen’s NCD Model ........................................... 52 Figure 2.16. Visual Depiction of Husig, Kohn, and Poskela Model ..................... 55 Figure 2.17. Montoya-Weiss & O’Driscoll’s Funnel Model .................................. 56 Figure 2.18. Idea Creation in a Person’s Mind .................................................... 83 Figure 2.19. Activities Leading to the Creation of Ideas ...................................... 83 Figure 2.20. Unknown Activities which Lead to the Creation of an Idea ............. 84 Figure 2.21. Illustration of How Techniques are Embedded in Activities,............ 85 Figure 2.22. Illustration of the Contextual Research Process ............................. 92 Figure 2.23. Illustration of the Outcome-Based Innovation Process ................... 93 Figure 2.24. Illustration of the IDEO’s Idea Generation Process ......................... 96 Figure 2.25. The Strategic Canvas from Blue Oceans Strategy with

Three Plotted Value Curves .......................................................................... 97 Figure 2.26. Illustration of a Blue Ocean Strategy Idea Generation Process ...... 98 Figure 2.27. Illustration of Flynn’s Idea Generation Process ............................. 100 Figure 2.28. Modification of Flynn’s Idea Generation Process .......................... 101 Figure 2.29. Montoya-Weiss & O’Driscoll’s Idea Generation Process .............. 121 Figure 2.30. Bakker, Boersma, & Oreel Idea Storage Processes ..................... 124 Figure 3.1. Process Control Model ................................................................... 131 Figure 3.2. Process Control Model with formal input and process controls....... 131

xii

Figure Page Figure 3.3. Continuous Idea Generation vs. Event Driven Idea Generation ..... 132 Figure 3.4. Idea Generation Triggered by Formal Events ................................. 134 Figure 3.5. Controlling Both Internally Idea Events an External Idea Events .... 136 Figure 3.6. Ideation Events Influence on Idea Generation ................................ 137 Figure 3.7. Controls over Sources of Ideas ....................................................... 141 Figure 3.8. Controls over External and Internal Idea Generation ...................... 144 Figure 3.9. Screening and Filtering Located After Idea Generation Activities ... 145 Figure 3.10. Screening and Filtering in and After Idea Generation Activities .... 146 Figure 3.11. Points of Control in the Full Idea Generation Process .................. 147 Figure 3.12. Statistical Results from Adams-Bigelow Showing How Idea Were

Generated ................................................................................................... 149 Figure 3.13. Strategy’s Possible Influence on the Idea Generation Processes . 151 Figure 3.14. Strategic Idea Continuum ............................................................. 152 Figure 3.15. Control model for Idea Generation ................................................ 153 Figure 3.16. Initial version of Glassman Model ................................................. 160 Figure 3.17. An Example of a Company’s Receptiveness to Outside Ideas at

Respective Levels of Concept Development .............................................. 165 Figure 3.18. An Example of a Company’s Receptiveness to Outside Ideas in

Different Innovation Categories .................................................................. 166 Figure 3.19. Illustration of the Idea Cloud, Idea Bank,

and Company Idea Bank ............................................................................ 174 Figure 3.20. Illustration of the Continuum of Idea Formality .............................. 175 Figure 3.21. Illustration of the Diversity of Idea Banks ...................................... 176 Figure 3.22. Illustration of Idea Bank Organized by Incremental

and Radical Ideas ....................................................................................... 177 Figure 3.23. Illustration of Idea Bank Organized by Innovation Category ......... 177 Figure 3.24. Idea Management Feeding Idea Back into Idea Generation to

Stimulate more ideas .................................................................................. 184 Figure 3.25. Diffusion Power Spectrum ............................................................ 185 Figure 3.26. How Portfolio Management Determines Options for New Projects

.................................................................................................................... 191 Figure 3.27. How Assessment of Idea Banks can be Used by Portfolio Managers

.................................................................................................................... 191 Figure 3.28. Late FFE Activities Linking to Screening and Filtering .................. 192 Figure 5.1. Vertical Packaging Machine with Integrated Scales ....................... 222 Figure 5.2. Conversion of Answers from Likert to Ordinal Scales ..................... 251 Figure 5.3. Distribution of Respondents’ Companies amongst their Respective

Industries .................................................................................................... 253 Figure 5.4. Distribution of Respondent’s Companies by Revenues and Number of

Employees .................................................................................................. 253 Figure 5.5. Distribution of Respondent’s Companies by Locations ................... 254 Figure 5.6. Respondents Organized by their Roles .......................................... 255 Figure 5.7. Correlations of the Satisfaction Variables ....................................... 256

xiii

Figure Page Figure 5.8. Correlation for Overall Satisfactions with the Idea Generation Process

.................................................................................................................... 257 Figure 5.9. Correlation of V48 Ability to Fill Front End Portfolio ........................ 258 Figure 5.10. Correlation of 51S Ability to Capture Ideas from Employees ........ 259 Figure 5.11. Correlations of 52S Ability to Capture Ideas from Outside Sources

.................................................................................................................... 259 Figure 5.12. Correlation of Dependent Development Variables ........................ 260 Figure 5.13. Correlations with Company Resources ......................................... 260 Figure 5.14. Correlations of Activities to Quality of Ideas Generated ................ 261 Figure 5.15. Correlation 0.851 Comparison with Model .................................... 263 Figure 5.16. Weak Correlation for Capturing Ideas from Employees ................ 264 Figure 5.17. Strong Correlation for Capturing Ideas from Employees .............. 265 Figure 5.18. Correlation for Capturing Ideas from Outsides Sources ............... 267 Figure 5.19. Correlation for Storing and Capturing Ideas.................................. 269 Figure 5.20. Correlation for Process Improvement ........................................... 269 Figure 5.21. Correlation for Development Activities .......................................... 272 Figure 6.1. Updated Glassman Model .............................................................. 283

xiv

LIST OF ABBREVIATIONS

FFE - fuzzy front end of the innovation process

PDMA - product development and management association

NPD - new product development process

CAP - Capitalization which defines the market value of the company

xv

ABSTRACT

Glassman, Brian Scott. Ph.D, Purdue University, May 2009. Managing Idea Generation and Idea Management In Order to Better Manage The Fuzzy Front End of the Innovation Process. Major Professors: Linda Naimi and Michael Menefee.

An expansive review of the literature on the fuzzy front end of innovation, idea

generation, and idea management was conducted and is shown. Based on a

depth of understanding, a control model was developed to aid innovation

practitioners in effectively controlling the idea generation and idea management

processes.

This control model, named the Glassman Model for Managing Idea Generation,

was then validated in two studies. The first was the application of the control

model via analyzing, diagnosing, and making recommendations for three

companies outlined in three individual case studies. The second study used an

online survey to develop normative data and correlations on the idea generation

and idea management processes. Improvements were made to the model based

on lessons learned from the two studies. Both studies supported and validated

the model as containing the factors needed to manage these processes

effectively.

1

CHAPTER 1. INTRODUCTION

1.1. Statement of Research Problem, Background, and Context

The popular management of trends in the twentieth century towards improving

innovation is well founded because it is based on a company’s un-deniable need

to improve itself for the future (Collins, & Porras, 2002; Berkun 2007;

Christensen, & Raynor, 2003; Christensen, 2000; Drucker, 1985). Thousands, if

not hundreds of thousands, of articles, books, and publications, along with

conferences on the topic of innovation and the hundreds of innovation consulting

firms stress this point.

Out of the innovation literature, new product development has condensed

as a distinct field of research (Kahn, 2005; Belliveau, Griffen, Somermeyer, 2002;

Griffen, Somermeyer, 2007; Belliveau, 2004). Hallmark books on this subject by

authors such as Kahn (2005), Belliveau (2004), and Griffen & Somermeyer

(2007) reveal a large breadth of knowledge in this subject and cover areas

including management, processes, tools, resources, people, organizational

culture, and best practices for new product development.

On the process side, Koen (2005) breaks the innovation process “into

three areas: the Fuzzy front end (FFE), the New Product Development Portion

(NPD), and Commercialization” (Koen, 2005, p. 3).

2

Figure 1.1. Koen’s breakup of the new product innovation processes

Of these areas, the fuzzy front end (coined by Smith & Reinerten in 1991)

according to Kahn is “an important issue in future research on product

development (Verwon, Herstatt, & Nagahira, 2008). Further, authors like

Backman, Borjesson, and Setterberg (2007) say, “the greatest opportunities for

improving the overall innovation process lie in the very early phases of NPD”

process being the fuzzy front end (p. 321). Hence, Zhan and Doll (2001) states,

“managers and researchers claim the benefits resulting from improvements in the

front [end] are likely to far exceed those that result from improvements aimed

directly at the design engineering process” (Koen, et al. 2001, p. 2).

Process models for the fuzzy front end highlight idea generation as being

a core activity (Hansen, & Birkinshaw, 2007; Khurana, & Rosenthal, 1998;

Gallagher, George, & Kadaki, 2006; Koen et al. 2001; Husig, Kohn, & Poskela,

2003; Hüsig & Kohn, 2003; Hüsig, Kohn, & Poskela, 2005; Flint, 2002). Simply

put, Vandenbosch, Saatcioglu, & Fay (2006) state that “each innovation begins

with an idea” (p. 12). Jack Foster (1996) asserts “new ideas are the wheel of

progress” (p. 3). Finally, Linda Rochford (1991) posits that “ideas are the raw

material for product development” (p. 4).

According to Stasch, Lonsdale, & LaVenka (1992), “the objective of all

idea-generating activities is to guarantee that the company does not leave the

exploration stage of new-product development to chance” (Stasch et al, 1992, p.

New product

development

Commercialization processes Market launch Process

Ideas for new product & Services

Decision

FFE

Early phase of the

innovation process

3

3). In addition, “organizations that are active in new product development work

must have a system of sorts to keep the flow of ideas coming” (McGuiness,

1998, p. 121). Tucker (2003) claims that idea generation is sometimes applied

sporadically inside companies. Gamlin, Yourd, & Patrick (2007) refer to Cooper’s

quote - “Idea generation is everyone's job and no one's responsibility" - when

they described how “no one individual in a company or business unit is

specifically in charge of idea generation, and often, when new ideas surface, no

action is taken” (Gamlin et al, 2007, p. 42).

There are several fully detailed process for idea generation (Ulwick, 2007;

Kelley & Littman, 2005; Kelley, Littman, & Peters, 2001; Kim, & Mauborgne,

2005; Conley, 2005; Flynn, Dooley, & O’Sullivan, 2003).

However, a detailed review of idea generation in Section 2.6 revealed a

gap in the literature being the total lack of knowledge on how to manage and

control the idea generation process. This represents a deep chasm in the

understanding of idea generation which must be filled.

Further, idea management and idea banks were also identified as a key

item of importance in the fuzzy front end, where its’ major functions are to

capture, store, and organize ideas (Flynn, Dooley, & O’Sullivan, 2003; Belliveau,

Griffin, & Somermeyer, 2002; Montoya-Weiss & O’Driscoll, 2006; Gorski,

&Heinekamp, 2002; Bakker, Boersma, & Oreel, 2006; Heck, 2005; Fritz, 2002;

Dijk, & van de Ende, 2002; Koen et al., 2001).

Price Waterhouse and Ernst & Young, “advocated that companies [should]

adopt processes to collect and preserve their internal ideas” (Fritz, 2002, p. 54).

This may be because many ideas are lost or dropped from internal sources or

because “firms overlook other employees as a source of creative ideas” (Flynn,

Dooley, & O’Sullivan, 2003, p. 17; Gorski, & Heinekamp, 2002).

Several fully detailed software tools for idea management and idea banks

which can be implemented directly (Moskowitz, 1997; Zien, & Buckler, 1997;

Gorski, & Heinekamp, 2002; Bakker, Boersma, & Oreel, 2006; Heck, 2005; Fritz,

2002; Dijk, & van de Ende, 2002; Koen et al. 2001). However, a detailed review

4

of idea management in Section 2.8 revealed a gap in the literature being the total

lack of knowledge on how to manage and control the ideas and idea banks. This

represents a deep chasm in the understanding on idea management which also

should be filled. Therefore, this research will examine how selected companies

manage and control the idea generation and idea management processes.

1.2. Importance and Significant of the Study

Innovation currently is an area of great interest among researchers and

management practitioners (Berkun 2007; Christensen, & Raynor, 2003; Kahn,

2005). In the innovation field, the fuzzy front end has been identified by experts

to be an important area of research. Zhan and Doll (2001) state that “managers

and researchers [who] claim the benefits resulting from improvement in the front

[end] are likely to far exceed those that result from improvements aimed directly

at the design engineering process” (Zhan and Doll, 2001, p. 52). Many authors

state the value of the fuzzy front end in the innovation processes (Backman,

Borjesson, & Setterberg, 2007; Koen, et al., 2001; Verwon, Herstatt, & Nagahira,

2008; Cooper, & Kleinschmidt, 1994; Kim, & Wilemon, 2002; Khurana, &

Rosenthal, 1998; Verwon et al., 2008).

The following examples illustrate that the front end can be improved

through improvements in the idea generation processes. MIT Technology’s

Review 2003 R&D scorecard survey of the top 318 companies in the world in ten

different industry showed that they cumulatively spent $274 billion on R&D with

$4.13 trillion in revenues. Increasing their R&D efficiency by 1% could

cumulatively save $2.7 billion. Conversely, increasing their return on their R&D

dollars by even 1% could cumulatively easily produce hundreds of billions in

additional revenue. Given this, one can see that even a small improvement to the

innovation process can produce tremendous results.

Additionally, the value of this study can be in the creation of new

knowledge and the aid it may offer practitioners. First, this research developed

and tested a viable control model (referred to within this study as the Glassman

5

Model for Idea Generation Management) to fill the gap in the literature on

managing idea generation and idea management. Second, the creation of new

knowledge will occur from developing, testing and supporting this model. Third,

the model is expected to aid practitioners in more effectively managing ideas and

idea generation. In addition, given research on previous front end models, it is

expected that the proposed Glassman model could be applicable in companies

of any country and any industry, and thus may have a global impact on

innovation practices.

In terms of research, this model may provide future researchers with a

model to study the effect of particular factors on the outcome of the idea

generation processes. Additionally, this model explains and contributes to other

works on innovation by tying together previously disparate activities and topics

like knowledge brokering (Hardagon, & Sutton, 2000), environmental scanning,

seeding ideas, and opportunity identification. Additionally, it may bring together a

more coherent view of the front end of innovation and its inter-workings.

As well, it will address randomness and the chaotic nature of the fuzzy

front end by giving innovation practitioners a means to turn idea generation into

and on demand activity.

Ideally, a properly designed control model for idea generation and idea

management could become another best practice model for innovation, which

will lead to greater recognition of the importance of managing innovation,

efficiency in the idea generation process and opportunities for further research

and funding.

1.3. Research Questions

A review of current practices suggests a lack of suitable control models for idea

generation and idea management. Further, the literature illustrates the lack of a

conceptual understanding of how to manage either idea generation or idea

6

management. Interestingly, both idea generation and idea management are

linked through front end processes (Alam, 2003; Montoya-Weiss & O’Driscoll,

2006; Flynn, Dooley, O’Sullivan, and Cormican’s, 2003). Hence, the following

study addressed these research questions:

1.) Based on a review of the literature, can a control model be developed to

aid in the conceptual understanding and management of idea generation and

idea management?

2) Can the developed control model be supported as capturing the required

factors needed to manage and control idea generation and idea management

effectively?

1.4. Assumptions

A number of assumptions have been made for the purpose of this research study

and are broken up into the major areas assumptions related to: 1) company’s

motives, strategies, and limitations, 2) communication and information, 3)

supporting the proposed model, and finally assumptions related to 4) behavior of

the employees.

The first set of assumptions are related to the company’s motives,

strategies, and limitations and start with the assumption that the company would

like to improve its’ innovation process and has access to people which can be

trained to manage the innovation process.

Next, it is assumed that innovation practitioners want to manage the front

end to achieve a specific set of business related goals to benefit the

shareholders (growth, profitability, competitive advantage, and so on). Thus they

do not innovate because it is entertaining and they enjoy experiments for the

sake of experimenting. For example Bose Company knowingly wastes millions of

dollars in R&D because the CEO enjoys playing with basic research. Next, it is

assumed that companies have a general strategy for innovation (grow offering,

7

develop a competitive edge, and so on) and that innovation practioners are

working towards and aligned with their company’s goals based on a general

innovation strategy.

Finally, it is assumed that companies have some sort of preference toward

certain types of ideas because of limitations in resources, capabilities, and

people. Thus, they do not have the ability to develop every idea that comes along

nor have the desire to do so.

The second set of assumptions relate to communication and information

sharing in the company. This starts with the assumption that a company may not

share particular ideas all their idea with employees for reasons of intellectual

property or trade secrets. Next, it is assumed innovation practitioners, in the front

end, are not restricted from accessing any information related to those processes

or ideas (total free communication), and that the product portfolio accurately

shows the current projects in the development pipeline.

The third set of assumptions relates to supporting the proposed model and

are innovation practitioners can: (1) promote events; (2) have control over the

execution of activities in the front end; (3) have the freedom to select employees

they choose; (4) have reasonable discretion over the use of resources given to

them for front end activities; (5) have a general understanding of their business

environment and companies strategy and needs; (6) are competent enough to

manage; (7) have limited control over people outside their company; (8) they

cannot control the company’s culture; and (9) finally are aligned with company

goals.

The final set of assumptions relates to behaviors of employees in the

company. It is assumed that innovation practitioners do not behave maliciously

and that they do not conduct front end activities their own benefits or for

malicious intents. Also it is assumed that employees and innovation practitioners

do not exercise their decisions based on irrational biases or determinable

psychological conditions.

8

1.5. Delimitations and Limitations

For the purposes of this study, the following delimitations are to be applied. First,

the following model will be directly applicable to companies in any country or

those which have formalized innovation process for creating new products and

service industry. Also the study supporting the proposed model may be applied

to companies which conduct innovation with a heavy emphasis on process-

based management.

Several limitations apply to this study. Since this study will require self-

reporting by respondents, the reported results may not be representative of the

respondent company’s actual behaviors or practices. In other words, the

respondents may knowingly or unknowingly falsify their responses.

Given the sample size, it is not reasonable to conduct on site visits to

validate the respondent’s answers; however, check questions will be put in place

to determine discrepancies and help indicate if respondents are being consistent.

Second, the proposed control model and supporting study will not take

into account company culture, or national culture because those factors cannot

be accurately gather through a survey and almost always require primary

research to accurately obtain.

9

CHAPTER 2. A COMPREHENSIVE REVIEW OF THE LITERATURE

2.1. Literature Review of Ideas

“Man can live without air for a few minutes, without water for about five days, without food for about two weeks, and ….without a new thought for years on end.” – Kent Ruth

2.1.1. Why does the Innovation Process Need Ideas?

The goal of a company’s innovation process is to create new products and

services, or improve operations, brand, customer’s experience, supply chain

operation, and so on. Yet, every one of the mentioned concepts starts as an

idea. Ideas are a core part of the innovation process. Vandenbosch, Saatcioglu,

& Fay (2006) states “each innovation begins with an idea”, and Jack Foster

(1996) asserts “new ideas are the wheel of progress” and Linda Rochford (1991)

ideas are the raw material for product development.” Logic says, all the current

products and services were once an idea in someone’s mind. Steven Covey

(2004) calls an idea the “first act of creation” where the second act of creation is

the deed of putting an idea into a physical form.”

Obviously, ideas are vital in the innovation process, and the following

references support this point (Verworn & Herstatt, 2001; Boeddrich, 2004; Hüsig

& Kohn, 2003; Hüsig, Kohn, & Poskela, 2005; Koen, 2005; Verworn & Herstatt,

2001; Alam, 2003; Stevens & Burley, 1997; Backman, Borjesson, & Setterberg,

2007; Rochford, 1991; Vandenbosch, Saatcioglu, & Sharon Fay, 2006; Montoya-

Weiss & O’Driscoll, 2006; Flint, 2002; Crawford, Di Benedetto, 2003; Doll, 2001;

Perk, Cooper, & Jones, 2005; McAdam & McClelland, 2002). Additionally, the

large amount of books, peer reviewed articles, magazine articles, and private

10

publications on ‘how to generate ideas’ illustrate the pressing need and growing

importance of ideas in the innovation process.

Finally, common sense says organizations need ideas for the future. They

need ideas to grow their company’s offerings, capabilities, and markets.

Interestingly, this researcher would love to meet the lonely executive who says

they “do not need any great ideas to save them money, grow their offerings, or

improve their operations.”

2.1.2. Value of Ideas

Mark Fritz eloquently demonstrated the value of ideas in his quote “The wheel,

the printing press, the light bulb, penicillin, the transistor, and every other great

human invention, discovery, or social advance started with a basic idea” (Foster,

1996, p. 24). Yet not all ideas are created equal. Museums, history books, and

TV shows all celebrate humanity’s greatest ideas, and yet most people seem to

think great ideas are somewhat rare. However, if one looks around and observes

the products and services they interact with on a daily basis, one can conclude

there have been many great ideas and perhaps great ideas are not as rare as

one might think.

In companies around the world, ideas are generated every day; however,

the subjective value of these ideas vary greatly and hence a portion of the

innovation literature looks at how to locate, screen, assess and filter out less

desirable ideas (Hüsig & Kohn, 2003*; Hüsig, Kohn, & Poskela, 2005; Koen,

2005; Cooper 1994, Verworn & Herstatt, 2001; Stevens & Burley, 1997;

Rochford, 1991). Mark Fritz adds “and yet we continue to treat ideas as easy-

come easy-go disposable items not deserving the same sort of attention or

respect we give other forms of intellectual property or knowledge – like

documents, for example” (Foster, 1996, p. 21).

New areas of study such as idea management and older areas like

creativity management and innovation management have studied how

companies create, deal with, and manage ideas. Without a doubt, ideas are

11

needed for innovation and that some ideas are more valuable than others.

However, prior to reviewing the research on idea management it may be very

helpful to understand what we mean by “ideas”.

2.1.3. Defining an Idea

Given that ideas are vital for innovation, it would be helpful to understand what

an idea is. Dictionary.com defines an idea as “any conception existing in the

mind as a result of mental understanding, awareness, or activity”. American

Heritage Dictionary states it as, “something, such as a thought or conception,

which potentially or actually exists in the mind as a product of mental activity.”

Neither of these definitions shed much light on what an idea is. Let us turn, then,

to Jack Foster’s discussion of ideas in his book entitled How to Get Ideas

(Foster, 1996).

Jack Foster (1996) discusses how others have defined ideas. For

example, James Webb Young, author of the book A Technique for Producing

Ideas (1992), said “an idea is nothing more nor less than a new combination of

old elements” (Foster, 1996, p. 48). Robert Frost wrote: “What is an idea? If you

remember only one thing I’ve said, remember that an idea is a feat of

association” (Foster, 1996, p. 48). According to Francis H. Cartier, “there is only

one way in which a person acquires a new idea: by the combination or

association of two or more ideas he already had into a new juxtaposition in such

a manner as to discover a relationship amongst them of which he was not

previously aware” (Foster, 1996, p. 48). Jacques Hadamard, a famous

mathematician who proved chaotic theory, observed “that invention or discovery,

be it in mathematics or anywhere else, takes place by combining ideas” (Foster,

1996, p. 49). Arthur Koestler, author of the book The Act of Creation posited “the

thesis that creative originality does not mean creating or originating a system of

ideas out of nothing, rather out [it is] of a combination of well-establish patterns of

12

thought-by a process of cross-fertilization”, where one “uncovers, selects,

reshuffles, combines, synthesizes already existing facts, ideas, faculties, [and]

skills” (Foster, 1996, p. 49).

According to Jack Foster (1996), these definitions all highlight new ideas

as a recombination of elements of others ideas. Using the dictionary definitions

one can deduct that ideas come from people (not machines or computers) and

are a result of mental activities. Hence this researcher defines a new idea as

being conceived as a result of mental activities where previous knowledge,

information, facts, or ideas were recombined and associated in some way to form

the new idea. To further support this definition, we can try a quick experiment

where we think of an idea for a new pen. Regardless, of what type of new pen

idea we produce, we can recount it as a combination of the basic thought of a

pen and some other idea or concept. For Example:

Pen + comfort + pad = pen with a soft grip pad

Pen + color + change in temperature = pen in which ink acts like a thermometer

Pen + sound + color = pen changes color by voice activation

2.1.4. Narrowing the Definition of Ideas

What types of ideas are there? Jack Foster (1996) discusses a variety of ideas

by saying, “there are ideas for all kinds of things, idea to solve problems, ideas to

help people, ideas to save and fix and create things, ideas to make things better

and cheaper, and idea the enlighten, invigorate, inspire, enrich, and embolden”

(Foster, 1996, p. 52).Obviously the definition of an idea is very broad and can

include anything from the idea of brushing one’s teeth in the morning to the ideas

of Adam Smith in his book, The Wealth of Nations (1776).

Since this thesis deals primarily with a company’s innovation process, it is

important to define ideas. For the purpose of this research, ideas refer to

opportunities, concepts or ideas which can create value for a company. article

by Sawhney, Wolcott, & Arroniz’s (2006) cites twelve areas of innovation. This

13

article offers a great means to categorize ideas for increasing the value of a

company. Sawhney et. al. (2006) discusses innovation in the following areas:

1) Offering – products and services offered by the company

2) Platform – building blocks that can span across several of the firms’

offering

3) Solution – an integrated blend of products and services that solve a

customer’s problems

4) Customer – discovering new customers segments and groups,

uncovering unmet needs

5) Customer experience – the experience the customer has with the

companies offerings

6) Value capture – new revenue streams, changing how the customer pays,

new price systems

7) Processes –new processes or improvements in current processes’

efficiency or effectiveness

8) Organization – changes in the organization’s forum, function, structure,

and management

9) Supply chain – activities providing goods, services, and info to the firm

and customer

10) Presence – points were the customer has contact or access to the firms

products or services

11) Networking – the way company and its’ products and service are

connected to the customer

12) Brand – the symbols, words, marks, culture, and image the firm portrays

to the world

14

Rochford, (1991) suggest a similar categorization of innovations:

1) Management – organizational structure, management processes, policies

2) Strategy – how the company plans future actions

3) Employees – attracting, acquiring, retaining, training, socializing, and

motivating employees

4) Products & Services – similar to above

5) Processes – similar to above

6) Tool – the gear, machinery, models, theories, practices used by the

company

7) Technologies – the technology used and created by the firm or for the

customer

8) Suppliers – finding, selecting, leveraging, enhancing suppliers to the

company

9) Market distribution – methods of finding, distributing, delivering, supplying

the customers and

10) Brand – similar to above.

There are visible differences between the above two categorizations;

however, both demonstrate ideas create value in a variety of forms. In later

discussions on new product development it may be helpful for the reader to

restrict the scope of ideas to those which relate to new offerings. Ideas related to

offerings can be anything from a minor tweak of a product (like its color) all the

way to a release of a new product technology which creates a new market.

2.1.5. Terminology

In reviewing the literature, this researcher has noticed many articles on idea

generation may not use the word “idea”. Subsequently there are several words

which have been interchanged with the word idea such as: invention, concept,

innovation which in essence mean the same thing. Some articles prefer to use

15

the term “concept” (Backman, Borjesson, & Setterberg, 2007; Wagener &

Hayashi, 1994). Some prefer “innovation”. Some prefer the word “opportunity”.

The term, “concept”, is often interchanged with the word “idea”, but it has

a slightly different meaning. Concept generally refers to “a set of proposed

solutions complying with a set of fixed constraints” (Backman, Borjesson, &

Setterberg, 2007, p. 86). Articles like Backman, et al. (2007) and (Crawford, Di

Benedetto, 2003) use the term concept instead of the term idea.

Similarly the term “opportunity” is interchanged with the word “idea”.

Vandenbosch, et al. (2006) state that “ideas and opportunities are intertwined.

Recognizing or creating an opportunity is an occasion for generating or testing an

idea; an idea may lead to an opportunity and it may require an idea to capitalize

on an opportunity” (Vandenbosch et al, 2006, 371). Researchers should note that

in the literature, the use of the term “idea” can be spotty in relation to methods for

generation of ideas for new products or services.

To help refine the terminology associated with a project in the new product

development process Merle Crawford, and Anthony Di Benedetto (2003)

proposed the “concept life cycle model” in the figure below. This model showed

the evolution of the terms associated with a project as it met given requirements.

This strict model for the terminology associated with a project show the

terminology for an idea changes as the idea is developed. Appendix A described

each of the twelve terms in this model.

16

Figure 2.1. Concept Life Cycle Model

It is questionable whether new product development practioners will

adhere to any strict terminology. Further, the concept life cycle model may not be

followed linearly by practitioners. For example some R&D labs are known for

having prototype concepts, being a tentative physical product, including feature

and benefits, prior to having protocol concept, being a statement of the intended

market user, the problem perceived, and the user benefit.

Nonetheless, for this thesis the word ‘idea’ was chosen over the word

‘concept.’ This way the reader will not have to memorize the terms shown in the

above figure 2.1. Further, the level of an idea’s development will be clarified. For

example, an idea may be in the commercialization phase or be successfully

launched by a competitor. This should also remind the readers of the value that

ideas have in the innovation process.

2.1.6. New and Old Ideas

Another way one can look at an idea is “if the idea is new or old.” It is often

thought that a company needs to come up with new ideas, but one should not

forget old ideas may work just as well. For example, say a manager was

Market Value

Clarity

High

Opportunity concept Idea concept

Stated concept

Defined concept

Protocol concept

Batch concept Processes concept

Pilot concept

Market concept

Successful

Prototype concept

Test concept

High

17

generating ideas about how to motivate his employees. Old ideas like ‘paying

more’ or ‘conducting moral surveys’ work just as well, or even better, than a new

idea like building ‘a in house gym.’ Vandenbosch, Saatcioglu, and Fay (2006)

observe that “not all ideas are creative, nor do they have to be. In fact, successful

managers often rely on old, ordinary ideas or new, but imperfect one to cope with

the challenges they face” (p. 95).

In new product development there is an often unsaid assumption that all

newly release products should be based on new ideas. This assumption is based

on the view that customers want new things. But what often is disputed is the

meaning of new. Is the product idea new to the market, new to the world, or new

to a company? Rochford discusses this in some detail. A product can be “new”

in the sense it is either: (1) new to the firm, taking the company into new markets,

new technologies, or new production methods; (2) new to the market, the first of

its kind, what some call an innovation; or (3) new in the sense it is better for the

customer with the product yielding some net benefit to the customer. For the

intentions of this study, a new product will be defined as a product not previously

manufactured by the firm. In other words, a product is new to the firm (Rochford,

1991).

This researcher has selected new to the firm as the definition of new ideas

for this thesis. This was chosen for the three following reasons: 1) managers

often mistakenly think the product idea is new, 2) managers apply the word new

to their project to improve their social image inside the company 3) because

companies’ often increase the attractiveness of their products and services to

customer by promoting it as new.

2.1.7. Summary of Literature Review on Idea

In summary, there is a strong need for ideas so a company can grow and

develop. This requires the innovation processes to generate or obtain ideas,

where the innovation will then use these ideas to grow the company’s offering,

improve operations, improve the brand image, improve the customer experience

18

and ensure sustainability. We have defined an idea as the result of the brain’s

activities in which previous knowledge or ideas are recombined in a way forming

a new concept. The definition was further specified to describe an idea as

creating value for a company. And in specific instances of new product

development, an idea is any changes to or new product or services offered by

the company.

This section also alerts future researchers to the fact that the word “idea”

may be interchangeable with words like innovation, concept, opportunity,

technology, offerings, and other. Thus future research on things like idea

generation should take these keywords into account in their searches. Finally,

this researcher discusses new and old idea, and fell on his definition of a new

idea as being “an idea which is new to the firm.”

2.2. The Evolution of the Innovation Process

2.2.1. The Importance of Innovation

The study of innovation has gained much notoriety since the 1980s, for good

reason. Companies now realize more than ever that their ability to innovate so

strongly affects their company’s future. Books with titles like “Innovate or Die” by

Jack & Matson (1996) and quotes by greats like Drucker (1985a) ‘company have

two functions innovation and marketing everything else is just expenses’ are just

a few of the messages in the popular media which blasts that innovation is vital.

Almost all articles or books on innovation open with statistics on the value

of innovation, or logic of how innovation creates tomorrow, or even strong winded

stories of innovative companies perpetuating throughout the decades while their

competitors die off. As well, conferences around the world on the topic of

innovation, and hundreds of top management consulting firms with department

19

specializing in innovation attest to innovation’s vital function in the businesses of

today. Magazines like MIT’s Technology Review (2003) even track and rate

yearly the top R&D spenders an achiever in each industry.

Hence it would be trivial and even redundant to open with a couple

paragraphs restating the value of innovation. Funny enough, this researcher has

yet to see an article asserting that innovation is not all as important as the

popular management trends makes it out to be. Nonetheless, this researcher

must say “innovation is important and must not be ignored.”

2.2.2. A Quick History of Innovation and R&D: A Process Perspective

It is amazing how fast and how far society has advanced over the last two

centuries from the horse and carriage to landing on mars, from living in dark

candle lit wooden houses to the luminous glamour of New York’s time square

skyscrapers. With all these advances it is funny to think that the formal study of

management did not even exist until Frederick Talyor launched the movement of

scientific management in 1911. So looking back, it is amazing that the first and

second industrial revolutions (1st from 1760 to 1850 and 2nd 1860 to 1900) were

achieved without any formal knowledge of management or innovation (Ashton

1997).

Similarly, the study of R&D management is relatively young since it was

started around 1920s or 1930s. The first accounts of a true R&D lab mentioned

in the literature are that of Thomas Edison’s in Menlo Park, New Jersey. As

Andrew Hargadon (2000) posit:

From 1876 to 1881, Thomas Edison in his Menlo Park, New Jersey laboratory produced one innovation after another: high-speed, automatic, and repeating telegraphs; telephones; phonographs; generators; light bulbs and vacuum pumps. Edison built the laboratory, in his own words, for the “rapid and cheap development of an invention” and promised “a minor invention every ten days and a big thing every six months or so.” And he delivered. In a

20

single six-year period the laboratory generated over 400 patents and became known worldwide as an invention factory. - The Menlo Park laboratory was one of the first dedicated research and development facilities. Over a century later, it remains the model for R&D in modern firms (Hargadon, 2000, p. 3).

Figure 2.2. Early R&D process

The early innovation process is depicted in the figure above and it

includes generating the ideas, testing the ideas, developing the ideas, and even

launching the ideas to market. It is thought the process was managed by a

primary stake holder (like Thomas Edison) where they eliminate poor project, and

decide how to advance others (Axelrod, 2008).

As one can see, much of the process was not formalized and depended

highly upon a knowledgeable stakeholder. Hargadon mentions in his articles on

knowledge brokering that the Menlo Park lab was a room full of bright inventors

and engineers from many disciplines who talked a lot about inventions and

technology, were close, constantly experimenting, prototyping, and working

towards making world altering technologies, which they did.

At some point later, possibly in the 1930 or 1940s, companies started

adopting the concept of a funnel in their R&D process. The funnel helped

manage cost and control risk while opening up the option for evaluating and

developing many ideas. Think of it as a literal funnel where the front end catches

many ideas, and eventually through the R&D process is funneled down to a few

preferable ideas.

21

Figure 2.3. R&D Funnel

This concept greatly allows companies to explore their options while

managing risk and cost. Remember as an idea progresses through the R&D

process it accumulates greater and greater expenses. Thus, using the funnel

concept to weed out less preferable ideas helped manage cost and reduce new

product risk.

Later yet, around the 1930s or 1940s the above process was split up into

two parts 1) R&D process and 2) new product development and

commercialization processes. The R&D process was a highly random process of

discovery where the new product development processes’ was a controlled way

of developed products and services for the market. The first processes opened

up options for the company where the second analyzed, selected, and developed

the best options.

Figure 2.4. R&D Funnel and New Product and Commercialization Processes

R&D funnel Output: Discovery in

knowledge, Inventions,

New ideas for product or

services New product

development Commercialization

Market launch

Idea for new

product &

Services

Input:

Research

Decision point

R&D funnel Input:

Ideas Output: Market

22

For the most part, these were different processes, with the R&D funnel

focusing on creating discoveries in understanding, creating new knowledge,

generating novel inventions, generating new product ideas, and figuring out

where to look next. The ideas from the R&D process along with other were then

feed into the new product development processes. Again the new product

development processes function similarly to the R&D funnel described above.

Companies like IBM, Xerox, and Bell Labs were famous for having their

R&D divisions filled with geniuses and brainiacs which came up with new far-out

inventions and discoveries. Some discoveries were so great that many

researchers were awarded Nobel prizes. Figure 2.4 shows the second process

divided into new product development and commercialization. The line between

those processes represents a formal point of evaluation so that projects can be

stopped before they enter the commercialization phase. This keeps poor projects

from advancing to the commercialization phase where expenses increase

considerably. Many companies do not have the resources to support a research

division and thus typically use a new product development and commercialization

process for innovation.

The next major change in the process was the addition of the “fuzzy front

end (FFE)” by Smith and Reinertsen in 1991 and is illustrated in Figure 2.5.

Figure 2.5. Addition of the Fuzzy Front End

Murphy & Kumar (1997) state the fuzzy front end “ranges from the

generation of an idea to either it approval for development or its termination”, and

is “often chaotic, unpredictable, and unstructured” (p. 32).

New product

development

Commercialization processes Market launch

Ideas for new

product &

Services Decision

FFE

23

The goal of the fuzzy front end is to reduce uncertainty about an idea and

develop it into a concept which could be entered into the new product

development process (see definition of a concept in Appendix A). The fuzzy front

end will be mentioned at length in Sections 2.3, 2.4, and 2.5 of this thesis.

The next major development was the introduction of the stage-gate

process by Robert Cooper (2008). The stage-gate process split the new product

development process up into multiple stages where at the end of each stage

there was a formal decision point being a gate. Each gate provided the stake

holders an opportunity to evaluate a project, and then make a decision to either

end/kill the project, or advance the project to the next stage. Killing a project was

accomplished by denying funding or removing resource.

The stage-gate process served as both a guide, by requiring specific goals

to be met at the end of each stage, and a means of controlling risk, by eliminating

poor projects as more information emerged. Each stage had goals like, to have a

working prototype or proof of market demand.

Again, if the goals were not met the project would not move into the next

stage. The concepts of State-gate truly revolutionize the NPD process.

Figure 2.6. State-Gate Process in the Overall Development Process and a

Map of Project Costs as the Project Progresses

Market launch Process

Decision

FFE

Commercialization Stage Gate process for NPD

Stage in

Relative

Expenses associate

with a project

Expenses increase as project proceed

Idea for new product & Services

24

Figure 2.6 above represents the current best practices model for

developing product and services. Amazingly, according to research by Hsiao &

Chou (2004), 40% of the companies surveyed had no formalized product

development. This means that 60% of companies report having some type of

product development process. Further, it is not known what percentage is of

companies are utilizing the current best practice model, as shown above. Some

companies may include the R&D basic research process in their development

process, but most usually keep it separate from the process shown in Figure 2.6.

Typically only new product and service ideas move through the above

mentioned processes. Other ideas, like those for process or manufacturing

improvement, move through a separate process such as Kazian or total quality

management and other ideas, like branding or value capture, may be developed

through their own unique processes.

The market launch process shown in Figure 2.6 is depicted as an

expanding cone to denote the additional costs and activities associated with a

market launch. Further, the chart in Figure 2.6 shows generally how expenses

rise in each respective stage. Current development models try to reduce risk and

uncertainty while expanding options for a company.

A recent article in Harvard Business review, entitled the “Innovation Value

Chain” by Hansen & Birkinshaw (2007), shows the innovation process as a

series of linked processes, where if any link is weak the whole innovation

processes is negativity affected. They emphasize that there are “no universal

solutions for organizations wanting to improve their ability to generate, develop,

and disseminate new ideas” (p. 15). As well, they emphasize “managers need to

take an end-to-end view of their innovation efforts, to pinpoint their particular

weakness, and tailor their best practices appropriate to their deficiencies.”

25

Figure 2.7. Innovation Value Chain

Figure 2.7 shows the innovation value chain as being divided into the

three major areas of idea generation, conversion, and diffusion. Idea generation

is composed of generating ideas in-house; cross-pollination is getting different

divisions and units to collaborate to combined knowledge and insight; and

external sourcing is getting ideas from outside the organization.

Conversion is composed of selection and development. Selection is

screening idea, analysis idea, and initiating funding for given ideas. Development

is transforming an idea or concept into the required final form. Finally, diffusion

involves spreading the idea around the organization so that the crucial share

holders involved in the market launch and operational activities commit to the

idea.

The innovation value chain model is not so much a process model as a

model describing the vital goals in each phase. The innovation value chain can

also be used to analyze how the best practices models fit and is performing in a

company’s development process. For example, the stage-gate process can be

seen to fit in both the selection and development areas. Whereas the PAC

approach, in which a product approval committee is used to select and screen

projects, would only be applicable to the selection of projects and cannot be used

to guide development (Koen 2005). One can see the genius in leaving the model

broad because it allows a company to tune its innovation value chain to the most

effective processes instead of blindly following the best practices models.

26

Hansen & Birkinshaw (2007) focused on diagnosing a company’s

innovation value chain, which is very helpful because few articles offer any

diagnostics tools for innovation. They described different deficiencies in

companies as delineated below:

1) Idea-poor companies are company, which spends a lot of time and

money developing and diffusing mediocre ideas which result in

mediocre products and financial returns. The problem is in idea

generation, not execution.

2) Conversion-poor companies has lots of good ideas, but managers

don’t screen and develop them properly. Instead, ideas die in

budgeting processes which emphasize the incremental and the certain,

not the novel.

3) Diffusion-poor companies have trouble monetizing their good ideas.

Of course a company can be weak in any one or more of these areas, hence the

authors offer references to other articles which discuss solution to improving a

specific part of the innovation value chain. Finally, the article ends by stating that

companies should benchmark and record statistics on each part of their

innovation value chain, so they can monitor performance and make specific

improvements.

2.3. Research on the Fuzzy Front End

2.3.1. Intro to Section on Fuzzy Front End

The term the ‘fuzzy front end’ is ambiguous and may elicit many questions like,

“what does the term mean?”, “what take place in the fuzzy front end?”, “why is it

important to research?” or “why should innovation practitioners care about it?”

This chapter addresses many of these questions and attempts to clarify what the

fuzzy front end is, and what type of research has been done on it to date.

27

2.3.2. Terminology for the Fuzzy Front End

As mentioned, the beginning of the innovation process is the main focus of this

thesis; however it goes by many names. The term the fuzzy front end was

popularized by Smith and Reinertsen in 1991, and was used since the word

“fuzzy” describes how chaotic, unpredictable, and uncertain this part of the

innovation processes can be (Koen 2005). However, there are several other

terms which were applied to describe this phase of innovation such the ones

listed below.

Front end of innovation,(Nobelius, 2000; Front End of Innovation

Conference, 2008; Koen, 2005; Koen, 2001) Early stages of the product

development (Nobelius, 2000; Khurana and Rosenthal,1998), early phases of

innovation (REF C3), early innovation phases (Lichtenthaler, Savioz,

Birkenmeier, & Brodbeck,2004), Pre-development (Hüsig & Kohn, 2003),

advanced development, Pre-project activities, (Hüsig & Kohn, 2003), Pre-phase

0, (Khurana and Rosenthal,1998).

The fuzzy front end of innovation or, for the sake of brevity, ‘front end of

innovation or FFE’ has many definitions in the literature, most of which define it

by stating the type of activities which take place in it. Basically, FFE involves

“activities taking place prior to the formal, well-structured new product process

development” (Koen, 2005; Koen et al., 2001, p. 3). Other similar definitions are

Reid & Brentani’s (2004) where the FFE “is considered to be the earliest stage of

the new product development (NPD) process and roughly is meant to denote all

the time and activities spent on an idea prior to the first official group meeting to

discuss it or what they call ‘the start date for team alignment” p. 5). Others

define it in terms of the activities which take place. Murphy & Kumar (1997)

define the front end as ranging “from the generation of an idea to either its

approval for development or its termination” (Verworn & Herstatt, 2001, p. 53).

A lengthier definition by Crawford and Di Benedetto (2000) is the fuzzy

front end’s “early activities are broad and include opportunity identification and

exploration, while later activities consist of information collection and concept

28

development preparing it for the transfer into the NPD process” (Backman,

Borjesson, & Setterberg, 2007). Yet, Khurana & Rosenthal define the front end

“to include product strategy formulation and communication, opportunity

identification and assessment, idea generation, product definition, project

planning, and executive reviews” (Verworn & Herstatt, 2001, p. 83). As well, Kim

& Wilemon (2002) define the FFE as “when an opportunity is first considered

worthy of further ideation, exploration, an assessment, and ends when a firm

decides to invest in the idea, commit significant resources to its development,

and launch the project (Kim & Wilemon, 2002, p. 31). Finally, Hüsig and Kohn

(2003) and have the most elaborate activity based definition of the FFE which

has lists of both exclusive and inclusive activities. Yet a comparison of the fuzzy

front end to the NPD process in table form seems to be one of the best ways to

understand what the fuzzy front end is, see Tables 2.1 & 2.2 below.

Table 2.1. Koen et al. Activities in the Front End of Innovation

and New Product Development Processes

Table 2.2. Koen et al. Factors and

and New Product Development Processes

2.3.3.

The activity-based definitions can give one a slight understanding for the

activities which take place in the FFE; however, further

According to Verworn & Herstatt

strategy formulation, communication, opportunity identification and assessment,

idea generation, product definition, pro

(Verworn & Herstatt, 2001,

activities are generation of ideas, initial screening, preliminary evaluation, and

concept evaluation” (p.11)

phases for the FFE being “1) idea phase 2) feasibility and potential phase and 3)

concept development phase. Interestingly, thi

state:

Activities do not occur in a specific order: It is important to note that these three different phases and gates differ from the normal stagegate process in some extent. First of all they are not a sequential order of activities that are followed through development process. This can happen, but in general the teams

Factors and Characteristics of the Front End of Innovation

and New Product Development Processes

2.3.3. Activities in the Front End of Innovation

based definitions can give one a slight understanding for the

place in the FFE; however, further clarification is needed.

Verworn & Herstatt (2001), the tasks in the FFE are, “product

strategy formulation, communication, opportunity identification and assessment,

idea generation, product definition, project planning, and executive review

Verworn & Herstatt, 2001, p. 383). Cooper’s (1988) article concludes the main

activities are generation of ideas, initial screening, preliminary evaluation, and

(p.11). Similarly, Hüsig and Kohn (2003) states

phases for the FFE being “1) idea phase 2) feasibility and potential phase and 3)

concept development phase. Interestingly, this Husig, Kohn, & Poskela

Activities do not occur in a specific order: It is important to note that these three different phases and gates differ from the normal stagegate process in some extent. First of all they are not a sequential order of activities that are followed through like in the following development process. This can happen, but in general the teams

29

the Front End of Innovation

based definitions can give one a slight understanding for the

clarification is needed.

the tasks in the FFE are, “product

strategy formulation, communication, opportunity identification and assessment,

planning, and executive review”

article concludes the main

activities are generation of ideas, initial screening, preliminary evaluation, and

states general

phases for the FFE being “1) idea phase 2) feasibility and potential phase and 3)

s Husig, Kohn, & Poskela (2005)

Activities do not occur in a specific order: It is important to note that these three different phases and gates differ from the normal stage-gate process in some extent. First of all they are not a sequential

like in the following development process. This can happen, but in general the teams

30

working in the front-end works on several parallel projects, and redirects ideas and concepts from one stage to another. While in the development stage-gate process the redirection of projects is more an exception, it is more the rule in the front-end (Hüsig and Kohn, 2003, p. 11).

Furthermore,

Concept and ideas merge, and activities are continuous in nature: for each opportunity that seems worth pursuing several ideas will be developed. Those ideas will be combined to one or more concepts. This implies that the subject of analysis keeps changing over the process. Therefore this process model is rather a representation of continuous activities that permanently go on in order to fill the NPD pipeline (Hüsig and Kohn, 2003, p. 14).

This researcher strongly agrees that the activities of the FFE do not occur

in a specific order, partially because of the work of Koen et. al. (2001) but also

because of the large observed variation in activities noted in case studies on the

FFE. This researcher also strongly agrees with the continuous nature of the FFE,

which is also represented in Koen et al’s model.

2.3.4. Importance of the FFE

One might ask what is the importance of the fuzzy front end in the innovation

process. Kahn the editor of PDMA handbook (2003) and an authority on

innovation and new product development states that he “sees the front end as an

important issue in future research on product development 2003” (Verwon,

Herstatt, & Nagahira, 2008). Also, “Rice calls the fuzzy front end ‘the root of

success’ for discontinuous product innovation” (Verwon et al., 2008, p. 32). More

importantly, an extensive empirical study by Cooper & Kleinschmidt (1994)

showed, “the greatest differences between winners and losers were found in the

quality of execution of pre-development activities” (Verworn & Herstatt, 2001, p.

43).

31

Furthermore, Backman, Borjesson, and Setterberg (2007) posit that “the

greatest opportunities for improving the overall innovation process lie in the very

early phases of NPD” process (Backman, Borjesson, and Setterberg, 2007, p.

52). Hence, Zhan and Doll (2001) states, “managers and researchers claim the

benefits resulting from improvement in the front are likely to far exceed those that

result from improvements aimed directly at the design engineering process”

(Zhan & Doll, 2001, p. 73).

Kim and Wilemon (2002) state “the importance of the FFE lies in the fact

that effectively performing front-end activities can contribute directly to the

success of a new product” (p. 32, Cooper 1988, 1998; Dwyer & Mellor 1991;

McGuiness & Conway 1989). As well they state, “one can find several low cost

opportunities to achiever large improvement in time-to-market” (Kim & Wilemon,

2002, p. 33).

However, only a few references state why it is so important. To prove the

value of the FFE Cooper and Kleinschmidt (1994) found that pre-development

activities received the least amount of attention (only at 6% of dollars and 16% of

man-days of the total) when compared to the product development and

commercialization stages. Interestingly, when they compared successes to

failures they found about twice as much money and time is spend for the front

end stages. Although the importance of the early development phase is

recognized, researchers and practitioners still focus on the later phases of the

innovation process, where information is more reliable (Verworn & Herstatt,

2001). It seems there are some concerns related to failure rates of projects in the

FFE as alluded to by Khurana & Rosenthal (1998) who commented that “most

projects do not fail at the end; they fail at the beginning” (Khurana & Rosentha,

1998, p. 1).

Unfortunately, a review of the literature failed to produce a list of

compelling reasons which support the importance of the FFE. Thus, this study

begins with developing categories that reasonably capture the importance of the

FFE. The first category of reasons concerns the costs involved in the innovation

32

processes. As mentioned above, a single idea may be cheap to develop and

analyze in the FFE but as Cooper and Kleinschmidt state cumulatively

developing and analyzing many ideas over time may show the FFE is a larger

expense than previously thought.

Second, the fuzzy front end is directly responsible for getting valuable

ideas into the innovation value chain or new product development (NPD)

processes. The old adage ‘trash in trash out’ applies well to the innovation

processes. The value and quality of the ideas going into the new product

development process is a major limiting factor affecting the quality of products

and services ready for market launch. Thus, researching the FFE to determine

how to get a high quality stream of ideas into the NPD processes is a creditable

research goal.

Third, it is clear that in reducing the amount of uncertainty through the FFE

activities, we achieve better results in terms of concepts, project plans, and

selections of tasks for the project as it moves into the new product development

process. In other words, the more information a new product team knows, and

the less uncertainty they have, the better they can optimize costs and plans for

subsequent new product development activities.

Lastly, the organizational fit and organization’s commitment to a new idea

is the final category of importance for FFE. Having a deep understanding of the

fuzzy front end will allow companies to generate ideas, then select or screen

ideas and concepts which fit with the company’s capabilities and strategies. As

well, it will allow companies to put in place the people, management, teams,

culture, incentives, and other mechanisms which are considered vital to obtained

ideas and pushing them through to market launch.

2.3.5. Deliverable at the End of the Fuzzy Front End

One might move on to ask, “What are the deliverables at the end of the fuzzy

front end?” And it is unfortunate, but this question has not been answered in

much detail in the literature. Cooper (1993) says, “one goal of the FFE is the

33

creation of a well defined product concepts prior to development” which seem

obvious given the NPD process requires a clear concept to proceed (p. 13). This

statement corresponds to Murphy & Kumar’s (1997) quote “empirically [it was]

found that the most important objective of the FFE is to understand project

requirements and … to have a clearly defined product [concept] prior to

development” (p. 1). Kim & Wilemon (2002) add the “selection of the right

opportunity” should also be an outcome (p. 3). Unlike others, Koen et al. (2001)

adds that an output for FFE should be the generation of intellectual property.

A review of the literature suggests several deliverables:

1) a clear product concept

2) knowledge and understanding required to develop the product concept

3) selection of the right/best idea/concepts

4) a strong business case

5) a development plan required to managed the NPD activities, and

6) assets such as intellectual property or working prototypes.

Deliverables for the FFE may vary widely from industry to industry. This is

because there are large differences in the expenses associated with NPD

phases amongst different industries. For example a fashion design firm may only

require a set of sketches to move a new line concept into the NPD processes;

whereas, a microchip manufacture may require a patentable invention, a clear

product concept, and proof of market demand prior to allowing the large cost of

the NPD process to be incurred. Nonetheless, it would be interesting to see a

comparative study of the require deliverables at the end of the FFE process.

2.3.6. Structured vs. Unstructured Fuzzy Front End

There has been some debate over whether a structured or unstructured fuzzy

front end was better for front end success. Some researchers argued that a

structured FFE was preferable (Hüsig & Kohn, 2003; Deliotte, 2006; Kahn,

Kucmarski, & Johnston, 2005; Flint 2002) while others argued un-structured was

34

preferable (Verworn & Herstatt, 2001). However, it seems this question has been

laid to rest by Husig, Kohn, & Poskela’s (2005) article in which they empirically

showed that having a structured front end creates better FFE results.

Interestingly, they mentioned financial success as a poor indicator for the

success of FFE, because of the large lag time associated with it. Also financial

success depended upon the processes after the FFE as was mentioned in the

innovation value chain article. Husig, Kohn, & Poskela (2003) used the following

measures of success for the FFE as being: (1) the number patents per

employee, (2) improved technical info, (3) better market information, (4)

managers more satisfied with the results FFE of the NPD, and (5) a better patent

portfolio.

The study supported the finding that structured FFE processes resulted in:

better technical and market info, created more satisfying FFE results for the NPD

managers, and better patent portfolios. Interestingly, they found that basing

results on the number of patents generated by employees was a bad measure of

success because each industry produces different number of patents.

Nonetheless, one of the underlying goals of the study of management is to

provide a means of controlling and managing activities inside a business, thus

even something as chaotic as the fuzzy front end can benefit from further

analysis.

2.3.7. Quick Review of Research on the Fuzzy Front End

To date (2008) there has been a fair bit of research conducted on the fuzzy front

end (FFE); however, in comparison to the research on the new product

development process, the FFE is relatively lightly researched. The type of

research in the FFE includes: theoretical pieces, case studies, primary survey

research, and applications of particular methods. Please note any reference with

an asterisk (**) next to it represents a comprehensive reference on that topic

area.

35

Ø Culture of the FFE (Hüsig & Kohn, 2003**; Koen, 2005; Zien & Buckler,

1997**; Kohn, Ernst, & Husig; 2006**, Koen et all 2003**)

Ø Management of the FFE (Kim & Wilemon, 2002**; Hüsig & Kohn, 2003**;

Hüsig, Kohn, & Poskela, 2005; Chang, Chen & Wey, 2007**)

Ø Strategy in the FFE (Verworn & Herstatt, 2001; Hüsig & Kohn, 2003**;

Cooper, 1998**, Copper, 1984c)

Ø Screening of idea in the FFE (Kim & Wilemon, 2002; Hüsig, Kohn, &

Poskela, 2005; Montoya-Weiss & O’Driscoll, 2006; Flint, 2002; Koen et al.,

2001; Cooper, 1998)

Ø Resource for FFE activities (Koen, 2005; Montoya-Weiss & O’Driscoll,

2006; Zien & Buckler, 1997; Adam-Bigelow, 2003**)

Ø Processes and activities in the FFE (Verwon, Herstatt, & Nagahira,

2008; Kim & Wilemon, 2002; Hüsig & Kohn, 2003**; Alam, 2003**;

Moskowitz,1997).

Ø Planning (Hüsig, Kohn, & Poskela, 2005)

Ø Uncertainty & analysis (Verwon, Herstatt, & Nagahira, 2008; Kim &

Wilemon, 2002; Hüsig, Kohn, & Poskela, 2005; Montoya-Weiss &

O’Driscoll, 2006; Flint, 2002; Koen et al., 2001; Cooper, 1998)

Ø People in the FFE activities (Kim & Wilemon, 2002; Hüsig & Kohn, 2003;

Hüsig, Kohn, & Poskela, 2005; Stevens, Burley, Divine, 1999**)

Ø Communication in the FFE (Reid & Brentani, 2004; Hüsig & Kohn, 2003;

Moenaert, Meyer, Souder, & Deschoolmeester, 1995)

Ø Teams in the FFE (Kim & Wilemon, 2002; Hüsig & Kohn, 2003**;

Stevens, Burley, & Divine, 1999)

Ø Idea generation in the FFE (Hüsig & Kohn, 2003; Hüsig, Kohn, &

Poskela, 2005; Flint, 2002; Montoya-Weiss & O’Driscoll, 2006**)

Ø Success Factors for the FFE (Verworn & Herstatt, 2001; Hüsig & Kohn,

2003**, Cooper & Kleinschmidt 1993 c, 1995 a, b, c,

Ø Learning effect in the FFE (Verworn & Herstatt, 2001)

36

Hüsig & Kohn’s (2003) article entitled “Factors influencing the front end of the

innovation process” is a comprehensive review of selected empirical NPD and

explorative FFE studies up till 2003. Anyone seeking an overview of research on

the FFE or a specific set of references on a particular FFE area is recommended

toward this article.

2.3.8. Summary of Research on the FFE

To summarize, this section started by reviewing several terms used to describe

the fuzzy front end, where in this thesis the terms “front end of innovation”, “fuzzy

front end” and “FFE” will be used. Second, a range of definitions were reviewed,

of which this researcher preferred the definition of the FFE to be “the set of

activities taking place prior to the formal, well-structured new product

development process.” Third, the importance of the fuzzy front end was

examined and elaborated on. The importance of researching the FFE can be

seen in its link and outcomes of: (1) improving return on investment in front end

activities, (2) ability to develop high quality stream of ideas, (3) reducing

uncertainty and risk associated with projects, and (4) fitting ideas to the company

and their context.

Fourth, the deliverables for the FFE were identified as: (1) a clear product

concept, (2) general knowledge and understanding, (3) the selection of the best

or most appropriate ideas, (4) a business case, (5) a new product development

plan, and (6) intellectual property. However, the area of FFE deliverables is still

viewed as one requiring future research. Fifth, the debate of whether a structured

or unstructured fuzzy front end was put to rest by Husig, Kohn, and Poskela’s

(2005) research which strongly supported a structured fuzzy front processes.

Finally, a review of the research topics on the fuzzy front end was presented with

the intent of demonstrating which major areas have been researched to date.

37

2.4. Review of Process Models for the Fuzzy Front End

2.4.1. Intro to Section

The following section reviews several process models for the fuzzy front end,

with the goal of understanding what processes can take place, how they are

ordered, and why. Second, the strengths and weaknesses of each model will be

reviewed, so one can understand where improvements in the process models

are needed.

2.4.2. Review of FFE Process Models

As mentioned earlier, this researcher will concentrate on the process side of the

fuzzy front end because he sees a great opportunity to strengthen it. Thus, a

review and critique of process models for the front end of innovation is very much

needed. To date there are several process models for the FFE and there is great

variation amongst them in their form, emphases, and appearances.

Also, most FFE models also have a visual model associated with them to

illustrate how they function. It seems many managers prefer to have rather

simple visual models of the process because, 1) it helps them understand how

the processes work, 2) the visual model helps them communicate the process to

the employees who will be using it, 3) it allows for a quick reference and finally,

4) it allows one to quickly understand how the parts of the process tie together.

However, one should always remember a model is a simplification of the

thing it represents, and something as complex as the fuzzy front end may not

translate into a simple visual model. Consequently, every line, object, symbol,

shape, color, and forum in a visual model can suggest some type of relationship

which may or may not be intended by the model’s creator. This is why creating

visual models may sometimes be a very difficult task. Nonetheless, this chapter

reviews the process models for the fuzzy front end along with the associated

visual models for their effectiveness.

38

2.4.3. Innovation Value Chain

The first model to be examined is the innovation value chain by Hansen, &

Birkinshaw (2007). Although this model does not concentrate on the in particular

fuzzy front end, it is useful because it gives a holistic overview of the innovation

processes, and broadly can take into account any of the twelve mentioned

innovation types by Sawhney, Wolcott, & Arroniz (2006).

The model shown in figure 2.8 is not so much a process flow model, but it

is designed to show the major activities which should take place as an idea

moves towards market launch. The true value in the innovation value chain is its

holistic view showing the innovation process as an integrated link of activities.

With this view point, the authors emphasize that companies should not be

concentrating so much on their innovation strengths but rather should focus on

their innovation weaknesses. Additionally, their article gives a framework to help

practitioners diagnose their own innovation value chain.

The visual representation of their model, shown below, concentrates more

on the general activities taking place rather than more specific activities as

shown in other process-flow models. This is advantageous because it allows the

model to show the general activities across many industries, but it can also be a

downside because it does not provide a prescription of the exact activities to be

carried out. However, again it seems this model was meant to be used more as a

tool for analysis then as a guide.

Figure 2.8. Visual Depiction of the Innovation Value Chain Model

Development Spread the ideaCross-pollination External sourcingIn-house idea generation

Selection

DiffusionConversionIdea Generation

Compares roughly to the

Fuzzy Front End processes

39

This model consists of three main areas: (1) idea generation, which is not

similar to the idea generation activities which will be discussed in later sections,

(2) conversion, and (3) diffusion. The authors describe idea generation as an

area in which ideas are created or obtained. Next, conversion is described as the

selection of ideas and development of ideas. Finally, diffusion is the act of

spreading a concept across the organization, getting commitment from key

parties, and readying the company for market launch and support activities.

Hansen & Birkinshaw (2009) eloquently describe examples of companies

which were poor performers in any one of these three areas, and explain how a

company may remedy the problems in these areas to improve its overall

innovation process.

Figure 2.8 shows which parts of their model overlap with the FFE. As can

be seen in Figure 2.8 the idea generation activities are broken up into (1) in

house idea generation, where the ideas are created in the company, (2) cross-

pollination where ideas are generated between business units or departments

and (3) external sourcing where ideas are created outside the organization.

The innovation value chain model is one of the few models which

highlights the multiple sources of ideas, and allows companies to analyze how

they are getting their ideas. Further, the authors suggest a solution to improving

cross-pollination by utilizing cross-unit networks, and solutions to fixing external

sourcing by utilizing solution networks and/or discovery networks which are often

referred to in the literature on open innovation.

However, the downsides of this model are it does not go in to detail about

the exact activities which take place. For example, in-house idea generation does

not highlight what employee groups or departments are creating, how they are

creating it, or describe the flow of activities. Additionally, the overlapping line

(see Figure 2.8) for the FFE was drawn in the middle of the development area

because the FFE only develops a concept to a particular degree before it is

passed into the NPD processes.

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Next, the conversion activities are divided into: (1) selection, where ideas

are screened, selected, and funded; and (2) development, where ideas are

developed into launch-able product and service. Now, the famous Stage-Gate

model integrates the functions selection and development together in-order to

reduce risk and cost; however, this model shows those activities to be separate.

So again, this is not a process flow model, but a more general model for the

activities which should be taking place. Interestingly, the authors label companies

with different weaknesses as being: idea-poor companies; conversion-poor

company; and diffusion-poor companies and suggest further readings to help

eliminate those weakness. Again, the focus of this thesis is on improving the

sourcing, generation, and selection of ideas inside a company, so this model can

be viewed as highly appropriate. As well, this model is particularly helpful in that

it allows practitioners to assess their companies own innovation processes.

The innovation value chain could also lead to diagnostic methods of

improving innovation in companies much like a doctor treats a patient. The

process would follow steps, were (1) diagnosis performed on the company, (2)

problems would be located, and (3) the appropriate solution is applied. The

diagnosis, problem, and solution process is also widely used by organizational

development experts to improve company’s performance in all areas. However,

for this type of process to be used many more types of diagnostic tools must be

created for the innovation process.

2.4.4. Cooper’s Stage-Gate Process Model

Cooper’s stage-gate process model is probably the most famous of the new

product development processes because it balances risk and expenses. Cooper

(2008) has mentioned the stage-gate model has undergone substantial

evolutions from its initially introduced; however, it is still based on the concept of

stages and gates.

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Figure 2.9. Visual Depiction of the a Stage in the Stage-Gate Model

Figure 2.9 above shows a stage as a set of activities, then analysis,

followed by a number of deliverables. Once a certain point is reached, the

deliverables are used by a gatekeeper. A gatekeeper is usually one or more

individuals who analyze the project to determine if it should go on to the next

stage. The gatekeeper can continue the project by providing funding, or kill a

project by withholding additional funding and/or by removing vital resources.

According to Cooper (2008), a gatekeeper can require a project to repeat the

stage or hold the project at a gate. However, holding a project at a gate should

be minimized or eliminated altogether, because it can stall the overall innovation

process, and definitely slows the stage-gate process.

Figure 2.10. Full Stage-Gate Process Model

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The full model for the Stage-Gate process is shown above in Figure 2.10

with five formal stages, and five formal gates. The process starts with the

discovery of an idea or concept. As with any process model, the item moving

through the process is understood to be an idea. The most recent article by

Cooper (2008) on the stage-gate process reviews many of the misconception,

miss-uses, and major errors its implementation.

One of the more important misconceptions is in the functionality of the

process itself. The state-gate process is meant to funnel the number of

development projects down, killing off the poor projects before they accrue too

much cost and use too many resources. Hence, each gate is not a review point

for the project or a milestone, it is an clear point were decision makers who

control the resources have the option to kill off projects which do not meet the

grades set by the company! Simply, the gates should be a way of killing off poor

projects early and often.

The gates in Figure 2.10 each test to see if different goals and objectives

have been met, and gates like gate 4 for example test to see if the project is

developed enough to warrant the expenses of testing which would take place in

stage 4.

The benefit here as Cooper posits, is that “no activity or deliverable is

mandatory: the stage-gate [process] is a guide that suggests best practices,

recommended activities, and likely deliverables. But the project team has much

discretion over which activities [they] executes and which [they] choose to not to

do. Every project is unique and merits its own action plan” (Cooper, 1998, p. 3).

This is also beneficial because having a guide speeds up development while it

reduces portfolio risk as the multiple projects precede through the development

pipes.

Below is a table taken from Verworn & Herstatt (2002) which gives a quick

overview of the checks at each gates and activities for each stage. Appendix B

illustrates activities at each stage and gate. A systematic process like this gives

the product development team a clear guide about what activities need to be

43

performed and what risks should be minimized as the project progresses. As

well, the gates can be viewed as a means of motivating the development team by

giving them clear short term goals.

Interestingly, Cooper (2008) notes the stage-gate process can be

shortened by reducing the number of gates for a project which have lower risk,

thus expediting the innovation process. The goal of the stage-gate process is to

help guide development and eliminate poor projects. Hence, it makes sense to

let projects with the greatest potential for success, accelerate through the

process, by-passing obviously unnecessary decision gates.

Table 2.3. Specific Activities and Decisions for Each Stage and Gate

∆Gate 1 • Company set criteria

Stage 1 • Preliminary assessment of market, technical requirements, and some soft

financials

∆Gate 2 • Meet criteria of gate 1 plus rough market, technical requirements

Stage 2 • Detailed market study, operation, legal review, detailed technical

appraisal, business case, product definition, project justification, and

project plan

∆Gate 3 • Meet criteria of gate 1 and 2, quality checks on activities, financial check

Stage 3 • Product development, product testing, marketing and operational plans,

cost analysis, preliminary market and customer feedback

∆Gate 4 • Meet criteria of gates 1,2 and 3 quality check on activities, check on result

of stage 3 activities

Stage 4 • In house testing, full customer testing, trial production, full business case

∆Gate 5 • Overall detailed financials, business check points, quality check on

previous activities, action plan for market launch

Stage 5 • Launch, implementation, and operational plans

Review • Compare actual results with project result for the project

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Figure 2.11. Options for Sage Gate Process

Cooper (2008) says the visual model depicts stages as being of equal

time where in fact they should not be. Stages at the beginning should be

relatively low cost and should not contain anywhere close to the amount of

activities as stages taking later in the process. One issue with the stage-gate

process is the visual model shows it as a linear process. However, there are

large amounts of looping and iterations within in each stage. Activities can, and

should, often overlap between stages. To illustrate this, Figure 2.12 shows

stages as pie graphs depicting the percentage of energy and money which

should be spent on specific activities. The size of the pie corresponds to the

respective amount of cost or time spent in that stage.

Visually-speaking, Figure 2.12 is a clearer guiding process than the simple

stage boxes in Figure 2.10, because it depicts the ratio of the activities at each

stage. Also, companies should keep in mind that they will need to set the

activities and requirements of each gate, and not blindly follow a recommended

set of activities for each stage.

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Figure 2.12. Pie Charts Depicting Activities in Each Stages

Cooper (2008) states that the process is a macro-scale guide and not a

means of controlling a project. Control should be performed through project

management which is a micro-scale activity. Finally, the last stage of post review

was added to insure the development process was conducted properly.

Amazingly, the stage-gate process was adapted to work with the open

innovation process by forwarding an idea, based on its level of development, to

the appropriate stage in the innovation process. Hence, fully developed product

market concepts (see appendix A for definition) can be placed directly into stage

5 (development) of the stage-gate development process.

2.4.5. Downsides of the Stage-Gate Model

Regardless of the strengths, the stage-gate process does have some major

downsides. First, this model relies on some type of discovery of ideas to occur.

Other fuzzy front end models include opportunity identification and idea

generation (for instance, the innovation value chain) whereas, stage-gate does

not. The stage-gate model misses what Crawford and Di Benedetto (2003) call

the early front end activities. Even though this model is very good at balancing

reward and risk, it is far from holistic because it is missing all of the early front

end activities.

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A later part of this section will review the activities and tasks which should

take place in the fuzzy front end. In that review, one will note there is still much

disagreement about which tasks and activities should be taking place in the FFE.

Also some author mentions that judging a concept to early will kill it prematurely

before it has a chance to grow into something more solid. So as a guide, the

stage-gate model is very weak for the FFE, because it lacks specifics about

which activities should actually take place.

Another problem is that the front end activities often spawn “better” ideas

for new products and services and the current stage-gate model does not show

how those ideas can be managed. Finally, the stage-gate process does not show

how knowledge management, idea generation, creativity management, company

strategy, and idea management play into the processes.

2.4.6. Khurana & Rosenthal FFE Model

The article by Khurana & Rosenthal (1998) titled “towards holistic ‘front ends’ in

new product development” reviews how strategy impacts the projects in the fuzzy

front end. They found from studying 18 business units that the most successful

units linked business strategy, product strategy, and product-specific decisions to

the FFE.

Interestingly, their research showed new product projects in the front end

can be aligned to the company’s strategy by means of the company’s culture or

the company’s processes. Further yet, Khurana & Rosenthal (1998) article shows

how strategy link to 1) product strategy, 2) product definition, 3) project definition,

and 4) organizational roles.

For alignment using culture, they discuss how Japanese firms tend to

align product projects with all four of the items mentioned above whereas, in

European and American firms, the alignment of a project with strategy and

product portfolio is done by using a process approach. Hence, they say both

47

process and culture are viable models for achieving a holistic front end. This is a

great step forward toward creating process models for managing the fuzzy front

end.

Their model is illustrated below. It shows how idea generation, preliminary

opportunity identification, and portfolio strategy affect the front end.

Unfortunately, this figure was introduced more as an illustration than as actual

way to summarize their findings.

Figure 2.13. Khurana & Rosenthal FFE model

Phase zero and Phase one shown in figure 2.13 are not well defined,

according to authors Backman, Borjesson, & Setterberg (2007). Phase zero is

when a core group is assembled to assess the basic customer needs, evaluate

the technology, and see how the technology fits with the business capabilities,

identify core requirement, test the concept, specify required resources, and

identify the risks. Again, this article is valuable because it links how business

strategy, portfolio strategy, and product definitions impact the project in the fuzzy

48

front end. However, this is not by any means a formulated process which can be

followed, but it does indicate that success can be achieved through the use of

processes in the fuzzy front end.

The value of this model is in showing how strategy can impact the

processes of the fuzzy front end. Unfortunately, they do not discuss what they

consider as success for a front end activity. The Husig, Kohn, Poskela (2003)

article entitled “The Role of process formalization in the early phases of the

innovation process”, went to great lengths to defined success in terms of metrics

which were measurable and applicable to just the fuzzy front end.

There are many downsides to this model but since its goal was mainly to

show how strategy can influence processes in the fuzzy front end, there is not

really much sense in listing all its downsides as a full process model.

2.4.7. Deloitte’s Spiral Model

The Deloitte spiral model deserves mentioning even though it was not introduced

through the formal product development or innovation literature. The Deloitte

spiral model developed by Deloitte & Touche is a process based model for

innovating in the fuzzy front end (Gallagher, George, & Kadaki, 2006).

The Deloitte consultants observed that incremental innovations tend to be

selected for development over disruptive innovations. This is because metrics

like financial metrics (ROI and NPV) and market metrics (like customer

preference) used to evaluate and select ideas naturally prefer incremental

innovations over disruptive innovations because those metrics have a poor time

dealing with uncertain information. Thus they state, incremental innovation

processes concentrate more on finding a good innovation rather than building

one.

Figure 2.14

The Deloitte consultants state,

resources on building a winning [disru

one” (Gallagher, George, & Kadaki, 2006

“sorting through ideas more often than not [in their observations] proves fruitless”

for disruptive ideas (p. 3)

should be developed from an understanding of customer needs

generated idea by quality not quantity.

pronounced spiral like feature to it, where ideas start at the middle then move to

the outside. The first, activit

14. Visual Depiction of the Delottie’s Spiral Model

consultants state, “it is important to focus efforts and

resources on building a winning [disruptive] idea rather than counting on finding

Gallagher, George, & Kadaki, 2006 p. 2). Interestingly, they state

“sorting through ideas more often than not [in their observations] proves fruitless”

(p. 3). Hence, they emphasize that disruptive innovations

should be developed from an understanding of customer needs and focus on

idea by quality not quantity. Their model shown in Figure

pronounced spiral like feature to it, where ideas start at the middle then move to

activities in the center of the spiral are dictated by the

49

odel

“it is important to focus efforts and

er than counting on finding

they state that

“sorting through ideas more often than not [in their observations] proves fruitless”

disruptive innovations

and focus on

igure 2.14 has a

pronounced spiral like feature to it, where ideas start at the middle then move to

in the center of the spiral are dictated by the

50

company strategy which guides the examination of user needs to particular target

market segments. However, it is unclear whether the spiral process starts with a

target market or a seed idea.

The following activities can be seen in the illustrated model ending at a

go/no go gate. If the project meets the objectives of the gate the process

continues on again. The process emphasizes a holistic view of the innovations

processes by looking at (1) user needs, (2) technical/partnering potential (3)

commercialization considerations (4) organizational implications. The building the

idea process of the Deloitte spiral is shown to end with a concept going into A)

the NPD process, B) an alternative organization, or C) a spinoff company.

The Deloitte process model is valuable because it emphasizes building

innovation concept based on needs rather than discovering a concept which can

be developed as the stage-gate model does. Also, several idea generation

processes will be mentioned in a later sections emphasize idea generation based

on customer understanding. The Deloitte model, unlike the other FFE models,

integrates strategy, decision making (go/no go), idea generation, prototyping,

business case analysis, planning, risk assessment, and requirements analysis.

Further, the required expenses and energy are thoughtfully shown on the models

axes. So, in the first iteration, one can see that cost and energy should be

relatively low. Finally, the go/no go decision point is analogous to the gates in the

stage-gate method which gives the team an idea of what objectives must be met

in order to pass and kills poor potential projects before they soak up too many

resources.

As well, the illustrated model show some ordered flow to the activities.

However, this researcher feels the order of some activities can be changed

slightly, or even done concurrently. Additionally, the activities of idea generation

seem broad, which seems to allow for specific idea generation processes to be

used. Note that, idea generation will be discussed in detail in later Sections 2.5,

2.6, & 2.7. Again, the “build an idea” approach seems to have advantages over

the “find an idea” approach for developing or discontinuing proposed innovations.

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Selecting quality over quantity is preferred because the act of screening ideas

requires resources in itself. Better quality ideas can be created through

processes and methods which will be discussed in the idea generation section

that follows.

2.4.8. Downsides of the Deloitte Spiral Model

Although this model does emphasize strategy in the starting point, it is

questionable how much company strategy and product portfolio strategy impact

this process because it is not described as a specific activity, as depicted in

Figure 2.14. Given the iterative nature it is possible that the initial concept is

highly modified and veers away from strategic objectives. Again by contrast, the

Khurana & Rosenthal (1998) model rigorously tries to align the new product

development project with the company’s strategic objectives, whereas the

Deloitte model does not. The Deloitte authors do make an argument that using

idea banks seems to be more of a finding an idea approach rather than a building

an idea approach. However, it is unclear how generated ideas are stored for

future review in this model. Hence, idea management is unclear in this model,

and sourcing of ideas mentioned largely in the Innovation Value Chain model is

all but absent here for the reasons mentioned above.

Activities such as experimenting are emphasized as front end activities

(Kelley & Littman, 2005; Kelley, Littman, & Peters, 2001). Yet, this model does

not mention those activities. However this researcher commends this model

because it includes prototyping, which to some degree can be viewed as an

experimental activity of form and functionality. Additionally, opportunity

identification and opportunity analysis seems to be missing from this model;

although one could argue it is an output of the activities related to understanding

customer needs and generated ideas/alternatives.

This researcher feels this model does contain benefits; especially since it

highlights the driving factors of building an idea verses finding and idea. The

Deloitte spiral model does to a large degree mirror the Stage-gate process

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because it manages risk by staging development; however, it is different than

stage-gate because it is more based on repeating activities to build ideas rather

than taking one selected idea and developing it. This researcher would like to

see case studies on the application of this model, to determine its effectiveness.

2.4.9. Koen’s NCD Model

Koen et al. (2001) introduced another process model in their paper entitled

“Providing Clarity and a Common Language to the Fuzzy Front End.” They

mention, as Deloitte does, that the activities in the front end are very complex

and iterative and thus they state “a sequential process model was not

appropriate” for the fuzzy front end (Koen et al, 2001, p. 2). As well, they state

the cultural differences and importance of management and leadership very

much affect the results of front end activities. Hence they introduced the following

visual model to help guide activities in the fuzzy front end.

Figure 2.15. Visual Depiction of Koen’s NCD Model

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The circular form of the above model is meant to represent an idea

iteratively passing across the five major activity areas. The center, termed “the

engine”, and was placed in the center to signify leadership, culture and strategy

as drivers the FFE. The inner spoke areas can be seen above and are fairly self

explanatory. The arrows between the inner areas indicate ideas “flow, circulate,

and iterate between and among the five elements” (Koen et al, 2001, p. 4).

Further they mention “while inherent looping back may delay the FFE, it typically

shortens the total cycle time of product development and commercialization”

efforts (Koen et al, 2001, p. 4). Further they say, activities can “proceed non-

sequentially.” Interestingly, their model does place an emphasis on opportunity

analysis and opportunity identification as the Deloitte model does not.

Regardless, it is thought from reviewing the recommended activities that Koen’s

model also sways toward the ‘build-an-idea’ approach.

The black wheel section on the outside signifies influencing factors; such

as, governmental policy, environmental regulations, law, and socioeconomic

trends. This can to some degree can be compared with the research on

environmental scanning where FFE practitioners are told to observe changes in

policies, technologies, and so on, to locate opportunities and generate ideas

(Flynn, Dooley, & O’Sullivan, 2003; Drucker, 1985). Interestingly, this is one of

the few models other than Hüsig, Kohn, & Poskela’s (2005) model which include

environmental items influencing the FFE.

The model shows new ideas, information, and opportunities can enter into

the process through the illustrated arrows, and the formulated concepts which

can exit towards the new product development process or the technology state-

gate process.One benefit of this model is its’ strong base in customer needs

developed from the opportunity identification and opportunity analysis phases.

This strong base can be used to generate ideas with higher value and

likelihood’s of success. Further, the iterative nature of the model is a definite

benefit especially for remolding concepts based on analysis; as well as, utilizing

continued idea generation to remold ideas into better forms.

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2.4.10. Downsides and Conclusion on Koen’s Model

Although the NCD model has benefits it also has several downsides, the

first being it provides limited guidance. The model does contain activities

however, like the innovation value chain model it can be too broad to direct

specific activities. The stage-gate models stated objectives at the end of each

gate which to a large degree helped focus activities; whereas, the NCD model

does not provide such guidance. As well, this model does not give indications of

how cost, time, and effort should be spent where the Deloitte model does.

Additionally, the lack of a formal (go/no go) gate to manage risk and

optimize resources is seen as a large weakness of this model which could be

remedied easily by adding it in; however, one should note there is still some

debate about whether eliminating ideas is an appropriate practices for the early

innovation process.

The introduction of environmental influencing factors is novel to a large

degree; however, it is largely unstudied how much environment factors influence

the FFE; and it is questionable if adding those factors adds any value other than

their symbolic nature. The lack of a direction for the flow of an idea may be a

benefit of the model. However, it can also hinder practitioners by confusing them

about which activities to undertake. Also, it is unclear if idea selection removes or

screens poor concepts from the process. Finally, it is ambiguous at what point a

concept would transfer to the new product development process, whereas, in the,

Deloitte and stage-gate processes, it is fairly clear.

This model is greatly valuable because shows the FFE process with

several large fundamental elements which require a large degree of iteration.

However, the downsides are:

(1) the lack of a (go/no-go) gate to minimize risk;

(2) the unclear flow of activities;

(3) lack of a link to time, effort, and energy; and

(4) the confusion about when to eliminate or transfer ideas weaken this

model.

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In summary, this model is more suited to developing an understanding of

the elements of the fuzzy front end, rather than serving as a guiding process

model for practitioners. Nevertheless, it represented a great advancement when

introduced in 2001.

2.4.11. Husig, Kohn, and Poskela 2003

Iin their article “The role of Process Formalization in The Early Phases of The

Innovation Process”, Husig, Kohn, & Poskela (2003) successfully argue that

having formalized processes for the fuzzy front end increase the probability of

front end success. As a side note, this article introduces a visual process model

of the FFE shown below.

Figure 2.16. Visual Depiction of Husig, Kohn, and Poskela Model

This model has environmental screening as in the Koen NCD model in

which external changes and trends will be analyzed and translated into potential

business opportunities. This is followed by a gate where opportunities generated

during the previous phase are screened and the best are selected to be moved

toward idea generation. However, the authors do make a clear distinction that

these phases and gates do not have to be in sequential order as in the stage-

gate processes, and that ideas can be “redirected” to other stages. Further they

say, for each opportunity worth pursuing several ideas will be generated where,

“those ideas will be combined into one or more concepts. This implies the subject

of analysis keep changing over the process. Therefore this process model is

rather a representation of continuous activities which permanently cycle in order

to fill the NPD pipeline.

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After the ideas are created, the “most promising ideas are subject to an

intensive search, or refined into detailed product project or concepts” in the third

stage (Hüsig, Kohn, & Poskela, 2005, p. 36). Finally, the concepts are evaluated

in the go/no go gate to see if they should pass into the NPD process. Although

this model does not have all the major attributes of the prior mentioned models, it

does serve its principle function which is to provide structured front end

processes in order to increase front end success. Hence, it appears this model

was designed to show the importance of structure in the fuzzy front end.

2.4.12. Montoya-Weiss & O’Driscoll

A notable mention should be given to Montoya-Weiss & O’Driscoll’s

(2000) article “From experience: Applying Performance Support Technology in

the Fuzzy Front End.” In this article they do not present a full front end process

model, but instead suggest a process model for dealing with ideas.

Figure 2.17. Montoya-Weiss & O’Driscoll’s Funnel Model

57

Figure 2.17 shows this model concentrates on the “finding an idea”

approach. These authors propose idea management software as a key tool in

managing the fuzzy front end. Their model emphasizes capturing ideas, primarily

from employees in the company. Their software program captures ideas and

allows the FFE team to analyze them through the software based on the factors

of: (1) market, (2) technology, (3) business, and (4) human factors. The software

guides the process. This begs the question: would the process and activities for

the fuzzy front end be best guided by (a) management based understand of how

the system should work or (b) tools and resources?

To answer this one should look at the many documented cases of

companies failing horribly in their attempts to borrow other processes like (six-

sigma) and implement them by simply applying software and tools. In order for

these complex processes to be successfully applied a company’s management

must develop a deep understanding for how the process works and why it works.

There is a risk in relying on software to guide the front end processes. Instead it

is highly recommended that a conceptual understanding of the front end

processes be developed prior to relying on software for front end development.

2.4.13. General Problems and Issues with Fuzzy Front End Models

Many of the process models for the FFE share similar problems and issues,

which need to be highlighted so that future process models for the FFE can

eliminate these weaknesses. A list of major problems identified by this

researcher is listed below:

1) No formal integration of gate in some models

2) Poor visual representation of cost, effort, time, and money

3) Poor integration of portfolio management and company strategy

4) Very poor link to idea management and idea banks

5) Poor link to knowledge management

6) Poor link to creativity management.

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2.4.13.1. No Formal Integration of Gates in Some Models

Cooper recently found that the gate at the end of each stage is a very useful way

of providing guidance to practitioners in the front end, and even more valuable for

killing off projects which do not meet a company’s set objectives (Cooper, 2008).

It is strongly believed that periodic gates are valuable and very useful activities

for the front end. However, models like Koen’s NCD model and Khurana &

Rosenthal’s models do not formally integrate gates.

2.4.13.2. Poor Visual Representation of Cost, Effort, Time, and Money

The Deloitte model shows on its axis’s time, effort, and expenses. This quickly

shows managers respective levels of investment during the FFE process which

helps to guide vital resources to particular activities, like idea generation. Not

having some visual way of displaying time, effort, or expense leaves out a

powerful means of guiding FFE management.

2.4.13.3. Poor Integration of Portfolio Management and Company Strategy

Khurana & Rosenthal (1998) showed a strong link between implementing

strategy in the FFE and improved FFE results. Yet, their model alone visually

shows product portfolio and company strategy as being integrated into a process

model for the FFE. Other models such as stage-gate say it should be considered

and may be influential at certain gates. Also Cooper’s (1999) article “New

Product Portfolio Management: Practices & Performance” shows the value in

having strategy and how it influences FFE activities. Several idea generation

articles also state that companies should use formal idea generation events to

flesh out the product portfolio (Rochford, 1991; Zein & Buckler, 1997; Patterson,

2005). There is a strong need to integrate company and portfolio strategies into

process models for the fuzzy front end. Therefore, future visual process models

for the FFE should take this into account.

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2.4.13.4. Poor Integration of Idea Management

Although all of the models mention idea generations (except for stage-gate which

relies on already discovered ideas) only one model being Montoya-Weiss &

O’Driscoll integrates managing idea and idea banks. Later sections (2.7 & 2.8) of

this thesis will discuss idea management and its value in the FFE. Sadly it seems

that front end innovation management has not been linked to idea management

in any substantial way. Thus, many of the models may result in lost ideas, ideas

being shelf and not revisited, or ideas just never making it to the correct front end

individuals (Perk, Cooper, & Jones, 2005; Flynn, Dooley, & O’Sullivan; 2003). So,

future models for the FFE should knowingly integrate idea management into their

processes.

2.4.13.5. Poor Link to Knowledge Management

Foster author of How to Get Idea dedicates a whole chapter on the

argument that an individual should get as much information as possible to come

up with good ideas. Revisiting the definition of a new idea as being “a

recombination of other ideas” one can deduce that knowledge is important in

idea generation activities.

Idea generating processes like IDEO’s ‘deep-dive’ and Anthony Ulwick’s

‘outcome based innovation’ all emphasize contextual and ethnographical market

research where customer behavior, unspoken needs, and customer context are

researched (Kelley & Littman, 2005; Ulwick, 2007).

All of these activities build a large amount of knowledge about the

customer, their behavior, and their environment which are then used to locate

opportunities and generate ideas. For example, contextual research studies

usually are delivered in video and written form which is directly used to generate

ideas (Conley, 2002).

Amazingly, the valuable knowledge generated during these intensive

research studies may be re-used to fuel future idea generation activities;

however, the documents containing them may be forgotten about or even worst

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lost in a company’s database. Why, can’t these documents be built upon

resulting in a richer record of information to help spawn idea, and locate unseen

opportunities? Note: idea management and knowledge management overlap to

a degree because ideas are considered a form of knowledge (Bakker, Boersma,

& Oreel, 2006).

Remarkably, the front end processes and FFE process models have no

link to knowledge management. Additionally, building the capabilities to execute

a project in the NPD also requires knowledge management, to insure the product

team has obtained the needed knowledge, or know how to get the information to

execute effectively. Even the business plan is considered a knowledge document

which must be built, developed, and managed.

Hardagon & Sutton (2000) article on knowledge brokering at IDEO is

probably the best evidences that knowledge management should be integrated

into FFE processes. They learned “the best innovators systematically use old

ideas as the raw material for one new idea after another” (p. 6). In the highly

innovative companies they studied, they found individuals: 1) captured good

ideas from things they researched for customers, observed from other great

inventions, or collected, and 2) kept ideas alive in product archive rooms,

databases, idea fairs, and pictures which is very similar to knowledge storage

and 3) applied old ideas in a new way by allowing individuals to communicate

problem through expert phonebook databases and disseminate good ideas

amongst their organization.

For example, IDEO offices are very open allowing for hundreds of unplanned

interactions per day.

Hence, a link to knowledge management could benefit idea generation,

opportunity identification, as well as, other activities of the fuzzy front end, and

should be integrated into future process models for the fuzzy front end. If

anything the process of knowledge brokering some how should be integrated into

the processes for the FFE especially for firms with large amounts of design work.

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2.4.13.6. Poor Link to Creativity Management

Creativity management is not mentioned in articles on the fuzzy front end,

but it however, has been mentioned greatly in the literature on idea generation

and opportunity identification. Steven, Burley, & Divine show individuals with

higher creativity which are coached in the NPD process and business basics out

perform individuals with normal creativity by up 5-to-12 times. This result was

obtained from a single long term study in one company but seems very

promising. This leads one to think that creativity management should concentrate

on placing individuals with high creativity into the FFE processes and train them

to practice discipline business.

As well, journals like ‘creativity and innovation’ among others attest to the

importance of creativity management. In the literature, creativity management

has gained much importance in FFE processes of companies (like marketing

firms, advertising, design firms and so on) where design task are prevalent

(McAdam & McClelland, 2002). Majaro (1991), state creativity can be divided

into three categories, depending on how it originates. These are A) normative

creativity, which is creativity in problem solving, B) exploratory creativity which is

creativity not related to a particular demand, and C) creativity by serendipity

which is luck or chance (Flynn, Dooley, & O’Sullivan, 2003). So tasks like

experimentation and prototyping can help increase creativity through both

normative and explorative means. Thus, activities which have high creativity

potential can be integrated into the FFE processes, and in this way, creativity

management can be knowingly integrated into FFE processes.

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2.5. Literature Review of Activities in the Fuzzy Front End

As can be seen in section 2.4, each FFE model tends to highlight some

activities over others; as well, some models may not mention an activity which

another model says is vital. Hence, this researcher feels it would be valuable to

create a comprehensive list of formally named activities which may take place in

the fuzzy front end, and then quickly describe how each functions.

2.5.1. List of Activities in the Fuzzy Front End

Table 2.4 below shows all of the activities mentioned in the FFE literature

which can or should occur in the front end of innovation. Note the table was split

into to columns so the information can be placed all on one page.

Table 2.4. List of Activities Which Can Occur in the Front End of Innovation

Knowledge management Idea GenerationConcept refinement Idea SelectionTesting (trial) Idea ScreeningMarket testing Diffusing IdeaFunctionality testing Knowledge Management Analysis Diffusing ideas

Idea and concept Analysis Idea ManagementMarket analysis Prototyping Competitive analysis Environmental Scanning

Building a business case Opportunity IdentificationPlanning for the NPD Opportunity AnalysisReview Review Development Research Strategy planning Market Research Application Exploration Customer research Partnering Technical ResearchPortfolio planning Commitment building

At first glance, one notices that many activities can occur in the front end

of innovation. Table 2.4 highlights the major activities which are referred to in the

literature. Table 2.4 places them in similar categories, so, for instance, concept

testing and market testing both fall under the major category of testing.

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The first set of tasks is concept refinement and includes selecting or

developing a concept definition. Concept refinement is a very broad activity

which can include many if not all of the activities mentioned below. In many

instances concept refinement means specifically, narrowing a definition of the

product or service into a short narrative or illustrated form.

Testing is a vital activity in the front end and includes concept testing,

market testing, technical testing, functionality testing, and manufacturing testing

among others. Concept testing usually pertains to testing the concept with

customers and users, where market testing is more looking at the demand and

receptiveness of the market to the product or idea. Functionality and technical

testing are self-explanatory.

The term “testing” may be inter-changed with the word “analysis.” For

example, concept analysis looks at the strengths and weaknesses of a concept

where concept testing could also be done the same way. The goals of testing are

typically understanding and the confirmation of assumptions. So something like

concept testing seeks to understand how customers feel about an idea and tries

to confirm the assumed value of that idea. Please note, the word ‘trial’ can be

inter-changed with the word ‘testing.’

Analysis is a very broad term and can be activities like idea analysis,

opportunity analysis, competitor analysis, or even functionality analysis.

Consequently, the term “analysis” alone is not very guiding as an activity and

must be combined with another term to really be made into an activity. For

example, market analysis can be anything from looking at the size of the market

and its revenues, to a detailed examination of trends, price-elasticity, and

impending market events.

The goal of an analysis is typically understanding and the building of

knowledge. For example the goals of a competitor analysis mainly are to

understand the competitive landscape which aids in judging the risk of the

competition. The words analysis and assessment can be inter-changed.

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Opportunity identification is a commonly cited activity and is the act of

locating favorable circumstances or situations in the marketplace. Opportunity

identification examines in the marketplace for: 1) a solution is needed or, 2) there

are un-filled customer needs, or 3) there is a chance to create new customer

needs, or even 4) there is some type of change in the market which creates a

chance for new business offerings. Opportunity analysis is the activity of

examining the opportunity to determine if it has validity and value. Opportunity

analysis seems to overlap to some degree with customer needs analysis. As

well, opportunities screening is the act of eliminating opportunities from further

consideration.

Planning or project planning is a typical activity which involves creating

project plans, with lists of: activities, milestone, objectivities, and deliverables.

The project plan is typically used to guide tasks in the new product development

process, but can also guide tasks for the FFE process.

Building a business case is a fairly comprehensive set of activities,

which includes many types of analysis, testing, planning, and development. Most

importantly a clear understanding of the risks, benefits, requirements, and

required resources should be clarified and presented to upper management.

Typically, building a business case results in a defendable business plan.

However, as an activity alone ‘building a business case’ is a bit too broad and

should not be used to guide specific activities. Importantly this term does

emphasize the need to prove the value of the idea, while minimizing the

downside. Hence, this researcher really prefers ‘building a business case’ to be a

goal more than a specific activity.

Reviews are also a highly cited front end activities. Reviews may be tasks

like a legal review, technical review, business case review, and so on. Reviews

are typically an activity where either upper management, stake holders, or parties

controlling resources have the opportunity to, examine, evaluate, and judge a

particular item. For example, a legal review is an activity where a company’s

lawyers can assess the legal impact a particular idea would have on a company.

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Reviews are an integral activity which may also include making particular

decisions, like the gates in the stage-gate process. The word ‘evaluations’ can

also be inter-changed with reviews.

Development is another broad word which can include anything from:

concept development, technical development, product development,

manufacturing, and project development. Development usually means doing a

set of activities to achieve a set of objectives like, building knowledge, creating

something, or conducting an analysis. Again, this word is very broad and could

also include things from performing analysis, testing, reviewing, to creating a

business case. Thus, the word development has to be tied to another word like

‘technical development’ to be more guiding as a set of activities. The word

‘formulation’ also can be interchanged with the word development.

Environmental scanning is an activity which is presented in some front

end models and includes observing and seeking for knowledge and

developments outside the company. Peter Drunker (1998) along with Auster &

Choo (1992) describe it in detail. Auster & Choo (1992) divide environmental

scanning into eight categories: (1) customer, (2) competitor, (3) industry and

sector, (4) technological, (5) economic, (6) specific economy, (7) regulatory, and

(8) socio-cultural. This activity may include scanning for ideas, locating

opportunities, or building knowledge (Flynn, Dooley, & O’Sullivan, 2003).

Conversely, environmental analysis is activities seeking to understand the

environment and how it is changing. The results of environmental scanning and

environmental analysis can be used by the idea generation processes to

generate ideas.

Selection activities may include idea selection and project selection. Idea

selection may include related tasks of screening, filtering, and culling of ideas.

Idea selection activities normally are related to choosing ideas to pursue or

develop further.

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Idea generation activities are highly quoted in the FFE literature and

relate to activities which produce ideas, like brainstorming. The goal of idea

generation is simply to produce ideas and will be discussed in detail in Sections

2.6, & 2.7.

Learning activities are not commonly quoted as a specific activity

although they are fundamentally a part of many activities, like primary research,

analysis, and testing.

Knowledge creation, knowledge storing, and knowledge diffusing

activities are not quoted as being formal activities in the FFE, although they are

fundamentally a part of many other activities. Meetings, analysis, testing,

reviews, documentation all create, store, and diffuse knowledge.

Only Hardagon & Sutton (2000) specifically quotes knowledge diffusion

activities in his knowledge brokering pieces on the FFE as a method of diffusing

ideas in the organization. Knowledge storing can also include storing results of

things like market studies, tests, and so on into databases, as well as, storing

ideas in idea banks.

Idea management is quoted as being a FFE activity, and will be

discussed in detail in Section 2.8. Idea management includes generating, and

storing ideas so they can be diffused, or selected.

Prototyping activities are highly quoted, and relate to the creation of a

physical or virtual creation of the idea, which can be used in analysis and testing

activities. Authors like Kelley highly cite prototyping as a critical front end activity

(Kelley, Littman, & Peters, 2001; Kelley & Littman, 2005).

Portfolio planning is also a front end activity, which involves making

decisions about how new ideas can fit into the group of ideas which the company

is developing and how those ideas align with the company’s strategies (Khurana

& Rosenthal, 1998; Cooper 1999; Patterson, 2005).

Feasibility activities assess the ability of the company to execute the

given project and can be broken up into many areas like, market feasibility,

technical feasibility. Feasibility is very similar to testing and analysis except it also

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makes a judgment as to some result. Feasibility may or may not include analysis

or testing. So technical feasibility activities may analyze the technology then

determine the degree to which the company can develop those technologies.

Risk analysis is also a highly cited activity which goals are to estimate the

level of risk with respect to (1) the competitors, (2) the market, and (3) the

capabilities of the company at executing a project.

Research activities are a very broad term and can include: exploratory

research, focused research, and even general research. Research can include

learning, knowledge building, evaluation, testing, prototyping, analysis,

environmental scanning, among others. The term research is associated with

activities such as learning, knowledge building, and testing, and may be

combined with another term to serve as a focused activity, like market research

or customer research.

Commitment building activities relate to getting devotion or dedication to

an idea and can include activities like idea selling which typically are performed

by product champions, product teams, or upper management (Hansen &

Birkinshaw, 2007). Again this discussion of activities in the front end was not

meant to be comprehensive but more of an overview of general activities which

can take place.

Application exploration activities related to finding, and exploring

applications and potential markets for a new radical or disruptive technology.

Interesting, Thongpapnal, O’Connor, & Sarin (2008) argue that application

exploration for radical & disruptive innovation is vita and if done poorly may

“result in serious repercussions on the perceived viability and business potential

of the proposed major innovation” (Thongpapnal, O’Connor, & Sarin, 2008, p. 4).

Application exploration is rarely mentioned in the FFE literature. However,

Thongpapnal, O’Connor, & Sarin’s (2008) study makes a strong argument that

application exploration should be a formal activity in the FFE, especially for

radical & disruptive innovations.

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2.5.2. Quick Categorization of Activities in the Fuzzy Front End

In reviewing activities which take place in the front end, it was observed that

some activities related to (a) improving and evaluating a concept, or the (b)

alignment and management activities, while others were general activities for (c)

coming up with ideas. Table 2.5 shows a rough categorization placed into these

three areas. One should notice that many activities overlap between areas.

2.5.3. Proposed Organization of Activities for the Fuzzy Front End

It seems from conducting this rough categorization that there is a big division

between front end activities related to developing a particular idea, and front end

activities for getting ideas. However, it was also observed that some activities

benefited both areas, such as analysis, idea diffusion, research, and testing.

Table 2.5. Categorization of Front End Activities

A) Activities related to a developing a particular idea

C) Activities related to generation of ideas

Analysis AnalysisBusiness case building Diffusing ideasCommitment building Environmental screeningConcept refinement Idea capture & storingDevelopment Idea diffusionIdea diffusion Idea generationKnowledge creation, storage, & diffusion

Idea screening

Partnering Knowledge creation, storage, & diffusion

Planning Needs analysisPrototyping Opportunity analysisResearch Opportunity identificationReview Opportunity screeningTesting Portfolio planningApplication Exploration Strategic planning

B) Activities related to alignment and management of FFE

Testing

Portfolio planning ResearchStrategic planningReviewIdea selection

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One should also note, future sections of this thesis will refer to activities

related to selecting and developing particular ideas as late front end activities,

and will refer to activities related to managing ideas, generating idea and

locating opportunities as early front end activities.

2.5.4. Summary of Section

In summary, this section reviewed the formal activities which take place in the

front end of innovation, then broke them down into three possible categories of

(a) activities related to developing a particular idea, (b) activities related to getting

or generating ideas, and (c) activities related to managing the fuzzy front end.

Some activities are easy to understand by those formally educated in

business. For example, any individual with an MBA should understand how to

build a business case, conduct technical reviews, and project planning,

competitive analysis, and opportunity analyses. However, other activities such as

market, technical, functional, and market testing, prototyping, and environmental

scanning may require additional training.

Some vital activities like idea generation, idea screening, product portfolio

management, and idea management are prove difficult for training, because

there is a limited amount of literature on these topics. It may be that idea

generation is the most poorly understood and most critical area for front end

success. Section 2.7 will attempt to clarify idea generation, and Chapter 3.2 will

introduce new theories on the topic of idea generation.

2.6. Literature Review of Idea Generation

As can be seen from section 2.5, the front end activities were broken up into two

broad categories one of which was activities related to the generation of ideas.

Interestingly, this researcher saw several opportunities to improve the fuzzy front

end by clarifying the understanding of idea generation. The following two

sections will focus on idea generation.

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2.6.1. Why is Idea Generation Important?

As mentioned previously, the output of the new product development process is

only as good as the concepts and ideas being put into it, “garbage in equal’s

garbage out.” Drucker noted that "innovative ideas are like frogs' eggs; of a

thousand hatched, only one or two survive to maturity" (Stasch, Lonsdale, &

LaVenka, 1992, p. 14). Stevens & Burley (1997) have shown it roughly takes

from 1,500 to 3,000 raw ideas to equal one business success. With such a poor

conversion rate one can understand why a company needs a stream of ideas.

Of course, one can argue over the exact conversion rates of raw ideas

into business successes, but it would not negate the matter that a large number

of raw ideas are needed to develop even one winner.

Again, idea generation processes, activities, or phase is of great

importance, where Stasch, Lonsdale, & LaVenka (1992) state, “the objective of

all idea-generating activities is to guarantee that the company does not leave the

exploration stage of new-product development to chance” (p. 21).

Aside from leaving idea generation to chance, changes in the idea

generation process may increase the quality of the produced ideas. Several

researchers state that idea developed from a deep understanding of the

customer usually have higher value and better chances of succeeding (Flint,

2002). So, logically, a business should try to increase the quality of the ideas

they are generating in addition to guaranteeing a steady stream of ideas.

In addition to generating ideas for new offerings, processes, solutions, and

so on, development projects periodically require ideas to solve problems. For

example, a new product may require new ideas for packaging to help it sell in the

stores. So, not only are ideas needed to form the bases of the new product, they

are also required to solve problems or create value as the project moves through

the development processes. This is backed by Verworn & Herstatt ‘s (2001)

statement that “idea generation should take part throughout the whole project” (p.

3).

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The innovation value chain model shows inhouse idea generation as a

vital link in the innovation process. Again, one must take idea generation in

perspective. If the other parts of the innovation value chain are weak or poorly

functioning, even the best ideas will not produce desirable innovation results.

Of course, ideas affect the product portfolio. Adams-Bigelow’s (2005)

found that 54% of the ideas from companies were generated through informal

activities, and of these, 25% were generated informally and without a specific

purpose. Of the 46% of ideas that came from formal idea generation activities,

only 33% were generated to fill gaps in the product portfolio. This supports

Tucker’s (2003) claim that idea generation is sometimes applied sporadically.

Finally, new ideas open up new strategic options for a company. In The Strategy

Paradox, Michael Raynor (2007) discusses Microsoft’s use of an option-based

strategy and their development of new ideas because they wanted to have the

strategic option to go into those markets when they emerged (Raynor, 2007).

2.6.2. What is Idea Generation?

Idea generation can occur inside or outside a business and is thought of as a

single activity or set of activities performed by individuals or groups. In the

literature, there are many books related to coming up with new ideas, products,

services, branding ideas, etc. Again, because the term “idea” is so broad, the

literature related to idea generation can be very broad and varied. Often books

providing idea generation methods do not even use the word “idea generation.”

For example, books on branding may describe exercises to help create new

branding concepts, whereas others, like Blue Ocean Strategy (2005) does not

mention idea generation and instead mentions creating new business and new

market spaces (Kim & Mauborgne, 2005).

This is why respective areas, like branding, manufacturing and customer

service may have their own terminology for methods which come up with new

ideas. Consequently, it is difficult to outline all idea generation techniques,

activities, methods, and processes, so this research concentrated on idea

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generation of new products or services. Yet, the idea generation processes

listed herein are believed to be highly useful across many disciplines. So, even

individuals with the goal of creating new market and promotional concepts will

benefit from the listed techniques, activities, and processes in the following

section.

2.6.3. A Review of Idea Generation Research

The following is a quick overview of research on idea generation. There has been

varying amounts of research performed on different areas of idea generation.

People were studied as factors in idea generation and the fuzzy front end

by (Stevens, Burley, & Divine 1999). They reported that highly creative people

trained in business and coach to be discipline in their application of business

principles outperformed individuals with normal levels of creativity on the average

of 10 times by generated revenues. A large vein of research on creativity in

individuals also strongly corresponds to idea generation, in journal areas such as

Psychology and Creativity among others. Gender and idea generation were also

examined (Ester 1996).

Idea generation in teams was studied by numerous researchers (Miller,

2005; Verworn & Herstatt, 2001; Paulus, 2000; Schlicksupp, 1977; Rickards,

1999; Aiken & Wong, 2003).

Research on tools to aid in idea generation mainly relates to software

programs which capture ideas and encourage collaboration (Miller, 2005; Flynn,

Dooley, & O’Sullivan, 2003; Flint, 2002; Bakker, Boersma, & Oreel, 2006; Tucker,

2003).

Software such as online collaborative whiteboards and creativity

enhancing software have been invented and discussed in other studies (Aiken &

Wong, 2003; Ester, 1996; Janejira, 2006; Montoya-Weiss & O’Driscoll, 2006;

Flynn, Dooley, & O’Sullivan, 2003; Wagener & Hayashi, 1994). Software

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designed to stimulate creativity and seed individuals with ideas by displaying

thousands of images to them was discussed by Satzinger, Garfield, &

Nagasundaram (1999).

Tools, such as tech boxes at IDEO which hold items like products,

material samples, and other random items, are to be used to simulate creativity

(Hardagon & Sutton, 2000). Kelley, the CEO of IDEO, advocates using any

resources possible to prototype ideas so the ideas can be quickly explored and

tested (Kelley & Littman, 2005; Kelley, Littman, & Peters, 2001).

Kelley also advocated using every surface in a room to display ideas

during brainstorming sessions, and to use any tool to help in communicating

ideas by using things like: paper, color pens, prototypes, hand jesters, videos,

and modeling clay. As of 2008, there are many idea generation software

protocols and web applications which can be applied to various situations. These

are discussed in Section 2.8.

Incentive’s impact on idea generation was found to be informative by a

number of researchers (Alam, 2003; Flynn, Dooley, & O’Sullivan, 2003;

Belliveau, Griffin, & Somermeyer, 2002; Gorski, & Heinekamp, 2002;

Abdulaziz,1995; Toubia, 2006; Derry, 2004).

Company cultures which promote idea generation were mentioned in the

literature on culture of the FFE front end in Chapter 3 of PDMA (Patterson; 2005)

as well as, in Flynn, Dooley, & O’Sullivan (2003), Zien & Buckler (1997), and

Kohn, Ernst, & Hüsig (2006). Company cultures impact on creativity was

researched across several disciplines ranging from psychology, learning, design,

creativity, and are to numerous to be mentioned here.

The impact of national culture on creativity was researched by

Eisenberg (1999) and others. Researchers interested in the many factors

affecting idea generation should look at the topic area of ‘creativity management’

and the above mentioned research area disciplines.

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The local environments which promote effective idea generation

sessions were mentioned in Miller (2005), Foster (1996), Kelley & Littman (2005),

and Kelley, Littman, & Peters (2001). A productive atmosphere was described as

being open to new ideas, playful, fun, humorous, devoid of interruptions, focused,

and risk taking. Rooms and buildings were arranged so unplanned interactions

would often take place and spawn ideas (Hardagon & Sutton, 2000).

Screening and sorting can aid in idea generation. Miller (2005)

mentioned that concept screening can be integrated into idea generation to

further spawn ideas. He also discussed advisory voting where each individual

has a number of votes. This approach was also used by IDEO; as well as, sorting

using un-weighted criteria, and screening and sorting which can be used to focus

an idea generation session to fill a product portfolio’s needs (Kelley & Littman,

2005; Kelley, Littman, & Peters, 2001).

2.6.4. Creativity and Idea Generation

Flynn, Dooley, O’sullivan, and Cormican (2003) found “that creativity within the

organisational innovation process is a highly complex area” (Flynn, Dooley, &

O’Sullivan, 2003, p. 74). They propose an ‘idea generation methodology.’ More

notably, they discuss Majaro (1991) which breaks up creativity into normative

creativity, exploratory creativity, and creativity by serendipity (Flynn, Dooley, &

O’Sullivan, 2003).

Again, “normative creativity focuses on generating ideas to solve

specific needs, problems, and objectives. Although the predefined nature of

normative creativity renders it more cost-effective than other creative

approaches, it may also restrict the field of creative vision” (Flynn, Dooley, &

O’Sullivan, 2003, p. 75). For example, idea generation techniques, activities (like

problem solving and brainstorming) can be seen to fill a particular need and thus

stimulate normative creativity.

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Exploratory creativity from Flynn et al. (2003) “focuses on generating a

broad spectrum of ideas, which may not necessarily be related to known

requirements or demands. It differs from normative creativity in that it does not

focus strictly on finding specific, almost pre-meditated solutions to known

problems” (Flynn et al, 2003, p. 43). Examples of this can be seen when ideas

are created from activities like experimentation, market research analysis, and

customer feedback. They concluded that “a hybrid of normative and exploratory

creativity can potentially provide a balanced combination of goal orientation and

imaginative freedom” (Flynn, Dooley, & O’Sullivan, 2003, p. 46).

Creativity by serendipity is when the idea underlying the innovation is

discovered by accident. However, Proctor (1999) disagrees with this premise.

But this research suggests that creativity by serendipity may be a useful catch-all

category for acts of creativity which cannot be explained. For example, the

accidental discovery of Teflon, Superglue, ScotchGuard, & the pace maker can

be placed here. Austin, Devin, Sullivan (2008) argue that creativity by serendipity

can be harnessed via implementing certain techniques. However, this thesis

cautions against dependence on this method, because it may generate many

ideas which are outside the strategic interests and organizational capabilities of

the company.

2.6.5. Environmental Scanning and Idea Generation

Environmental scanning influence on the idea generation process is discussed

here in greater detail, since it will be of great use for the following sections.

Environmental scanning, which is “searching and monitoring internal and external

environments for potential stimuli to “initiate” the idea generation process, is only

mentioned in a few articles on idea generation.

Drucker proposed this in his 1985 book, Innovation and Entrepreneurship,

that innovation opportunities are created by changes in the external environment.

These changes can occur as a result of (1) unexpected occurrences (2)

incongruities being something which does not fit in its context, (3) process needs,

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(4) market changes, (5) demographic changes, (6) changes in perception, and

(7) new knowledge. This seems logical since changes open up new opportunities

while they may close others. Thus scanning for these changes is a logical first

step to identifying these opportunities, and helps by stimulating the creativity &

insight to see the opportunities which can result in the creation of ideas to fill

those opportunities.

Auster & Choo (1992) suggest a similar categorization based on (1)

customer information, (2) competitor information, (3) industry information, (4)

technology and processes, (5) general economic considerations, (6) specific

economic climate, (7) regulatory factors, and (8) socio-cultural factors (Flynn,

Dooley, & O’Sullivan, 2003).

Regardless of the categorization, the added resolution created by splitting

up changes or information into specific categories greatly helps searching, and

scanning efforts. Traditionally, information sources like journals, newspapers,

magazines, newsletters, and word of mouth among others kept individuals

abreast of changes. Yet developments in internet tools, such as Google alerts,

automated online news reporting through feeds, and journal databases which

send alerts for news articles, are new ways to stay on top of changes in the

environment. Researchers in high tech companies such as Intel, Cisco, and AMD

are well known for scanning journals for changes in technology and knowledge

and often use it as a source of new ideas. Unfortunately, there are only a few

articles linking environmental scanning to idea generation (Flynn, Dooley, &

O’Sullivan, 2003; Auster & Choo, 1992; Aguilar, 1967; Drucker, 1985).

A few fully detailed idea generation processes, like the Blue Ocean

Strategy, recommend environmental scanning (Kim & Mauborgne, 2005). One

major issue with environmental scanning is that it can quickly result in information

overload if the organization tries to observe too much from the environment.

Additionally, unfocused scanning may accumulate information which cannot be

used in idea generation. Idea generation processes like ‘lead user innovation’ by

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Von Hippel uses environmental scanning to look at changes in the way lead

users apply their technologies (von Hippel, Tomke, & Sonnack, 1999).

Nonetheless, environmental scanning should be focused toward

information which can be effectively used to generate ideas. For example, to

innovate in the supply chain process, a retail store may examine journals on

operations or articles on supply chain leadership companies, like Walmart. Thus,

environmental scanning for ideas may depend upon the type of ideas desired.

This is another reason why environmental scanning should be driven by strategy.

Environmental scanning can also look at history for information which can

spawn ideas. For example, the governments of developing countries can look at

the histories of economic development in industrialized nations like the US to

identify opportunities to fund developments in their own countries.

2.6.6. Seeding Ideas

The act of environmental scanning is very broad and already occurs in many

functions of a company, including competitive intelligence, market intelligence,

scanning of competitor’s offerings, mapping competitor’s pricing, reviewing new

technologies, general market research, and so forth. Each one of these activities

scans the environment in a particular way with a particular goal, like mapping the

competitor pricing with the goal of providing pricing information to the marketing

department.

The goal of environmental scanning is to help identify opportunities and to

seed the creation of ideas. Flynn et al. (2003) says environmental scanning is a

method of capturing stimuli which can be distributed to employee to spawn ideas.

Many of the already existing processes and functions, like competitor price

checking, can be slightly modified to capture information which may stimulate

ideas. For example, while scanning competitor prices, any weird or innovative

pricing displays can be noted and sent along with the pricing report to the

marketing department. This may result in the marketing team using the

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information to generate new ideas related to pricing displays or result in the team

copying it, whereas normally, a typical pricing report would not capture this type

of useful information.

Seeding individuals with ideas is important in stimulating creativity. The

premise of Knowledge Brokering by Hardagon is that individuals can trade and

promote ideas when they interact with others, thereby increasing the ability to

solve problems and create new ideas (Hardagon & Sutton, 2000). Hardagon

continues by saying that knowledge brokering can be influenced by the company.

For example, office space designs which promote communication and

collaboration, like free coffee bars and community work areas, are a non-invasive

method of getting employees to share ideas (Bean, & Radford, 2002; Hardagon

& Sutton, 2000). While, formal methods of seeding and sharing ideas can be tech

box or software programs (Satzinger, Garfield, Nagasundaram, 1999; Kelley &

Littman, 2005; Gamlin, Yourd, & Patrick, 2007).

The 3M corporation even has formal technology fairs where other

employees share and spread ideas, technology, and knowledge (Hardagon &

Sutton, 2000). Again, seeding others with ideas, information, or concepts, can

be done formally or informally and greatly promote internal idea generation.

2.6.7. Opportunity Identifications

Opportunity identification is a recommended activity in many idea generation

processes, thus a discussion of it is needed to further understand idea

generation. Vandenbosch, Saatcioglu, and Fay (2006) believe ideas and

opportunities are intertwined. Recognizing or creating an opportunity is an

occasion for generating or testing an idea; an idea may lead to an opportunity

and it may require an idea to capitalize on an opportunity. Simply put, they are

saying that ideas and opportunities are often separated because one is seen as

the supporting base for the other, where, in fact, the act of creating an idea may

result in the discovery of an unseen opportunity, or vice versa.

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Yet discovering an opportunity requires some creativity in itself and is

similar to the act of creating an idea. Referring back to the review of creativity

one can see that the act of opportunity identification can be seen to simulate

exploratory creativity because is it looking for unmet needs.

Environmental scanning to locate new opportunities or analyzing captured

information to locate unseen opportunities can seed an individual with the

stimulus needed to generate new ideas.

2.6.8. Issues and Problems with Idea Generation

Several concerns arise regarding the process of idea generation. Foremost,

despite the many books and articles on idea generation, it is still relatively in its

infancy. Compared to areas like quality manufacturing or business strategy,

innovation is poorly understood. Idea generation is often less understood as part

of the whole innovation process. To help new product managers, idea generation

must be placed in the larger context of the whole innovation process, and its

conceptual workings must be clarified. To accomplish this goal, this research

attempted to address several large problems which are preventing innovation

managers from improving their company’s idea generation processes.

First, there are very few comprehensive lists of idea generation activities,

and techniques which one can utilize. More importantly, the literature confuses

activities and techniques when in fact they are distinctly different. This research

study provides a series of tables of idea generation techniques, activities, and

processes so practitioners can have some idea of their options and have a

means of comparing them.

Second, the research on sources of ideas is often confusing and

contradictory. Some say sources of ideas are people like customer or suppliers

while others say it is a process, like marketing research. Consequently, several

articles mix idea generation activities (like marketing research) with sources of

ideas (like customers), which leads to more confusion.

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Third, some authors advocate customers as the best sources of ideas,

while others suggest better ideas come from consultants or universities. This

begs the question: what are the best sources for ideas? A comprehensive review

of the sources of idea is needed and will be of value to innovation practitioners.

Fourth, there are no reviews of the major idea generation processes.

There are several famous idea generation processes like outcome based

innovation, IDEO’s innovation processes, and blue ocean strategy, none of which

have been reviewed or critiqued for their ability to create ideas. Each process is

very different and there are no guidelines to help innovation practitioners select

the process which is most appropriate for their needs.

If there is no literature reviewing or comparing these popular processes

how can one confidently select an idea generation process? Thus, the popular

idea generation processes will be described, reviewed, and compared in the next

section in order to address this issue.

Fifth, no articles were found on how to control the idea generation process

let alone any general models showing how to manage it. To manage the idea

generation process, one must begin with a clear understanding of how to control

it. Chapter 3 will review the points of control and create a general model for

controlling the whole idea generation process.

Finally, there are no tools to analyze or diagnose a company’s idea

generation process. The innovation value chain is an invaluable tool to assess a

company’s whole innovation process. Plus it can highlight companies which are

weak in internally generating ideas or sourcing ideas from the outside. But, the

innovation value chain cannot be used to analyze the particular weaknesses of a

company’s idea generation process.

To date, this research review was unable to discover any tools which

analyze the idea generation processes of a company to determine weaknesses

or points of poor management. This is understandable, given the relatively light

amount of research conducted on managing idea generation. Nonetheless, not

having a tool to analyze one’s own idea generation process is like having a

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mechanic without a pressure gauge to test the compression of an engine’s

pistons. Consequently, there is a strong need for an analysis tool to assess the

effectiveness of the overall idea generation process.

2.6.9. Summary of Section

In summary, this section looked at what idea generation is and why it is

important. This section then quickly reviewed the research areas conducted on

idea generation to date. In particular, creativity, environmental scanning, seeding

ideas, and opportunity identification were examined.

The issues and problems related to the process of idea generation were

then discussed to be 1) the lack of a comprehensive list of techniques, activities,

and processes, 2) the confusion in the sources of ideas, 3) the best sources of

ideas, 4) lack of review of major idea generation processes, 5) no models to

control or manage idea generation, and finally 6) the lack of tools to analyze and

diagnose the idea generation process of a company. The following section will

address these problems.

2.7. Highly Detailed Review of Sources of Ideas, and Idea Generation

Techniques, Activities, and Processes

This section addresses several problems identified in the previous section, but

will concentrate on reviewing the techniques, activities, and processes which can

be used in idea generation. A detailed examination of these two items will fill a

gap in the literature and greatly aid innovation practitioners.

2.7.1. People are the Only Source of Ideas

Where do new ideas come from? What are the most likely sources for new

ideas? There seems to be a discrepancy in terms of the sources of ideas. Alam

(2003) shows the sources of ideas to be individuals or groups, while Rockford

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(1991) and Stasch, Lonsdale, & LaVenka, (1992) describe it as involving a mix of

individuals and processes (like marketing studies, research projects). This

confusion creates a large problem which must be resolved in order to improve

innovation processes.

The definition of an idea as stated in Section 2.1 is “a result of association

and combination of other ideas inside a person’s mind” and that “the mental

activities they partake in create those ideas” (p. 15). Again, people are the

sources of ideas. This researcher has never seen an entity like a computer, or

machine creates an idea, with the exception of an article in MIT Technology

Review which described a computer algorithm that created novel patentable

designs of antennas (Williams, 2005).

Without people, there are no ideas. Manufacturing plants running totally

autonomously, software programs executing code on a server, machines

punching parts, have never been known to create an idea by themselves.

Individuals may look at things and come up with new ideas, but things were not

the source of the ideas, they were the stimulus!

The confusion in the term “source” results from confusing it with “seeding”,

which is the act of feeding the brain information, knowledge, and other ideas

which can be used creatively to come up with new ideas. This is why marketing

research itself does not create ideas - the people conducting the marketing

research do.

People are the source of ideas and activities are what produces these

ideas. Activities in the brain involving association, recombination, creativity and

so on, are necessary to create ideas. People in comas or who are unconscious

do not create ideas. People may create ideas while sleeping because their brains

are active and are actively recombining things in unique and often irrational

ways. By looking at it this way, some insights can be grasped.

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Figure 2.18. Idea Creation in a Person’s Mind

When people and activities are separated, one can see how the activities

affect the output of ideas. A later part of this section will review techniques, like

visualization, redefining the question, and thought experiments, and how they

force the brain into a particular mental activity. Activities like marketing research

or strategic planning force the brain through a set of mental activities which may

increase the likelihood of ideas being generated.

Figure 2.19. Activities Leading to the Creation of Ideas

Figure 2.19 above shows two individuals, the top being an executive, and

the bottom an R&D person. By splitting the source from the activity one can see

the effect on each the individual (their creativity, IQ, role) opposed to the effect

which the activities have on the resulting ideas. A highly creative R&D person

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using the detailed outcomes-based innovation process will produce many

valuable ideas, whereas, an executive of average creativity following an ad hoc

process of strategic planning, marketing review, then playing golf may also come

up with ideas, but of much lower quality.

Figure 2.20. Unknown Activities which Lead to the Creation of an Idea

Sometimes, individuals will not remember which activities lead up to the

creation of their idea. From a management perspective, this is not as useful

because processes which are unknown cannot be examined, refined, or even

controlled; hence the idea may seem like a serendipitous creation which is hard

to reproduce. From this point forward, the source of the idea being the individual

or group of individuals will be separated from the activities which they performed

which resulted in ideas.

2.7.2. Techniques, Activities, and Full Processes for Idea Generation

Again there are many techniques, activities, and processes for generating ideas;

importantly one should be very careful to distinguish among them. According to

Encarta, a technique is “procedure, skill, or art used in a specific task” and should

not be confused with activities, or processes. For example, a technique may be

to do “what if scenarios” and “visualization exercises”, while an activity would be

a brainstorming session where several of these techniques can be employed.

An activity can be something like marketing research, brainstorming,

proto-typing, charting, or surveying customers. An activity may be short (like a

five minute session of prototyping) or a long protracted task (like surveying all the

customers a company serves) conducted over several months.

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Whole Processes

Activity ... Activity NIndividual(s)

Activity 1

Activity 1Technique 1 Technique ... Technique N

Ideas

Figure 2.21. Illustration of How Techniques are Embedded in Activities,

which are Embedded in an Idea Generation Process)

A process is a series or ordered set of activities with a desired set of

outcomes. Idea generation processes include IDEO’s deep dive, blue ocean

strategy processes, and outcome-based innovation. Tables 2.6 to 2.10 list idea

generation techniques, activities, and processes. Naturally, there may be some

arguments created over the categorizations, but offering practitioners an ordered

list is valuable regardless of discrepancies in these categorizations.

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Table 2.6. Techniques which Aid in Idea Generation

Techniques Description Reference Note

Visualizations Imaging the solution, imaging the problem, visualizing the actions, items, issues, recombining and associating things visually

* PDMA handbook 2005 chapter 17, * Jack Foster "How to Get Ideas" Experimentation for

validation

Measure, tests, validate, via physical, virtual, or thought experimentation with the goal of confirming a hypothesis or gathering data

* PDMA handbook 2005 chapter 17, *Tom Kelley, * Rochford Linda 2001 * Hardagon 2000

This is very broad, and can include product, technical, market, concept, functionality, manufacturing and testing

Experimentation for Learning

Learning, trials, or spawning new thoughts through physical, virtual, or thought experiments

* Design Thinking Tim Brown Harvard Business Review June 2008

Graphing, plotting, charting

Helps visualize unknown or un-seen relationships * PDMA Handbook 2005 chapter 17

There are hundreds of different ways to display information

Scenario games Create scenarios and try to play them out to their logical end.

* Jack Foster "How to Get Ideas" pg 117, * Rochford Linda 2001

Aggregation , Combination Combining characteristics of a product, service, offering, processes, into a single thing

* Rochford Linda 2001

Metaphors & Analogies Compare a problem, solution, or thing to a person, place, thing, concept, time, or experiences to draw out relationships

* PDMA handbook 2005 chapter 17, * Jack Foster "How to Get Ideas" 110

Our truck is tough like a ram, why not make it look more like ar ram

Though experiment Measure, tests, validate, explore, through thought by deductive or inductive reasoning and proceed through to the logical results to gain an insight

* PDMA handbook 2005 chapter 17, * Rochford Linda 2001

Redefining question Re-wording the question to change the perspective on the problem

* Jack Foster "How to Get Ideas"

How do I work harder to "how to I get more work done" (improve work efficiency)

Think like a child Being open to re-questioning base assumptions, look at the world with extreme curiously to find new relationships

* Jack Foster "How to Get Ideas" pg 55

Why do refrigerators have to have doors?

Lateral thinking The shifting of thinking patterns, away from entrenched or predictable thinking patterns to new or unexpected ideas

* Edward de Bono The Use of Lateral Thinking, published in 1967. * Jack Foster

Remove boundaries, and base assumptions

Remove boundaries, and retest base assumptions, do not assume restriction unless strictly told

* Jack Foster "How to Get Ideas" pg 102

Set strict limits Set limitations, remove typical options * Jack Foster "How to Get Ideas" pg 106

Find solutions within limitations

Purposefully break the rules

purposefully violate base assumptions, and rules * Jack Foster "How to Get Ideas" pg 115

Re-define the problem Change the format of the question, * Jack Foster "How to Get Ideas" pg 131

Abstraction Make the problem or situation more abstract * Rochford Linda 2001 Increase company revenue changed to better the company

Adaptation Adapting a solution, offering, process to suit a companies need by modifying it

* Rochford Linda 2001, * Hardagon 1997 & 2000

Reduction Reducing the amount, functionality, or features of a particular thing

* Blue Ocean Strategy 2005

Elimination Eliminating a particular, feature, attribute * Blue Ocean Strategy 2005

Raise or increase Increasing a particular feature, attribute or factor above the norm in that industry

* Blue Ocean Strategy 2005 Large button telephones, calculators and remotes

Creation Creating new features, attributes, factors, which an industry has not seen

* Blue Ocean Strategy 2005

Division of part Breaking up the whole in to smaller and smaller features, functions, or pieces

* Rochford Linda 2001

Iteration Repeating a process or set of actions with the goal of narrowing them down to a set of solutions

* Rochford Linda 2001

Devil's Advocate or methodical doubt

A method of exposing every weak point, while letting others quickly find solutions

* Rochford Linda 2001

Detailed observation Looking closely at something, trying to understand every facet and function

* Hardagon 1997 & 2000 * Tom Kelley 2001 & 2005

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Table 2.7. Activities which Specifically Trigger Creativity

Activities Description References

Brainstorming Creating ideas in open discussion, (typically many techniques are applied)

*Chapter 17 PDMA handbook 2005, Rochford, Ref Tom Kelley, Ref Hardagon, Hsiao, S. -., & Chou, J. -. (2004

Method "6-3-5" "6 participants write 3 ideas within 5 mins on paper, then pass ideas to next person till one full rotation is made

* Belliveau, P., Griffen. A., & Somermeyer, S. (2007) The PDMA ToolBook 1 for New Product Development, Hoboken, New Jersey: John Wiley & Sons. Inc

Problem inventory analysis

generating a list of negatives of a offering then finding solution to eliminate those negatives

(2007) The PDMA ToolBook

Visualization exercises Same as techniques just proceed as a formal activity

(2007) The PDMA ToolBook

Experimentation activities

Measure, tests, validate, explore, via physical, virtual, or thought experimentation

* 2005 PDMA hand book chap 17, Tom Kelly, Ref 30, Hardago, Stefan Thomke 2001

Scenario activities Instead of the technique, this a full activity where scenarios for marketing strategy, business unit strategy, tech strategy, were feasible scenarios are thought out

* Foster, J. (1996). How to Get Ideas, Berret-Koehler Publishers, San Francisco163 * Rochford, L. (1991). Generating and screening new product ideas. Industrial Marketing Management, 20(4), 287-296.

Six thinking hats role based brainstorming activities where each individual plays a different role, Facts, optimism, judgment, feeling, creativity, control

* DeBono Group http://www.debonogroup.com/6hats.htm

Focus group activities A collected group of individual focusing on giving feedback on a particular, product, service, and process

* Rochford, L. (1991). Generating and screening new product ideas. Industrial Marketing Management, 20(4), 287-296.Incubation &

relaxation

Relaxing and thinking lightly or not at all about the problem to be solved (sleeping) letting the mind sub-consciously work on the problem

* Foster, J. (1996). How to Get Ideas, Berret-Koehler Publishers, San Francisco163

Activities that are Specifically Creative

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Table 2.8. Activities which Seed Individuals with Ideas

Activities Description References

Environmental scanning

Scanning the outside environment in the areas mentioned in (environmental scanning)

Drucker 1985, Auster & Choo 1993, REF 27

Systematic search of a field

researching all direction starting from fixed starting point

* Rochford, L. (1991). Generating and screening new product ideas. Industrial Marketing Management, 20(4), 287-296.

Conferences and trade shows

Industry conferences to aid in learning about new knowledge, technologies, developments,

Reviewing idea databanks

Reviewing the ideas in an idea bank *Hardagon, A. and Sutton, R.I (2000) Building and innovation factory. Harvard Business Review, 78 May-June 157-166 Link

Technology fairs same as conferences but held internally just for employees

*Hardagon, A. and Sutton, R.I (2000) Building and innovation factory. Harvard Business Review, 78 May-June 157-166 Link

Suggestion & improvement capture

Capturing ideas and issues from internal and external individuals

Deep questioning Question with the goal of deeply understand all aspects of a offering, service, industry

* Foster, J. (1996). How to Get Ideas, Berret-Koehler Publishers, San Francisco pg 146.

Tech boxes Maintaining a archive of products, materials, pictures and other things that can seed ideas

*Hardagon, A. and Sutton, R.I (2000) Building and innovation factory. Harvard Business Review, 78 May-June 157-166 Link *Kelley, T., & Littman, J., & Peters (2001). The Art of innovation, Lessons in Creativity from IDEO, America's Le

Company get togethers

Meeting where employees can talk informally like at bars, restaurants, or parties

Seeding activities

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Table 2.9. Activities Which Use Analysis to Spawn Creativity and Ideas

Activities Description References

Opportunity identification Locating unmet needs or gaps in the market place that can present opportunities

* Flynn, M., Dooley, L., O'Sullivan, D., & Cormican, K. (2003). Idea management for organizational innovation. International Journal of Innovation Management, 7(4), 417-442.

Opportunity analysis Analyzing to see if a opportunity possess real value, and looking for potential problem and issue that can be solved to realize that opportunity * Flynn, M., Dooley, See above.

Customer needs analysis The customer needs are determined via surveying, interviewing, or feedback mechanisms. Feedback then is analyzed to determine customer needs

Wasted base analysis Looking for sources of waste tangible and in-tangible and finding ideas to utilize that waste

Competitive mapping Mapping competitor via, offering, pricing, branding, or other means to extract gaps and understanding

Analysis of customer feedback Examining customer feedback to determin unmet needs, or opportunities

Ethnographic research Researching customer behaviors and cultural aspects across different cultures to gain insight and understanding

Belliveau, P., Griffen. A., & Somermeyer, S. (2007) The PDMA ToolBook 1 for New Product Development, Hoboken, New Jersey: John Wiley & Sons. Inc

Application Examining possibilities and results by application (2007) The PDMA ToolBook

Attributes based discriminant analysis (PREMAP)

Develop by performing a discriminant analysis from brand's effective attributes, then mapping and analyzing them

* Rochford, L. (1991). Generating and screening new product ideas. Industrial Marketing Management, 20(4), 287-296. * Foster, J. (1996). How to Get Ideas, Berret-Koehler Publishers,

SWOT analysis Looking at the strengths, weakness, opportunities, & threats to a competitor or offering

Morphological analysis/ Matrix

"Splitting up problem into parts and look for partial solutions to each, leading to generation of ideas"

* Belliveau, P., Griffen. A., & Somermeyer, S. (2007) The PDMA ToolBook 1 for New Product Development, Hoboken, New Jersey: John Wiley & Sons. Inc.

Competitive intelligence activities

Observing, reporting, & documenting competitor actions (changes in offerings, prices, brand, partnership, strategy …)

Critical path mapping & analysis

Graphically representing activities their duration and finding gaps and problems with their flow

Dimensional investigation Mathematical equation used to relate functions, and economic properties of the product

* Belliveau, P., Griffen. A., & Somermeyer, S. (2007) The PDMA ToolBook 1 for New Product Development, Hoboken, New Jersey: John Wiley & Sons. Inc.

Porters analysis Using porter's analysis to understand an industry and gain insight into power relationship

Portfolio analysis Looking at the portfolio of offerings to find new possibilities, gaps, or weakness in the offerings

Gap analysis Comparing where a specific performance metric should be against where it is

Patent scanning Reviewing new or expired patents to see new product or service opportunities

Whole product solution analysis

Analyzing the offerings of an emerging market and determining which offering must be made to complete the whole product solution

* Moore, Geoffrey, (2004). Crossing the Chasm, HarperCollins Publishers, New York, New York,

Marketing research Researching the market, competitors, and market condition to determine trends, changes, and gain insight

Forecasting Predicting trends, and forecasting future developments in an industry, then trying to predict customer needs and requirements

* Kahn, K. B., Castellion, G., Griffin, A. (2005). The PDMA Handbook of New Product Development: 2nd (228-248). Hoboken, New Jersey: John Wiley & Sons. Inc.

Root Cause Analysis Looking for root causes of: failure, issues, and problems in the process of trying to diagnosis a system, behavior, or processes

Analysis based idea generating activities

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Table 2.10. Full Idea Generation Processes

Processes Description References

1 Full Contextual research process

Detailed studies of customer unmentioned needs and situation

* Conley, C.V. (2005). Chapter 15: Contextual Research for New Product Development. In A. Kahn, K. B., Castellion, G., Griffin, A. (2005). The PDMA Handbook of New Product Development: 2nd (228-248). Hoboken, New Jersey: John Wiley & Sons. Inc. Link to

2 Outcome based innovation Uncovers desired user outcomes then generates ideas to fill those outcomes

*Ulwick, A. W. (2007, Fall). Turn customer input into innovation. Harvard Business Review, 80(1), 91-97. *Sutton, N. (2007). Outcome-driven innovation®: A critical review. Masters thesis, Cranfield CERES

Ulwick's Job Mapping Define the job process then use a set of techniques to add, remove, combined, or split the jobs into parts, use that understand to generate ideas

* Bettencourt, L., & Ulwick A., The customer centered Innovation Map, Harvard business Review, May 2008 109-114

3 Deep Dive by IDEO Similar to contextual research but heavier on idea generation

* Kelley, T., & Littman, J. (2001). The Art of innovation, Lessons in Creativity from IDEO, America's Leading Design Firm, New York, New York: Doubleday publishers* Kelley, T., & Littman, J. (2005). The Ten Faces of Innovation: IDEO's Strategies for Bea

4 Blue Ocean strategy Heavy on new ways to analyze market to find gaps to generate new sub-markets with very little immediate competition

* Kim, W. C., & Mauborgne, R. (2005). Blue Ocean Strategy How to Create Uncontested Market Space and Make the Competition Irrelevant. Boston, Massachusetts: Harvard Business School Press

5 TRIZ based innovation A russian idea generation technique combined with strategy

* Hart M. book review of Fey, V., & Rivin,. E Innovation on Demand: New Product Development Using TRIZ, New York, New York, Cambridge University Press

6 Flynn's idea generation process

Utilizes environmental scanning, opportunity identification, and ends with idea generation

* Flynn, M., Dooley, L., O'Sullivan, D., & Cormican, K. (2003). Idea management for organizational innovation. International Journal of Innovation Management, 7(4), 417-442.

7 Lead User innovation Following and working with lead users to generate leading edge ideas

* Von Hippel, E., Thomke, S., & Sonnack, M. (1999). Creating breakthroughs at 3M. Harvard Business Review, 77(5), 47-57, 183.

8 Multi-day ideation retreats A fully structured retreat design to run through many idea generation activities over a series of days

* Miller, C.W. (2005). Chapter 17: Getting Lighting to Strike: Ideation and Concept Generation, In A. Kahn, K. B., Castellion, G., Griffin, A. (2005). The PDMA Handbook of New Product Development: 2nd (228-248). Hoboken, New Jersey: John Wiley & Sons. In

Full Idea generating processes

2.7.3. Review of top idea generation processes

Many of these techniques and activities are well known in business practices

while others are not. For the goal of brevity this study does not discuss any of the

techniques or activities in detail, and instead will concentrate on elaborating on

idea generation processes. These idea generation processes are consider

extremely valuable because they have been tested to be effective in generating

valuable ideas and again tie together a set of activities, which utilize multiple

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techniques to produce ideas. There seems to be few full idea generation

processes which have been proven to be effective in creating valuable ideas. An

individual could slap together a set of activities from the tables above and label it

an idea generation processes. But creating an effective idea generation process

is much more difficult. Hence, this research views proven idea generation

processes as gems, because of their rarity and difficulty in refining.

Consequently, the following section discusses the top idea generation processes

in detail.

2.7.3.1. The Contextual Research Idea Generation Process

Chapter fifteen of the 2005 PDMA handbook written by Conley (2005) reviews

contextual research for new product development. Contextual research can be

thought of as indepth customer research, where one looks for information about

what people do, rather than what they think and say. The context is the every day

situation of the customer, their environment; their behavior, the situation they are

in, and their local environment (Conley, 2005).

Typically, customer feedback leads to minor changes or incremental

innovations in the product, whereas, contextual research looks at the bigger

picture to determine unseen opportunities for innovation by looking at the

environment, interaction, processes, activities, and customer types. As Von

Hippel puts it, this information is “sticky” because it is very difficult for the user to

convey this detailed information” (Von Hippel, Tomke, & Sonnack, 1999).

The power of contextual research is its ability to communicate this “sticky”

information and use it to spot unmet needs or simulate new innovative ideas. The

process of contextual research involves: (1) designing the study, (2) selecting the

research team, (3) gathering required research tools like cameras, (4) selecting

the customers to observe, and (5) creating a topic guide for interviews.

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Figure 2.22. Illustration of the Contextual Research Process

The research is based on a vigilant observation of users in their

environment. This is commonly done by job shadowing or observation from a

distance. Also it is recommended that users verbalize their actions by talking

about them out loud. Activities should be captured on rich media like video,

photographs, and audio tape, as well as more traditional lead mediums like note

pads. It is recommended that this take place over several observation sessions.

After the research info is gathered it is analyzed to determine the goals of each

activity and then coded into bite-size chunks. Coding is used to identify patterns

of issues. “In analyzing data, one must avoid simply responding to problems

seen in the field, because many problems are symptoms of a larger systematic

issues” (Conley, 2005, p. 98).

The coded information is then used by the new product development

teams to extract insight and simulate ideas. Next, several brainstorm meetings

are performed with each concentrating on a different issues or patterns

discovered during coding. The generated ideas should be recorded, sorted, and

voted on, then documented. Reporting the contextual research to the larger

organization is a vital step, and helps seed other individuals outside the NPD

group with idea and information. Report of the research can be displayed by

videotaped examples, diagrams, illustrations, photographs, and in the traditional

written form. This process produces the largest benefit in that it develops a deep

understanding of customer needs which has been said to develop the most

valuable ideas (Veryzer, Mozota, 2005; Flint, 2002).

Another benefit is the hard to see customer issues and problems can be

uncovered and solved. Also by heavily document the finding, the research can be

used at future brainstorming session for years to come. Finally, by spreading the

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research results individuals all over the organization can be seeded with valuable

information. This can be thought of as taking advantage of the organization’s

creativity to help spawn more ideas. A typical study is cited to take 20 to 30 visits,

and take anywhere 12-16 weeks at a cost of $150,000 plus.

2.7.3.2. Outcome Based Innovation

Outcome-based innovation by Anthony Ulwick looks at gathering the customer’s

desired outcomes, not their espoused needs or wants. By doing so he states

more valuable products and service ideas can be obtained (Ulwick, 2007). He

also warns about the dangers of responding directly to customer wants and

whims, and says a company should not be entirely customer-driven. A major

change in the way interviews are conducted is required to gather the customer’s

desired outcomes. For example a customer may say he wants a medical tool

made out of a more expensive stainless steel, when in fact he is looking for an

outcome of increased durability.

The steps in the process are (1) plan the outcome-based customer

interview, (2) capture desired outcomes, (3) organize the outcomes, (4) have

customers rate the importance of each outcomes, (5) use the outcome to

uncover opportunities, and (6) brainstorm ideas for the selected opportunities.

Figure 2.23. Illustration of the Outcome-Based Innovation Process

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The first step requires the selection of the customers. Conducting outcome

driven interviewing requires training and practice because the interviewer must

coax out desired outcome not needs or solutions, then restate the outcome with

measurable results. For example, an interviewer must get the customer to say an

outcome like “they want to easily remove your oil in 5 minutes” not the feature of

“have a more accessible oil plug.”

Organizing outcomes requires compiling a list of collected outcomes,

removing duplicates, and categorizing outcomes into groups. Rating outcomes is

the next important step and requires the research team to present a full list of

outcomes to the user so (a) they can rate the respective importance of each

outcome, and (b) they can rate their level of satisfaction if that outcome is

achieved. Next the research team must categorize and rate uncovered

opportunities. Ulwick proposes a numerical rating system to rank uncovered

opportunities. Finally, the top opportunities are the topic of idea generation

activities like brainstorming activities.

The benefit of this process is that it is deeply rooted in customer

understanding, and better yet, the fact that the customer has identified his level

of satisfaction if the given outcomes can be satisfied. Hence, the risk that

customers may reject new proposed products and solution ideas is much lower.

So, this process is seen to develop higher quality and higher value ideas.

Moreover, the process starts by focusing on customers being served by the

company, but at the same time allows for new strategic options for new products

and services to be developed. This process is a poweful way of coming up with

high quality incremental and disruptive product and service ideas because it was

quoted to be successfully used and because it has a well thought out flow.

2.7.3.3. IDEO’s Idea Generation Process

IDEO’s idea generation process shares similarities to contextual research except

it is much shorter in duration and more intense in its level of activities. IDEO is a

world famous multidisciplinary design firm with their own special idea generation

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process focused on delivering valuable ideas in a short one or two week period

to their clients. Their process uses substantially fewer resources than a full

contextual research study (Kelley & Littman, 2005; Kelley, Littman, & Peters,

2001).

The process starts with a meeting with the client and the idea generation

team so the problem can be bounded, like developing a new tooth care product.

The team, typically multidisciplinary in nature, splits into subgroups, then goes

out into the field to observe users, buyers, and influencers of the target area

much like contextual research. After about a day’s worth of information collection,

the teams reassemble to discuss their findings.

Unlike contextual research, which spends a lot of time coding and

analyzing data, IDEO’s process goes right into discussing the findings. During

this discussion which is, like a “show and tell” activity, they discuss problems they

found, strange behaviors they noticed, and the overall context of the users’

situations. They do this by reviewing pictures, videos, or demonstrating activities.

Next they move into a series of brainstorming and screening activities. First, each

individual writes as many ideas as they can, in say, a 20 minute period, after

which they all discuss their ideas. Then a collaborative brainstorming session

takes place.

At the end of the session each individual is asked to submit their top four

ideas which are then posted on the walls around the room. The group votes on

the submitted ideas, and from one to three ideas are pushed into prototyping.

During prototyping the teams do everything they can to transform the ideas into a

physical or tangible prototype. The process ends with a formal presentation to

the clients where a few fully developed ideas along with their prototypes are

shown and discussed.

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Figure 2.24. Illustration of the IDEO’s Idea Generation Process

Again this process has a base in customer understanding, but not as

strong as a base in outcome-based innovation or contextual research. This

obviously helps ground the idea in a level of practicality, while giving it the

needed stimulus for brainstorming.

This process is also much heavier on the creativity aspect because many

of the activities are designed to simulate and encourage creativity. The

prototyping phase is pronounced, mainly because IDEO deals heavily with

customer product designs and because they see a strong creative value in

prototyping and experimentation. This process can be applied formally inside a

company; however, the culture required to effectively conduct this process must

be finely tuned to be tolerant of the wildly creative atmosphere required by it.

2.7.3.4. Blue Ocean Strategy

The main premise of Blue Ocean Strategy by Kim and Mauborgne (2005) is that

a market can be created which has all the attributes of the main market but has a

lower level of competition and much more room to grow. This approach makes

the analogy that existing markets are like red oceans colored by the blood of

competition, and that blue oceans are fresh untapped or emerging markets

where competition is relatively scarce or nonexistent. For example, Cirque du

Soleil created a new type of circus and Net Jets created a new market space

between charter jets, private jets, and commercial travel.

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Kim and Mauborgne (2005) proved the value of blue ocean markets

through their study of 180 companies which found blue ocean products and

services account for 61% of gross profits, even though they accounted for the

smallest number of launches (14% of total product and service launches). The

results of blue ocean activities can range from creations of new product and

services ideas all the way to dramatically altering the way a company offers its

business services.

Figure 2.25. The Strategic Canvas from Blue Oceans Strategy with

Three Plotted Value Curves

The Blue Ocean Strategy is built around the strategic canvas (shown in

the figure above) which is a very useful tool for analyzing factors of competition in

a market. Figure 2.25 shows the value curves of budget wines, premium wines,

and Yellow Tail wine. Notice the difference in the value curve of the Yellow Tail

as being high in fun. The combination of the value curves of Yellow Tail wine sets

it apart from competitors. Blue Ocean does not suggest a given process but

rather a set of activities which rather easily be combined into a formal idea

Wine Market

Low

Price

High

Rela

tive

leve

ls

Prestige Taste Fun

Yellow Tail Premium Wines

Budget Wines

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generation process. For the sake of clarity, this thesis has created one such

process based on pages 89 to 93 of the book (Kim & Mauborgne, 2005).

Figure 2.26. Illustration of a Blue Ocean Strategy Idea Generation Process

The proposed process starts with a development team conducting primary

research by speaking with customers, non-customers, competitors, and similar

solutions in different markets. The team then conducts secondary research

(literature scanning) on trends in the market, demand, major factors of

competition, and strategic changes in their markets. Next, the team proceeds

through six separate brainstorming activities, each resulting in two to three new

value curves. Each brainstorming activity uses the techniques of reducing,

eliminating, raising, and/or creating factors for the new value curves. The

brainstorming activities are:

1) Look across the industry to determine trade-offs which customers

innately make. For example, NetJets saw the trade-off in convenience and cost

between charter/private jets and commercial airline travel, and tried to capture

the best of each.

2) Look across strategic groups within an industry. Toyota did this when

they created Lexus by adding the quality and amenities of a Mercedes to Toyotas

while reducing the price, and removing some of the more expensive/un-

necessary features.

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3) Look across chains of users, influencers, & buyer to see if there can be

shifts, addition, reduction, or elimination in the value curve which would better

satisfy a single or all groups. An example is the paper towels which are

perforated in thirds stratifying mothers (buyers) who were concerned about their

children (users) wasting paper towels.

4) Look across complementary products and services which the

customers use before, during, and after. For example, Barnes & Noble uses in

store coffee bars and food to enhance their value curve because they realized

their customers were leaving to get those items and by putting those things in

their stores resulted in longer customer visits and a more pleasant customer

experience.

5) Look across functional and emotional appeal is simply taking something

functional and making it more emotional or vica versa. Starbuck added and

emotional experience to a coffee house, while the Body Shop removed the

emotional packaging and presentation of perfumes and soaps.

6) Look across time by having an insight into trends, “how the trend will

change value to customer and impact the company’s business model.” Three

principles to assessing trends are they must be decisive to your business, be

irreversible, and have a clear trajectory. For example, Cisco saw the trend for

increased data exchange and hence they adapted their value curve to fully take

advantage of this trend. Apple saw the clear trend of downloading music online

and legalized it with Apple’s iTunes.

After each of the brainstorming sessions, one to three value curves are

created. The new value curves are shown in a visual strategy fair where each is

discussed for 5 minutes. The judges (possibly executives) cast votes or assign

points to each curve. The best curves are then analyzed, tested, and refinement

using the buyer’s utility map, and price corridor of mass tools among others. After

refinement the ideas with their respective value curves are again presented to

the executive committee for review.

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Again the goal of the Blue Ocean Strategy process is very different than

other idea generation processes because it looks for ideas which can

dramatically change the strategy of a company. This researcher sees this as a

valuable process which could augment executive’s strategic planning processes.

One should note, ideas from this process most likely cannot be placed

directly into the new product development process, because they require

changes to the company as a whole which is greatly outside the scope of the

NPD process.

2.7.3.5. Flynn’s Idea Generation

Flynn’s process uniquely highlights environmental scanning as a major step. The

first step in his processes involves setting the strategic direction and can be

based on product portfolio needs (Flynn, Dooley, & O’Sullivan, 2003).

Figure 2.27. Illustration of Flynn’s Idea Generation Process

The goal of the next step, being environmental scanning, is to capture

stimulus and information. This activity should be bounded because not

everything can be observed. The goal of the following step, of opportunity

identification and analysis, is to find opportunities (as mentioned in section 2.6.7)

and validate the value of those opportunities. Finally, opportunities are used

along with information from environmental scanning in idea generation sessions,

and ideas are captured and recorded.

The major issue with this process is that it is too broad to be directly

useful. All of the activities could vary greatly in scope and be un-manageable if

not bounded, like environmental scanning. Hence, this researcher sees Flynn’s

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process as a general map which can be used to make more specific idea

generation processes. To illustrate this, Figure 7.28 shows a process which

more specifically generates ideas from information captured from competitors.

Figure 2.28. Modification of Flynn’s Idea Generation Process

2.7.4. Detailed Examination of Sources of Ideas

The previous part of this chapter had an underlining assumption that ideas were

being generated from individuals inside the company, which is not always the

case. Many more ideas are being generated by others outside the company

which could be turned into new innovative products and services. It is a severe

error to think ideas can only come from inside your company. This error has been

termed the “not-invented-here” syndrome (NIH syndrome) where a company

rejects idea generated outside its walls because they think those ideas are

inferior to their own. Ideas from outside the company, can be (a) used directly

with little or no modification, and/or (b) can be modified to suit the needs of

the company, and/or (c) can be used to seed people inside the company

with stimulus to help them generate their own ideas.

At present, there are many external sources of ideas; again a source is

an individual or group of individuals. Additionally, there are many internal sources

of ideas other than individuals in the new product development groups.

The literature on idea management and idea banks states many

companies in general lose or drop ideas which are not from their usual sources,

and hence idea management programs should be put in place to capture these

ideas (Flynn, Dooley, & O’Sullivan, 2003; Gorski, & Heinekamp, 2002).

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The following tables were compiled to show the many potential sources of

ideas, and also show respective activities and methods which can idea from

those sources.

Table 2.11. Major Categories for Source of Ideas

The sources of ideas have been split into five main categories. In-

particular, Alam (2003), Belliveau, Griffin, & Somermeyer (2002), and Stasch,

Lonsdale, & LaVenka (1992) have spoken in detail about sources of ideas and

provided a strong base to create the following tables. Employees are highly cited

as sources of ideas especially in articles discussing ideas management and idea

banks. Typically, executives and R&D employee submit ideas, but expanding the

envelope to all employees in the company can tap valuable sources of ideas.

Parnell, & Menefee (2007) show that employees may have different

perspectives based on their positions that may influence their decision making.

This gives a basis for the obvious assumption that employees in certain positions

may be more likely to come up with ideas based on their perspectives and duties.

So, a line operator may be more likely to come up with ideas for reducing line

cost and down time, while an executive may be more likely to come up with

strategic ideas to fend of competition.

Source

1 Employee sources / Internal sources

2 Customer sources

3 Organizational sources

4 Supplier sources

5 Competitor sources

6 Other companies

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Table 2.12. Employee Based Sources of Ideas

2.7.4.1. Customers as Sources of Ideas

Customers are the first major source of ideas, and have been split into the seven

categories shown in Table 2.13. Interesting most companies focus on their core

customers groups because they provide the bulk of the business. However,

innovation experts strongly advocate reaching out to new customer groups. To

avoid this natural tendency to concentrate on the core customers, 3M has an

edict which requires 30% of revenues of a business unit must come from new

products released in the last four years (Collins, & Porras, 2002).

Source Description Direct way to

get ideas In-direct ways to generate ideas References

1 Executive Executive in the company direct solicitation, utilized idea generation activities and processes,

Suggestion system, idea database

Ref 30, 58

2 Management Management professional in the company

Same as 1 Same as 1Ref 30, 58

3 Finance Self-explanatory Same as 1 Same as 1

4 Sales Self-explanatory Same as 1 Same as 1

5 Sales Reps Sales reps differ from sales in that they work for the company through in-direct means

contractual agreements, direct solictation,

Same as 1

Ref 30

6 Marketing Self-explanatory Same as 1 Same as 1 Ref 30

7 R&D Self-explanatory Same as 1 Same as 1 Ref 30

8 Customer service Self-explanatory Same as 1 Same as 1 Ref 30

9 Operation / production Self-explanatory Same as 1 Same as 1 Ref 30

10 Think-tank A group dedicated to coming up with new ideas, research, and knowledge

Same as 1 Same as 1

Ref 28,33,58,

11 Annoymous employees Self-explanatory Same as 1 Same as 1

11 Quality control Self-explanatory Same as 1 Same as 1 Ref 30

Employee Sources

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Table 2.13. Customer Sources Which Can Result in Ideas

Homogeneous customer groups are customer groups with similar needs

and attributes and are often studied during market segmentation studies. By

listening to them, ideas can be extracted which may better serve those groups.

A lead user was shown to be a source of ideas by Eric von Hippel, and is

defined as users who are working at the for-front of trends and technology in their

markets and are experience problems way before their peers. Von Hippel also

proposed a full detailed idea generation process for use with lead users, called

“lead user innovation” (von Hippel, Tomke, & Sonnack, 1999).

Dissatisfied users are a great, often overlooked, source of new ideas

because they are aware of the problems which led to their dissatisfaction.

Contacting dissatisfied customers is left to customer services which should try to

capture information from dissatisfied customers. This information can be used by

new product development team to come up with better ideas. For example, one

Source Description Direct way to

get ideas In-direct ways to generate ideas References

1 Homogeneous customer group

This is typically a sub-segment of the companies customer which all share similar characteristics and attributes

Direct solication; Customer submitted ideas; interviews; statifaction surveys; focus groups; customer contracts negotations, others

Deep market research; contextual research; problem analysis; Customer Gap Analysis; satisfaction surveys , many others

Ref 18,21,27,23,

2 Core customer groups

Customer groups that provide the bulk of the revenue or profit for the company.

same as 1 same as 1 Ref 54, 32, 30, 58, REF Neal & Corkindale 1998,

3 Lead User Highly advanced user has needs way in advance of the bulk of the market place, because they are visionaries and try an advances quiker to get a competitive edge

Direct customer request, interviews, lead user processes, focus groups, customer projects

See lead users innnovation process by von Hippel

Ref von Hippel HBR 1999, Urban & von Hippel 1986

4 Possible new customer group

Customers the company is not yet serving but would like to. same as 1 same as 1

5 Dis-satisfied customers

Customer that are dissatisfied and are still with your company, or have switched to a competitor. May also include dissatisfied customer of a competitor.

Customer interviews, customer feedback surveys, dissatisfaction survey, focus groups

same as 1

Ref 58, Wharton: How to turn customer ideas into innovation HBR Companies and the customer who hate them McGovern & Moon

6 User, inflencer, buyer customer groups

The individuals buying, using, and influencing the purchase may be very different. Each group should be considered differently for ideas, to better satisfy all groups.

same as 1 same as 1Ref Blue ocean strategy, Ref Harvard Business Review on Innovation 2001 Chan Kim & Mauborgne

7 Anonymous Customer who submit ideas annoymously or been recorded as annoymous

Received though annoymous submittion or direct contact but not recorded

Idea contests, suggestion systems

Ref 40

Customer Sources

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woman who was very dissatisfied with Nabisco Oreo packaging which could not

be easily closed, told customer service the company should change the

packaging immediately. The result? Nabisco (Oreo) released a simple resealable

flap that has since increased the freshness and consumption rates of their Oreos.

Users, influencers, and buyers are different customer groupings even

though they are often referred to as a single unit. For example, a user of a

construction tool may be a construction worker, the influencer may be a foreman,

and the buyer may be the owner of the construction company - each of which

have their own specific needs. Finally, customers may sometimes anonymously

submit ideas to a company. Unfortunately, follow-up feedback or additional

information cannot be obtained (Perk, Cooper, & Jones, 2005).

2.7.4.2. Non-for-profit Organizational as Sources of Ideas

NASA is well known to be a source of inventions and ideas, and has been

credited with many well known inventions like the microchip. National

laboratories are a government funded way of inducing innovations in US

companies by creating new knowledge and spreading novel concepts. There are

a number of national laboratories each having their own licensing and technology

transfer departments. Keeping up with the invention and discovery of all of these

can be a daunting task. National labs are very similar to NASA in that they all

have formal licensing departments and continually market their achievements.

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Table 2.14. Non-for-profit Organizational Based Sources of Ideas

National organizations are primarily non-for-profit organizations. Every country

has a list of national organization most of which are not funded by the country.

Examples would include NSF, boy scouts, and so on. The largest problem with

organizational sources is there are so many. It is difficult to know which ones

Source Description Direct way to

get ideas

In-direct ways to generate

ideas References

1 NASA NASA openly lists inventions that can be licensed and tries activity to seek placements for the promising technologies

Visit website, talk to licensing officer, scanning new technology releases

Scanning new technology releases at there website; scanning SBIR, STTR awards; Open innovation network

technology.jsc.nasa.gov/

2 National Lab National laboratory of the US and other country produce many technology related ideas

Visiting respective website, talking to licensing officers at each lab, solicing national labs, scanning new technology releases

scanning published literature, open innovation network

Limited by design, R&D laboratories in the US national innovation system Crow, Bozeman 2001 , www.lanl.gov, www.anl.gov, www.sandia.gov, www.jlab.org, www.bnl.gov, www.inel.gov,www.inl.gov, www.lbl.gov, www.nrel.gov, www.llnl.gov

3 National Org These are typically non-for profit national organization of all types.

Same as 1 Same as 2

4 University University are known for transferring inventions and discoveries to the private sectors, include professors, researcher, & students

Same as 1+idea competitions, + idea awards

Same as 2

5 Research Parks These are groups of research companies, where the research park promotes their technologies, and ides

Same as 1 + Open Innovation network

Same as 2

6 Groups of practices

This are organization dedicated to aiding a professional group, like the national society of professional engineers and the National lawyers guild

Same as 1 + conferences, meetings, networking, solicitations

scanning published literature, referral, search and find

6.1 Professional Same as 1 + Conferences, trade shows, meetings, talking to members

conference proceedings,

6.2 Consumer6.3 Economy Looks at general region

or nations 6.4 Religious/race

6.5 Interest/hobbies Hobby and interest groups.

Same as 6.1

7 Media sources Speaking with editors Searching media

Non-Profit Organizational Sources (not competitors)

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may have valuable ideas relevant to one’s business. For example, auto

manufacturers want to stay tuned into national or regional auto clubs and race

car teams so they can capture new technology ideas which could reduce cost.

Direct solicitation or hosting events like idea competitions are ways to extract

ideas from national organizations

Universities have been a hot bed of new technology and ideas over the

last 20 years and have been growing greatly in their licensing efforts in recent

years (2000-2008). The researcher, professors, and students at universities are

ripe sources of novel ideas, concepts, and creativity which can be harvested by

companies. Open innovation models include universities into their networks.

Scanning research papers on a particular subject area will show which

universities are highly active in those areas. Those universities can then be

directly solicited for ideas, via contacting the faculty, department heads, or

licensing technology officers. Similarly, idea competitions can be held to gather

ideas from universities. The rules may state who is allowed to compete:

professors, researchers, or students, but in the interest of gathering the best

possible ideas and open field is best.

Research parks are a rather new development and may be associated

with a university. They play a role in incubating technologies, and companies; as

well, as aid in transferring technologies to industry. The University of Rhode

Island found, that, as of 2004, there were 150 research parks in North America

(unauthored, 2004). Again, the methods of gathering ideas are similar to that of

universities; however, the licensing and business development officers are much

better able to direct solicitors to a relevant business in their research park.

Finally, there are thousands of groups of practice, such as the national

society of professional engineers and national lawyer’s guild. They include

international, national, regional, state, and local organizations. Yahoo directories

are an excellent means to locate groups of practices, because it is organized by

type, category and region; however, it does not hold all organizations. (See

HTTP://DIR.YAHOO.COM/BUSINESS_AND_ECONOMY/ORGANIZATIONS/ ).

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Groups of practices and be organized into professional (like the lawyers

guild), consumer (like association for consumer research), economy (social

venture network), religious/races, special interest, or hobbies (like Nascar or

aircraft owners & pilots associations). These groups of practice can be valuable

points of ideas. Again because there are so many, it may require more energy to

locate and solicit relevant groups of practices. One should also note that groups

of practice outside of a company’s core business area may hold sources of new

ideas. For instance, a boater’s conferences may hold valuable ideas for home

builders looking for water proofing ideas. Unfortunately, it can be time consuming

to join and scan groups of practices to far outside ones core business area.

2.7.4.3. Suppliers as Sources of Ideas

Suppliers are great sources of ideas and they can also help integrate those

ideas to one’s business. Suppliers were loosely structured to include any

organization which supplies a company with anything from work to actual goods,

and includes current and possible suppliers, consultants, idea consultants, and

research firms. Robert tucker states: “If you ask a supplier if they have any ideas

or new technologies they usually provide none, whereas, if you bring a problem

or opportunity to them and ask them to help solve it they are delighted and

provide many ideas” (Tucker, 2003, p. 2).

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Table 2.15. Supplier Sources

Amazingly, research firms were never mentioned as sources of ideas

before. Firms like Forester research which identifies trends in the market place

have an excellent sense of the opportunities which exist and often state such in

their publications. Also they can be contacted directly for ideas. Partners and

alliances were put under supplier sources because they supply resources,

knowledge, and capabilities to a company.

Source Description Direct way to

get ideas

In-direct ways to

generate ideas References

1 Current suppliers The current suppliers to a company could provide ideas

Solicitation, problem statement, direct contact, part of contract requirements,

Scan for news from suppliers, locate best practice suppliers, Open innovation networks

Ref 27, 54,

2 Possible suppliers These are possible supplier which may be activity or in-activity biding for business

Solicitation, direct contact, part of bid requirements,

same as 1

3 Consultants Consultants of all types may provide ideas.

contracting with consultants, solicitations, direct contact,

solicitation, open innovation networks

Ref 18*, 30

4 Idea consultants Using companies like IDEO, design firms,

requirements for contract

solicitation, open innovation networks Ref Tom Kelly,

5 Research firms Marketing, consumer, industry, and economic research firms can be sources of ideas

same as 1 solicitation, open innovation networks

Ref 59

6 Partners / Alliances Partners and Alliances which supply resources, knowledge, capabilities

Contractional agreements, + same as 1

solicitation, open innovation networks

Supplier Sources

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2.7.4.4. Competition as Sources of Ideas

Competitors could be great sources of ideas, as NPD handbook showed

many businesses are fast follower of the best in class competitor. Best in class

competitors are often cited in popular media as pioneering a new process,

releasing new products, and so forth. Ignoring best in class competitors can be a

large mistake because they are often rich sources of ideas.

Direct competitors are all the companies in direct competition to ones

business, which may include best in class competitors. While, indirect

competitors are companies which are in a similar business and are servicing

customers outside of markets which your business is concerned with. For

example, a car dealer in Indianapolis selling Jeeps is in indirect competition with

a car dealer selling Jaguars in the same area. Whereas a friendly competitor

may be a Jeep dealership in Denver Colorado who is willing to share helpful tips

and ideas.

Table 2.16. Competitor sources

Source Description Direct way to get

ideas In-direct ways to generate ideas References

1 Best in class competitors Best in class competitor are often looked toward for sources of new ideas

Direct communications with competitors, competitative intellegence, direct observation

Market research firms, best in class practice reports, GAP analysis of competitors, SWOT analysis of competitors, competitive mapping, porters analysis, market research

REF 3, 18

2 Direct competitors Direct competitors to the business

Same as 1 Same as 1REF 3, 18

3 Indirect competitors Competitors in market outside of the companies given competivite area,

Friendly communication, + same as 1

Same as 1

4 Friendly competitors Friendly competitor that are not in real competition with one's company

Direct solicitaion, Friendly communication, + same as 1

Same as 1

5 Substitute sources As Porter defines markets that could be substitutes to ones market

Same as 1 + industry trends reports Same as 1

6 New potential entrance sources

As Porter defines markets that could be threats to enter ones market

Same as 1 + industry trends reports Same as 1

Sources from competitors

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Substitutes are, as Michael Porter defines it, products and services which

can be substituted for ones which your company is selling. For instance, cereal

companies look at substitutes like breakfast bars, fast food restaurants, and

others cereal substitutes for changes and new ideas.

Finally, potential new entrances are companies treating to enter the

industry. For example, the core US airline market close observed the launch of

JetBlue and closely examined all of JetBlue new innovative like in seat TV

systems.

2.7.4.5. Other Companies as Sources of Ideas

Unfortunately the category of direct competitors and non-for-profit organization,

do not account for the millions of for-profit companies which exist that can be

used as potential sources of ideas. Most notably, media sources are great

sources of ideas.

Media sources include publications like: journals, magazines, patents,

article databases, books, articles, and new publication; as well as, media like

radio programs, television shows, and movies.

Table 2.17. Sources of Ideas From Other Companies

Keep in mind the original author is the source of the idea and the

publishers, being the media companies, are the means of distribution. If one

considers the publishers a group of individuals then they would be a formal

Source Description Direct way to get

ideas In-direct ways to generate ideas

References

1 Other companies All other companies around the world

All All

7 Media sources Books, magazines, articles, patents, newspaper,

Speak with editors, Searching media

3 Inventors Indepent inventors direct solicitation, scanning new invention disclosure

Sources from other companies

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source of ideas, even though they are re-distributors. For instance, a magazine

like Harvard business review are great source of ideas for improving

management even though the new source of the idea may be Michael Porter.

Media sources may be great sources of ideas which should not be

neglected. Formal scanning mechanism for new ideas should include relevant

media sources because of their targeted nature and breadth of coverage.

Independent inventors are also valuable sources of ideas however they

are difficult to locate, contact, and solicit. Nonetheless, having one or two highly

talented inventors which can be called upon for idea can be of great value.

2.7.5. Issues with External Sources of Ideas

Of course there are many issues with obtaining ideas from outsides sources.

Some companies believe receiving outside ideas may jeopardize internal

development efforts. For example, this researcher contacted Arm-hammer to

submit an idea but was sadly informed they will not listen to outside ideas.

There are hundreds of issues in setting up and receiving ideas from

external sources. One should consider the benefits and downsides carefully. If

possible the downsides should be reduced or eliminated via creative problem

solving, because there are greater benefits than risk in sourcing external ideas.

Also, one should remember their own company may be afflicted with the not-

invented-here syndrome, which may severely limit their ability to innovate.

2.7.6. Which Source of Ideas is the Best?

Given the detailed review of the sources of ideas, one might ask: “which sources

of ideas are the best?” The answer is: “it depends.” It would be ludicrous to state

one group is the best sources of ideas. There are too many factors affecting the

production of ideas from a single source to make any kind of reasonable

conclusions across sources. For example, things like: culture, management,

leadership, and incentives vary greatly between even similar sources of ideas.

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Additionally, the typical sources of high quality ideas in one industry may be

different than another industry. So given those variations and the large number of

affecting factors, concluding one source is the best source of ideas is absurd.

The question should instead be: “what sources can this company turn into

great sources of ideas?” This would suggest things can be done to improve the

quality of ideas coming from internal and external sources. The following sections

will dive into and explore the feasibility of this suggestion.

2.7.7. Major Issue with Idea Generation (Lack of Control Models)

Unfortunately, even after this detailed review of idea generation and its

respective literature; no models were uncovered which could be used to manage

the whole idea generation process. This represents a massive gap in the

literature. Further, a conceptual understanding of how to manage the idea

generation process has not been developed in the literature. This constitutes a

severe limitation in the literature which must be rectified.

2.7.8. Summary of Section 2.7

To summarize, a detailed series of tables respectively showing idea generation

techniques, idea generation activities, and idea generation processes were

created to fill the gap in the literature. Following this discussion, the top idea

generation processes were described and critiqued.

The next section described how companies may react differently to

outside ideas based on their innovation category and level of concept

development. This was followed by a detailed series of tables showing the

sources of ideas, which was offered to fill a gap in the literature.

Finally, this section concludes with the question “what can be done to

improve the quality of the ideas generated?” This question will be addressed in

the Chapter 3.

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2.8. Literature Review of Idea Management and Idea Banks

2.8.1. Introduction to Section

The following section will review idea management and idea banks with the goal

of fleshing out the knowledge required to manage the fuzzy front end of

innovation.

The following section begins by explaining what idea management and

idea banks are and then go into why they are so important and valuable. Then

this section will move into a detailed review of several key articles on this topic.

Finally the section ends by stating several problems and issues with the

knowledge in this area.

2.8.2. What is Idea Management and What are Idea Banks?

Unlike the Fuzzy front end, there are very few definitions for idea management.

Drawing from other papers on idea management, this thesis defines idea

management as the process of capturing, storing, and organizing ideas can

be used in other processes, like the late FFE processes (Flynn, Dooley, &

O’Sullivan, 2003; Belliveau, Griffin, & Somermeyer, 2002; Montoya-Weiss &

O’Driscoll, 2006; Gorski, &Heinekamp, 2002; Bakker, Boersma, & Oreel, 2006;

Heck, 2005; Fritz, 2002; Dijk, & van de Ende, 2002; Koen et al., 2001). Also idea

management can be used to perform preliminary evaluations and screening

of ideas as well as diffuse ideas across the company

In contradiction to this definition, Vandenbosh, Saatcioglu, and Fay (2006)

proposed that the “concept of idea management is defined as the process of

recognizing the needs for idea and generation and evaluating them”

(Vandenbosh, Saatcioglu, and Fay, 2006, p. 32). This thesis finds this definition

limited, because it severely overlaps with the management of idea generation

process and more importantly contradicts other references on idea management.

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Idea banks can be defined as a tool for facilitating the capture, storage,

and organization of ideas (Moskowitz, 1997; Zien, & Buckler, 1997; Gorski, &

Heinekamp, 2002; Bakker, Boersma, & Oreel, 2006; Heck, 2005; Fritz, 2002;

Dijk, & van de Ende, 2002; Koen et al. 2001).

Also suggestion systems or suggestion programs can be defined a

process or system for capturing, storing, and organizing ideas

(Backman, Borjesson, & Setterberg, 2007; Flynn, Dooley, & O’Sullivan, 2003;

Gorski, & Heinekamp, 2002**; Fritz, 2002; Gamlin, Yourd, & Patrick, 2007;

Lamont, 2004; Dijk, & van de Ende, 2002; Stasch, Lonsdale, & LaVenka, 1992).

2.8.3. Need for Idea Management and Idea Banks

The literature discusses a clear need for idea management. Flynn et al. (2003)

describes the need for idea management in their quote: “However the process by

which organizations generate these ideas is one which has received significantly

less attention and been allowed to develop in an “ad-hoc” fashion” [thus] it is

logical to maximize the output of the idea creation phase” (Flynn et al., 2003, p.

3). Since there are more ideas accessible in idea banks the “increased

competition between ideas will ultimately improve the quality of potential

innovations being presented to the process” (p. 3).

Gorski & Heinekamp (2002) state that “collecting and evaluating ideas is

downplayed because managers believe they have ample ideas” (Gorski &

Heinekamp, 2002, p. 74). This may lead into the need to extract and capture

ideas as stated by Dijk & Van de Ende (2002), “apparently, there is a large

dormant reservoir of useful ideas in many companies, but communicating these

ideas is not simply a matter of offering large bonuses” (p. 62). According to Dijk &

Van de Ende (2002), “research showed that in Swedish industry of 1970 that

60% employees that had good ideas didn’t communicate them” (Dijk & Van de

Ende, 2002, p. 11). Price Waterhouse, Ernst & Young, “advocated that

companies adopt processes to collect and preserve their internal ideas” (Fritz et

al., 2002, p. 36). This may be because many ideas are lost or dropped from

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internal sources (Flynn, Dooley, & O’Sullivan, 2003) or because “firms overlook

other employees as a source of creative ideas” (Gorski, & Heinekamp, 2002, p.

58). An analysis of this information suggests that the value of idea

management and idea banks in the innovation process involves:

1. Capturing and storing ideas from internal and external sources

2. Utilizing the ideas by sending them to appropriates people and processes

3. Locking in intellectual property rights.

The first category of capturing and storing ideas is important because, it

seeks to take advantage of ideas created inside and outside the company which

otherwise might be lost or poorly utilized. Second, it is important because it is a

formal method of capturing and keeping ideas from formal idea generation

processes and activities. Third, it increases the idea options available to the

company. Finally, and most importantly, it better utilizes the creative capacities of

employees inside the company to produce ideas and locate opportunities.

The second category helps to better capitalize on ideas for present and

future use. Additionally, ideas can also be used as a stimulus for other idea

generation activities or aid in locating and identifying other opportunities.

The third category concerns locking in intellectual property rights which

facilitates processes related to obtaining patents, copyrights, trademarks, and

trade secrets. Capturing ideas from sources (like employees) which may no

longer be accessible (maybe because they left the company) is a benefit which

falls under this category (Gorski, & Heinekamp, 2002).

2.8.4. Terminology for Idea Banks

There are several terms which have been interchanged with the phrase “idea

banks”, including: idea pools (Tucker, 2003), idea war chest (Montoya-Weiss &

O’Driscoll, 2006), idea refrigerator (Zien & Buckler, 1997), and idea archives

(Bakker, Boersma, & Oreel, 2006). Each metaphor makes one imagine the

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concept of an idea bank in a different way. Idea pools may make one imagine

ideas as a stream of water which can be kept, depleted, and refilled. Idea banks

call to mind ideas as being safe and secure, while idea war chests recollect

valuable ideas which can give a competitive advantage.

However, one must also remember metaphors limit the way a concept can

be viewed. For example, an idea archive may make one feel that ideas are in a

solid and manageable form which can always be organized and cataloged, when

in fact many ideas are intangible and often only exist in people’s minds. Thus,

one must always remember the terminology we use also limit our understanding

of a concept.

In reviewing these terms, this researcher noticed all of these terms viewed

ideas as solid forms which can be managed. But, in reality ideas often exist only

in people’s minds and sometimes are only revealed through spontaneous

conversations. In order to capture the sometimes intangible nature of ideas, this

thesis proposes the term “idea cloud” to account for the larger group of ideas

which may be stored in people’s minds. The term “idea cloud” denotes a thing

with light boundaries which cannot be easily mapped and may exist anywhere.

The term “idea cloud” will be used in the next section of this chapter to clarify

idea banks.

2.8.5. A Review of the Literature on Idea Management and Idea Banks

The following section will review key articles on this topic area

2.8.5.1. Review of Chapter 9 of PDMA

Chapter 9 of PDMA ToolBook for New Product Development, written by Gorski

and Heinekamp (2002), provides an excellent overview of idea banks and idea

management. The goal of an employee suggestion program is to pull from the

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unique knowledge of the workforce in order to identify new product opportunities

and process improvements. The authors discuss the history of suggestion

programs. Here, they say, idea suggestion programs trace their roots to the total

quality movement of the late 1980s’ but similar programs have existed for

hundreds of years. Interestingly, the first suggestion boxes, they claim, were

implemented in the 1880s by a shipbuilder and in 1895 by NCR, and consisted of

standardized forms which were filled out and placed into suggestion boxes. After

a couple days the forms were removed then the ideas were recorded in a master

log.

The authors state that “employee suggestion box systems remain in use

today, many still in their original format” (Gorski & Heinekamp, 2002, p. 83).

Beneficially, the authors provide a table of the strengths and weaknesses of the

suggestion box system, where the most notable weakness is its slow,

cumbersome nature, loss of ideas, and horrible participation rates.

The authors then move on to the “Kaizen” idea program, which also

captured ideas for improving operations and greatly outperformed suggestion

box systems by resulting in participation rates of up to 75% unlike the 10-20%

participation rates of a typical American suggestion box program. The greatest

weakness is its focus on incremental changes.

Next, the authors discussed employee-driven idea systems (EDIS) which

are a variation of the Kaizen idea program, where the idea submitter became

responsible for driving the idea from concept to implementation. EDIS systems

were mentioned to have higher participation rates, quoted to be around 60%. The

largest weakness of EDIS is their focus on incremental change and the ability of

the submitter to implement the ideas.

Lastly, they discussed the web-based idea collaboration systems which

use a software program or internet website to capture ideas. They also

mentioned that web-based idea banks greatly reduced the energy required to

submit, collect, manage, and diffuse ideas. They mentioned several weaknesses,

including: there can be large amounts of ideas submitted which could easily

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overwhelm the managers, and ideas may be stolen since they are viewable by

anyone in the company; and submitters may not get feedback on their ideas and

be left feeling frustrated.

Next, the authors provided an example of how a web-based idea system

was put in place at Bank One. From this they derived a step-wise list for

implementing an idea system. Here they state the steps are:

1) reviewing current methods for idea capture,

2) gaining management support for the new system,

3) defining the new product idea program,

4) defining the scope of ideas to be captured and audience members which

may participate,

5) establishing idea ownership,

6) choosing the form of the system,

7) implementing and evaluating the system,

8) establishing measurements and goals,

9) defining awards to push participation,

10) training employees to use the system, and

11) setting up ongoing administration and maintenance.

Again the value in their chapter is the review of the idea capture systems, and

the step-wise-process for implementing an idea capture system. However, one

major issue with this paper is they only consider ideas from internal sources as

coming from employees.

2.8.5.2. Review of Vandenbosh, Saatcioglu, & Fay

The article entitled “Idea management: A systemic view” by Vandenbosh,

Saatcioglu, and Fay is interesting because it looks at the influence which

personality types have on idea management and idea generation. In this article

they defined idea management as the process of recognizing the need for ideas,

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generating, and evaluating them. They then observed personality affects idea

management, and then proposed five types of personality categories.

1) Incrementalist take small steps, ideas are usually modest changes

2) Consensus builders focus on harmony among stakeholder rather than

ideas

3) Searchers combined info from diverse places,

4) Debaters argues to develop ideas

5) Assessor seem to be infinitely objective and flexible

Most of the individuals they interviewed in their small sample fell into the

incrementalist category. Consequently, this article gives an interesting view into

how personality can affect idea management.

2.8.5.3. Review of Montoya-Weiss & O’Driscoll Article

Moving back toward software programs for idea bank and idea management,

Montoya-Weiss & O’Driscoll (2006) article “From Experience: Applying

Performance Support Technology in the Fuzzy Front End” shows an interesting

application of idea banks and idea management at Nortel communications

company (Montoya-Weiss & O’Driscoll, 2006, p. 73).

The case study of Nortel revealed they would only create ideas upon

customer request and thus were totally failing to use their employee bases as a

source of ideas. From this obvious need Nortel developed a software solution to

capturing ideas from internal sources and named it “Galileo”. Their article also

highlights FFE evaluation, and screening is often done at a “gut-level” instead of

by a standard objective set of criteria. Their solution to this issue was to have the

idea capture software integrate preliminary screening and evaluation of ideas into

the submission processes.

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Figure 2.29. Montoya-Weiss & O’Driscoll’s Idea Generation Process

Figure 2.29 shows this researcher’s depiction of the process where ideas

are captured in mass, then qualified by having them pre-screened “in a

consistent manner at a very high level” (p.27). The objective of the first phase is

to: (1) standardize screening, (2) validate ideas in their primary area of market

readiness and technical feasibility, and (3) capture IP.

Again, the software program guides users submitting ideas through these

self-screening, and self-analysis activities. This researcher considers this method

of capturing then self-screening and self-analysis valuable because, it gives the

additional information need to categorize, analyze, and select ideas for later FFE

processes.

Next, the concept development phase is designed to “assist idea

generators in ‘growing’ their embryonic idea into robust, fully developed

concepts” (Montoya-Weiss & O’Driscoll, 2006, p.18). Here the software program

provides a set of deep probing questions which must be answered in areas

ranging from benefit, all the way to, alignment with the business strategy. By

answering these questions the idea owner develops the idea into a concept.

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The following concept rating phase is to provide a common framework

within all NPD ideas can be quantitatively rated where ideas are quantitatively

and qualitatively rated in the areas of marketing, technology, human factors, and

business.

The decision maker who evaluates the submitted ideas can then use

the results of the concept rating phase to select ideas to be assessed and

developed in FFE activities. This phase called “concept assessment” performs

this task and goal is to “reduce the subjectivity and lack of information that is

typically associated with idea evaluation and selection decisions” (Montoya-

Weiss & O’Driscoll, 2006, p. 53). In this phase the decision maker is taken

through a standardized idea evaluation process.

The strength of the software based approach to idea management and

idea capture is they integrate evaluation and screening into the idea capture

process. However, this approach is also seems to have many downsides.

First, the system can be easily “gamed” by individuals who want their

ideas pushed to the top. Hence, individuals can over estimate the potential of the

ideas in each phase resulting in ideas which look juicer than they actually are!

In addition, it is hypothesized that self-rating of ideas can result in a

preliminary analysis which is totally off from the actual potential of the idea.

Predicting the potential of ideas is very difficult task, and many activities of the

late FFE are dedicated to this. Hence, it is hard to imagine that the large amount

of uncertainty associated with a rough concept will allow ideas on average to be

rated with any meaningful level of accuracy.

Additionally, the nature of the system seems to limit creativity by going

straight into analysis rather than allowing individuals to collaborate and mold a

particular concept with other concepts resulting in a superior idea.

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Finally, the biggest issue is the reliance on software to help manage the

FFE. This researcher strongly believes that relying on a software tools to manage

the FFE process is a vital error since an in-depth understands of the FFE must

be developed first. In other words, management’s understanding of the FFE

should drive the use of particular tools, not the converse, where the tools drive

management’s activities.

2.8.5.4. Other Articles Discussing Idea Management

Flynn, Dooley, O’Sullivan, and Cormican’s (2003) article on idea management

discuss innovation, creativity, idea generation, and idea creation software.

Interestingly, the idea generation software they propose enables cross-functional

teams to brainstorm over intranet connections and capture ideas. Another

interesting benefit of this program is that ideas can be traced back to their

sources so those individuals can be rewarded. However, it is questionable how

effective brainstorming in virtual teams can be. This researcher prefers the

collaborative and high energy nature of face-to-face brainstorming sessions.

Van Dijk and Van den End described in detail suggestion systems at

Xerox, KPN telecommunications, and Shell Oil Company (Dijk & Van de Ende,

2002). They also noted a huge difference in participation rates where employees

in Japanese companies’ participation are five to ten times that of American

companies. Notably, they highlighted the following areas with respect to

suggestion systems: encouragement to participate; creativity; accessibility;

organizational support; committed resources; and idea feedback.

Bakker, Boersma, & Oreel (2006) discussed an “idea capturing” software

called “Eureka” which is used to capture, review, evaluate, and select ideas. In

their models of creativity management, they emphasize the links between

creating ideas, selling ideas, and funding of ideas. They also showed at what

stage an idea should be placed in the idea archive. Additionally, they depicted

the idea archive as a trash can which keeps potential intellectual property in

storage as shown by Figure 2.30.

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Figure 2.30. Bakker, Boersma, & Oreel Idea Storage Processes

Interestingly, they speculated that having a backup of rejected ideas can

help one avoid wasting energy in re-screening and re-evaluating rejected ideas.

They stated that “electronic idea management systems that are used in the crea-

political phase have both an enabling and a constraining effect upon the success

of an idea” (Bakker, Boersma, & Oreel, 2006, p. 57). Bakker et al asserted that

“the management must be aware of the fact that an electronic idea management

system is not a neutral element in the process of creativity management, but one

which produces an effect within a context in which creative ideas must be

transformed into practicable idea” (Bakker, Boersma, & Oreel, 2006, p.3). To

avoid one such unintended consequences, employees should remember idea

capture systems will not do the hard-work of developing and selling the idea for

them (Bakker, Boersma, & Oreel, 2006, p.53).

Other research on creativity and idea capture systems should note Lu’s

(1992) thesis which proposed a very early version of a collaborative

brainstorming software used over an internet connection. Since then, a wide

array of collaborative and idea capture software protocols have been proposed

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including: Akiva, BrightIdea, Imaginatik, Kerika,Qmarket, Innovator

express, Accept Innovation Management, Employee Suggestion Box ,

NextNet, Incubator , Hype.de, and so on.

Gamlin, Yourd, & Patrick (2007) referred to Cooper’s quote, “Idea

generation is everyone's job and no one's responsibility," when they described

how “no one individual in a company or business unit is specifically in charge of

idea generation, and often, when new ideas surface, no action is taken” (p. 30).

These authors then discussed an idea capture software with unique features

allowing for online collaboration and the ability for one to connect to experts in

particular areas.

Lamont’s (2004) article, “Idea management, Everyone’s an Innovator”

again discusses idea capture and management software, but emphasizes idea

champions being assigned to particular ideas to get them through the process.

She also views idea management as a component of knowledge management.

In addition to these articles, there are several dozen short magazine and news

articles on idea management and idea capture software, all promoting software

based solutions. Again, there may be some harm in relying solely on these items.

So in reviewing the literature on idea management and idea banks it is

evident that, the bulk of the literature focuses on software and web programs

which store, manage, and screen ideas. Only a few articles, as mention look at

management practices in any useful detail. As well, only a few papers describe

process models for idea management and idea banks (Montoya-Weiss &

O’Driscoll, 2006; Chang, Chen, & Wey, 2007).

Interestingly, idea banks and idea management integrate activities from

the early and late front end of innovation, where these activities are idea

generation, screening, collaboration, and development of ideas into the concept.

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2.8.6. Problems and Issues with Idea Management and Idea Banks

This research has identified many problems and issues with the current literature

on idea banks and idea management which is preventing it from being utilized to

its fullest potential. Hence, the remainder of this section will describe these major

problems.

First, the idea management and idea banks do not link to idea generation.

Only one article (by Flynn and his co-authors) states that idea management

should include and link to idea generation. All of the other literature assumes

ideas are captured by employees willingly submitting their ideas into idea banks,

but no articles discuss submitting ideas as part of a pre-designated idea

generation process.

Second, many articles on idea management and idea banks discuss

analyzing and screening ideas so they can be better used in late FFE processes.

However no articles suggest providing feedback of the assessed ideas to aid in

controlling and managing the idea generation process.

Third, no articles on idea management look at the idea banks as an early

means of portfolio management which can be used to tune and select the idea

generation processes needed to fill the product portfolio. Hence, the literature on

idea management totally fails to link usefully to idea generation processes.

Fourth, as mentioned there is no link between idea management and idea

banks and portfolio management.

Fifth, there is no research or survey data indicating the usage of idea

banks or idea management amongst companies. This represents a major gap in

the literature.

Lastly, and most importantly, there are no theoretical models showing

points of control for idea management and idea banks which can be used in the

management of early front end processes.

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2.8.7. Summary of Section

To summarize, this section examined what idea management and idea banks are

and the importance and value they provide for the front end of innovation. The

state of the literature was reviewed, and several key articles on idea

management and idea banks were reviewed in more detail. Finally, many

problems with the literature and knowledge in idea management and idea banks

were discussed. The following chapter will try to address these problems plus

illuminate new theories which can be used to manage idea banks.

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CHAPTER 3. DEVELOPMENT OF CONTROL MODELS

This chapter addresses the first research question: “From a review of the

literature, can a control model be developed to aid in the conceptual

understanding and management of idea generation and Idea management?”

To meet this goal, this chapter begins with a review of management

control models, and then select the most appropriate control theory for

development of this researcher’s control model. Next, the major points of control

for idea generation are examined and decided upon. Finally, the major points of

control for idea management are examined and decided upon. The combined

control model is illustrated in Figure 3.16. It is strongly believed that the proposed

model called the Glassman Model © will facilitate the conceptual understanding

and management of the idea generation model.

Chapter 4 proposes a research methodology to answer the second

research question: “Can the proposed idea management control model be

supported as capturing the required factors needed to manage and control idea

generation and idea management?”

3.1. Review and Selection of a Control Theory

There are several control theory models which can be applied to create a control

model for idea generation and idea management. One of the most famous is the

cybernetics-based theory of control. Kirsch (1997) defines cybernetics as, “the

process of comparing actual performance with planned performance, analyzing

variance, evaluating possible alternatives, and taking appropriate corrective

actions as needed” (p. 2). Cybernetics is a very common approach to control

where feedback on outcomes is used to determine gaps and necessary

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corrective actions. However, cybernetics has been criticized because it ignores

behaviors, corporate culture, the environment, and self regulation (Jaworski,

1988).

Other models of control are: outcome-based control, behavioral based

control models, clan models, self-control models, feedback control models, and

control process, along with others. The outcome-based control model “allows

employees to decide their method of achieving the given goal” (Schwepker,

Good 2005, p. 3). The general sentiment among innovation practitioners is that

outcome-based control of idea generation is very ineffective and inefficient at

generating needed ideas. Further, Steven & Burley’s (1997) idea curve has

shown the dismal conversion rate of ideas to selected concepts at a 3000 to 1

ratio. More importantly, if the outcome-based control model worked for idea

generation, there would be no need to answer the proposed research questions

for this dissertation, because companies would already be good at generating

ideas to meet their respective needs.

Behaviora-based control models seek to control behavior by articulating

rewards and punishments for behaviors (Kirsch, 1997). Unfortunately, this model

of control cannot be used for idea generation because it assumes that prior

knowledge of effective and appropriate behavior exists. The literature on idea

generation does not highlight effective behaviors. If anything, the literature shows

anecdotal unsupported behaviors which supposedly stop or obstruct ideas from

being generated (Foster, 1996). Thus, behavior-based control models cannot be

used herein, for the main reason that there are no known or proven behaviors to

base them on.

Clan control models use the company’s culture, values, beliefs, and

philosophy’s as a means of control (Kirsch, 1997). Research on the culture of

innovative companies has shown a tremendous amount of variance among them,

further no studies have been conducted across several companies to show which

cultural attributes promote control of idea generation. Consequently, clan control

models should not be used because (a) company culture takes a long time to

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establish, (b) are not feasible as implementing as a method of control, and (c) no

supported knowledge of cultural control for idea generation exists.

Feedback control models are common in marketing control and again fall

under the cybernetics paradigm. Tadepalli (1991) says feedback control models

are, a “reactive approach to control in which managers wall for problems and

take corrective action. In terms of marketing control, the feedback method forms

the basis for the control process” (Tadepalli, 1991, p.26).

Control process models are also based on the cybernetic paradigm.

Tadepalli (1991) states that control process involves “the following steps: set

goals and performance measures, measure achievement, compare achievement

with goals, compare variance between achievement and goals, report variances,

determine cause(s) of variance, take action[s] to eliminate variance, and follow-

up to ensure that goals are met” (Tadepalli, 1991, p.26). Control process models

provide an excellent base for idea generation because it can be viewed as a

process which can be controlled. In idea generation, the outcome (i.e., ideas) can

be measured and variance from the set goal of ideas can be found and corrective

action can be taken.

Jaworksi (1988) terms control points as being input control or process

control, where input controls are “common input control include selection, criteria,

recruitment and training programs, manpower allotments, strategic, plans, and

forms of resource allocation” (Jaworski, 1988, p. 5). In addition, process controls

are “exercised when the firm attempts to influence the means to achieve desired

ends. It differs from output control in that the focus is on behavior and/or

activities, rather than the end result” (Jaworksi, 1988, p. 5). Integrating this into

an illustration, one would see the figure below.

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Figure 3.1. Process Control Model

Jaworksi (1988) further describes formal and informal means of control

where formal are selected knowingly and stated explicitly. He further identified

four main criteria to distinguish formal and informal control where formal control

is (1) documentation by management, (2) implicit assumption of conformance, (3)

initiated by management, and (4) management is responsible for maintaining the

formal system, where informal control is the opposite of those four criteria.

So the final selected control model will be a linear process control model

using formal input and process control only, this model is shown below. Again,

the process control model has been shown in field of management, operation,

marketing, electronic and so on, to be an effective means to controlling a

process producing a few very specific measurable output, like reports, quality of

manufactured goods, goods per hour, and so on.

Management of Process

Idea Generation Processes

Inputs Controls

Process Control

Outputs

Difference between Outputs and desired results = Gap

Feedback to tune controls

Figure 3.2. Process Control Model with formal input and process controls

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Further, it is believed there are several benefits in selecting this simplistic

process control model. First, because of its simplicity practitioners will be able to

readily grasp the process and major point of influence. Second, because it will be

linear it over comes the inherent confusion in circular loop control model as

stated by Morse’s (2005) article “Crap circles.” Finally, it will be easier for

practitioners to identify weaknesses in their own methods of control and work to

strength them.

3.2. Development of a Control Model for Idea Generation

3.2.1. Continuous Idea Generation vs. Event Based Idea Generation

It is hypothesized that, many businesses continuously come up with a stream of

idea while others may generate ideas in spurts say as a response to a strong

need for more ideas. There is evidence to suggest that some companies, like 3M

and Google, continuously create streams of new ideas. There is also evidence of

companies which generate ideas in groups in a non-continuous manner. Figure

3.3 show the top source for creating ideas in a continuous stream while the

bottom source is creating it in groups at given points in time

Time

Continuous idea generation

Event driven idea generation

Source

Source

Group of ideas

Group of ideas

11-2007 12-2007 1-2008 2-2008

Figure 3.3. Continuous Idea Generation vs. Event Driven Idea Generation

Displayed on a Timeline

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3.2.2. Supporting Evidence for Ideation Events

Tucker discussed Bristol-Myers Squibb (BMS) which runs idea campaigns

where it is “sort of a call for idea to all corners” of the business. These campaigns

were publicized and generated 4,000 inquiries from 429 of BMS’s employees all

over the world. BMS holds 20 to 30 of these campaigns per year (Tucker, 2003).

Gamlin, Yourd, & Partick (2007) asserted an event-based approach to

generating ideas, where “focused events” are conducted to capture idea around

a specific problem. They mentioned a properly run event is publicized, and that

Bayer Material Science has held 36 events (as of 2007). One example was

Bayer’s ‘back to school’ event in which 240 ideas were generated, resulting in 14

viable ideas. Koen (2005) also mentioned similar events for web-enabled idea

generation.

Stach, Lonsdale, & La Venka (1992) discussed Pillsbury’s company,

which for decades has held a bake-off event in which customers enter ideas to

win rewards and social notoriety. Interestingly, they described five types of

company situations which encourage the search for ideas. Schepers et al. (1999)

also described idea competitions at Siemens. These examples support the

contention that some companies create ideas in batches as a result of some

event which they hold or conduct.

This research uses the phrase “idea generation event” to properly

describe any event, campaign, contest, or incident, which results in the formal or

informal generation of ideas. For example, Pillsbury’s bake-off is a formal event

lasting over a month which triggers the generation of ideas, while an informal

event may be a competitor releasing higher than expected earnings, spurring

employees to strike back by generating new product ideas.

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Figure 3.4. Idea Generation Triggered by Formal Events

Figure 3.4 illustrates an event resulting in the generation of ideas. Idea

generation events like competitions and campaigns may have a formal deadline

after which ideas will not be received (depicted in Figure 3.4 by the dotted line).

Furthermore, some events may be under the control of the company while others

may not be. This begs the question: “can idea generation events be controlled in

order to aid in the production of quality ideas?”

Tucker (2003) wrote that “if you ask a supplier if they have any ideas or

new technologies they usually provide none, whereas, if you bring a problem or

opportunity to them and ask them to help solve it they are delighted and provide

many ideas” (Tucker, 2003, p. 34). This suggests that the methods used in

conducting the event, and the way it is organized and managed may have a large

impact on the resulting ideas. This can be backed by the participation rates and

quality of ideas created during a college based business plan competition.

Thus, this researcher hypothesized that the following four factor

categories can be used to control the idea resulting from an idea generation

event

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a) Incentives – social, monetary, tangible,

b) Promotion – to which sources and the amount it is promoted

c) Event timing

d) Execution – The way the event is conducted, formatted, and

managed.

Logically, one can deduce that incentives directly affect the outputted

ideas and effectiveness of the overall event. In cases of external idea generation,

incentives may be more important than internal. Some companies like 3M use

social recognition as a major incentive for submitting ideas, while others use

monetary compensation (Alam, 2003; Flynn, Dooley, & O’Sullivan, 2003).

As in advertising, the promotions of the event directly affect the number of

internal or external sources which are aware of it, and way it is promoted affect

the motivation of those sources to partake in those events. Given that

promotional budgets are always limited, a company should choose wisely which

sources it should promote to and the levels of awareness they hope to achieve.

Timing is an important factor - announcing an event during the busiest

time of year may result in very few participants submitting ideas. Conducting an

event during slack time or immediately after conferences may be wise because

employees may be seeded with ideas from the recent conference and have the

time to develop them. Finally, the way the event is executed (i.e., how it is

conducted, formatted, and managed) always will be of great importance in

generating ideas. Making the event not attractive enough or being unclear about

the events purpose could all negatively affect the outcome of the event.

3.2.3. Controlling External and Internal Events

Some events may occur due to outside stimulus like a new competitor entering a

market, a change in economy and so on. These types of events are considered

uncontrollable events. Figure 3.4 below shows the idea generation event

preceding idea generation activities. This figure shows the differences in the

points of control between a controlled events and un-controllable events.

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It is hypothesized that external uncontrollable events impact on idea

generation and can be controlled by: a) the cultural response of the company,

b) the processes response of the company, and by c) the awareness of the

employees to external events.

The cultures of companies like Microsoft are highly sensitive to certain

types of events like new competitors. Thus, executives at Microsoft may

intentionally promote and spread news of a competitor’s new entrance into their

market to elicit a cultural response resulting in the generation of new ideas from

their company.

Figure 3.5. Controlling Both Internally Idea Events an External Idea Events

Similarly, formal processes like competitive intelligence or market

research can automatically trigger a company to respond to an un-controlled

external event by generating ideas. So for example, a company like Corning may

automatically generate ideas for new plastics if the standard price for one of their

top level plastics drops to a commodity price level.

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Uncontrollable events can also occur inside a company. For example,

poor financial returns or missed quarterly earnings may prompt employees in a

company to respond by generating new ideas. Any event, either internal or

external, which stimulates idea generation is valuable.

Figure 3.6. Ideation Events Influence on Idea Generation

Idea generation events can also be formal and informal. Formally

controlled internal events may be uses effectively to fill gaps in the product

portfolio or generate ideas for other needs. But a company responding to

uncontrollable informal events (like a competitor entering the market) by

generating ideas could be very valuable because it is a natural competitive

response by the company.

Event influenced

Idea Generation processes (Early Front End)

Idea Generation processes (Early Front End)

Output Ideas

Output Ideas

Idea Generation processes (Early Front End)

Event driven Idea Creation (also call strategic driven innovation)

Event InfluencedIdea creation

Event-lessIdea creation

We were going to go bankrupt so the company initiated a idea generation event

No major event triggered this idea

Output Ideas

Ideation Event

Source

Source

Source

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It was hypothesized that events can have different levels of impact on the

idea generation process. The figure 3.6 above shows how idea generation: a)

can occur without the influence of any major event, or b) can be influenced

by an event, or b) can be directly triggered by an event.

There is supporting evidence for event-less idea creation and event driven

idea creation (Tucker, 2003; Gamlin, Yourd, & Patrick, 2007; Stasch, Lonsdale, &

LaVenka, 1992; McAdam & McClelland, 2002). However, this research did not

find much support in the literature for event-influenced idea generation. It can

easily be surmised that events can influence idea generation. Take the following

hypothetical instance. A company notices a competitor entering the market with a

slightly better technology, this externals events weight heavily on R&D individual

minds and influences them as the generate ideas for their next line of products.

While by contrast, in an event-driven scenario the company formally requests

new product ideas to help beat the new competition in exchange for monetary

rewards.

It is unclear whether one has more control over external or internal events.

The amount of control for each event very much depends upon the situation. So

for example, an executive may have more control in their own company because

of their position or influence, while in another case, a similar executive may have

more control over external idea competition because he is paying a supplier to

host, advertise, and conduct it.

3.2.4. Controlling the Source

Another way to affect the output of the idea generation process is to control the

source of ideas - people. A review of the literature on creativity showed there are

several factors which can affect the creativity of an individual. Drawing from the

research, This researcher hypothesized that idea generation could be most

greatly affected by controlling the following factors for the source

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1. Selection of the source

a. Individual (their creativity, IQ, experience, knowledge, so on.. )

b. Group compositions

c. Source (see sources listed in chapter 2, section 2.74)

2. Affecting Motivation

a. Intrinsic

b. Incentives

3. Knowledge and Stimuli

4. Environment for creativity

5. others (catch all category)

Steven, Burley, & Divine showed that highly creative people with business

discipline product disproportionately more revenue when placed into

development project (Stevens, Burley, & Divine, 1999). As well, Kelley & Littman

(2005) among other recommended non-homogenous team with very diverse

backgrounds and expertise.

Section 2.7 speaks at length about the different groups of individuals

which can be sources of ideas. Obviously one can use selection of the source

group as a method of control. Yet again, it is ridiculous to think one source of

individuals is always the best. It again depends upon the circumstances and the

type of ideas required, the time frame the ideas are needed in, the money and

resources allocated to generating ideas and so forth. For example one might

choose the core customer group as a source for incremental ideas for the next

product release, while, one might choose to solicit national laboratories and

consultants for radical technology ideas to be release in the next five years.

Motivation is well known to affect task performance, and creativity

research has shown intrinsic motivation and the incentives provided affect the

motivation individuals have for generating ideas (Alam, 2003; Flynn, Dooley, &

O’Sullivan, 2003; Belliveau, Griffin, & Somermeyer, 2002; Gorski, & Heinekamp,

2002; Abdulaziz,1995; Toubia, 2006; Derry, 2004).

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Knowledge was also described as greatly increasing one’s ability to

produce ideas in a given area (Foster, 1996; Kelley, Littman, & Peters, 2001;

Kelley & Littman, 2005; Hardagon & Sutton, 2000). Kelley and Hardagon also

mentioned that providing employees with as much knowledge as possible greatly

increases their abilities to bring disparate concepts to the table and create highly

innovative ideas.

Of course, there are many other factors affecting the ability of the source

to generate ideas like their situation, work-load, communication abilities, access

to tools, and so forth. Leaving an open category of “other” can help researchers

and practitioners to keep in mind that this list is not comprehensive.

3.2.5. Internal vs. External Source and Methods of Control

There is a great difference in the amount of control which can be placed over

internal sources versus and external sources. Internal sources like employees,

management, and sales people can be controlled via the above-mentioned

points of control. On the contrary, one may only be able to control the selection of

external sources and their incentives.

Nonetheless, open innovation research has taught that for every talented

developer inside a company, there are a hundred outside who may be just as

talented. Consequently, innovation practitioners should greatly consider external

source even though there are less points for controlling them.

Figure 3.7 illustrates the difference in points of control for external and

internal sources. It is surmised that the lack of control of external sources may

even reduce the amount of management resources needed to generate ideas. In

some instances, it may be easier and cheaper to control external sources at an

idea generation events, like a bake-off contest, than to internally hire and

manage two full-time food researchers to develop new food ideas. One can make

a similar argument for hiring a consultant, or idea generation company to

generate ideas.

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Figure 3.7. Controls over Sources of Ideas

3.2.6. Controlling Idea Generation Activities

Now that controlling the sources of idea and idea generation events has been

discussed, controlling the idea generation activities can be examined. Section 2.7

contained a fairly detailed examination of idea generation processes. From this

examination, one can hypothesize the following things can be controlled

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1. Selection and combination of idea generation techniques, activities,

& processes

2. Execution of the idea generation techniques, activities, & processes

3. The tools, and resources given to idea generation process

4. Environment (direct environment, company culture, and national

culture)

5. Other.

The underlining assumption of the books, articles, and papers on idea

generation is that it can be fine-tuned and better methods can be selected. It is

beneficial that authors like Anthony Ulwick, Eric von Hippel, and Tom Kelley

advocate their own sort of idea generation processes because it opens up

practitioners’ eyes up to different and better ways to generate ideas.

The diversity of idea generation methods definitely allows new product

practitioners to select from an ever growing array of options. Hopefully, the list of

idea generation techniques, activities, and processes in Section 2.7 allows

practitioners to get a better idea of their options.

It takes skill to execute or perform an idea generation activity or process

correctly. Kelley, Littman, & Peters, (2001) speak about how to properly conduct

a brainstorming session. Kelley et al. (2001) recommends a brainstorming leader

who makes sure ideas are not criticized, ideas are flowing, all members are

giving and receiving input, and the session is constantly bring new ideas into the

mix.

Each of the idea generation activities mentioned in Tables 2.2 to 2.5 can

be conducted properly or improperly, which obviously will affect the quality of the

results. Management and leadership of the idea generation activities is a critical

means of controlling idea generation and should not be ignored. Because

improperly these processes could result in useless and, even worst, harmful

ideas.

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The tools, and resources provided to the idea generation process in some

cases are critical. IDEO idea generation process requires prototyping during the

show and tell and prototyping activities. Not providing the raw materials and

manufacturing tools to create prototype kills this critical link in IDEO’s idea

generation process. Similarly, the outcome based innovation process requires

customer visits. Yet short-cutting these customer visits to save money will cripple

this process and result in a few poor ideas.

Idea generation processes are invaluable, because they usually include

estimates of the resources (time, money, people, and physical items) needed to

perform the processes properly. Unfortunately, idea generation activities are

usually not too specific.

Environments are divided into direct environment, company culture, and

national culture where studies focus on their impact on creativity. The easiest to

control is the direct environment, which is often done by allowing employees to

participate in idea retreats in parks, business hotels, or other settings like exotic

locations.

Company culture is much more difficult to control, as shown by change

management literature. Companies like IDEO, 3M, and Google have taken great

efforts to tune their culture to generate ideas (Kelley & Littman, 2005; Hardagon

& Sutton, 2000; Lashinsky, 2006; Berkun, 2007). This researcher believes one

cannot change their company culture quickly enough to be able to affect short

term idea generation, and hence should consider more long term methods of

controlling idea generation.

Finally, “Other” is a general catch-all category, which may include things

like state of the business, the amount of training provided on the processes,

communication between members, and others. Again the effects which the

people have on quality of the generated ideas are taken into account in the prior

source part of the model.

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3.2.7. Internal and External Idea Generation and Control

A company may have very limited amounts of control over external idea

generation activities. For example, a company might be able to recommend to an

external source a process for coming up with ideas, but ultimately, the company

may have little or no control over the four mentioned point, as depicted in Figure

3.8.

Figure 3.8. Controls over External and Internal Idea Generation

Of course, contracts can be put in place to enforce the use of a given

process, but it is unlikely that outside groups would want to help create ideas

given these restrictions. Sensibly, it was deduced that some control may be

gained by providing resources to the outside groups to aid in their idea

generation activities. For example, some money may be given to a consulting

firm to help subsidize the consultant’s time, or some prototyping materials may

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be given to a college club to help aid them in creating ideas. Once more, one

may also be able to suggest idea generation activities but again they would have

a limited amount of enforceability.

3.2.8. Screening and Filtering Before Being Captured

Section 3.3 will discuss in detail, idea banks, screening, and filtering. But there is

some value in quickly discussing, screening and filtering, because it sometimes

is directly integrated into the process of generating ideas and thus affect the

outcome of the ideas produced.

Section 2.7 showed several idea generation processes, and if one notices

screening and filtering is integrated into several of those processes. For example,

IDEO’s and Blue Ocean strategy’s process generates many ideas but through

the voting process many ideas are filtered out as illustrated by figure 2.26.

Of course, the degree of screening and filtering can be considered to be a

control point which is both separate from, and inside the idea generation

activities as shown in figures 3.9 & 3.10. For instance when hosting an idea

competition; a company can specify the type an attributes of ideas which can be

entered into the competition. Hence, one can consider a screen/filter another

construct which can control and affect the flow of ideas.

Figure 3.9. Screening and Filtering Located After Idea Generation Activities

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Figure 3.10. Screening and Filtering in and After Idea Generation Activities

One can also hypothesize that individuals may perform self-screening of

ideas prior to submitting their ideas to the company. An example can be seen in

IDEO’s idea generation process, when the employees each select their top three

ideas to submit to the group. As Rochford (1991) states: “many people do some

sort of screening themselves and eliminate the idea rather than submitting it for

consideration” (Rochford, 1991, p. 82). Also, companies like IDEO accept all

types of ideas, while others like Arm & Hammer screen out all ideas submitted by

customers. Screening and filtering can also occur inside a company by:

A. Attributes of the idea (category, driver, revenue potential so on)

B. Source of the idea (group which created it)

C. Way the idea was generated (method used, tools used)

D. Condition inside or outside the company

Above is a rough list of hypothesized factors by which ideas may be filtered or

screened. The first is the attributes of the ideas which may include its category,

the idea driver (market driven or technology driven), revenue, difficulty and on

and on. This is the largest category and is typically the way ideas are screened

(Bakker, Boersma, & Oreel, 2006). Second, the source idea can be used in

screening. Typically ideas from the CEO or chairman are not screened out,

whereas, ideas from the mail room boy may be. Third, the way the idea was

generated can be used to screen out the idea. For instance, a new product

development manager may only want ideas which were produced with a detailed

understanding of the customer.

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Finally, conditions inside and outside the company is a large catching all

category which can include anything from the financial status of the company to

economic climate. One may use reason like, “we are just out of money, or too

busy to deal with these ideas now” as excuse to screen out ideas. Again,

screening can be performed by oneself (self-screening ideas) or by the

organizations. Many things may lead to self-screening of ideas like the

receptiveness of the company to previously submitted ideas, credit given to the

inventor, ridicule for previous idea, and so forth. Again, screening and filtering will

be discussed in much more detail in the following sections.

3.2.9. Quick Review on Areas of Control

So too quickly review, four major areas for controlling the full idea generation

process have been identified and are illustrated in figure 3.11 below. The source

is the start of the process, and it was hypothesized that sources inside the

company can be controlled much more than sources outside the company.

Figure 3.11. Points of Control in the Full Idea Generation Process

Next, the events triggering idea generation can be an area of great

control, and were hypothesized to constitute both formal and informal events and

controllable and uncontrollable events. Formal events can be a great method of

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controlling idea generation. Afterwards, idea generation activities can be

controlled via the mentioned means, and is important that a company examine

their methods of generating idea so they can improve them.

Finally, the screening and filtering is an area of control which could greatly

affect the resulting ideas. Thus it should be examined closely because it may

greatly limit the creation and flow of ideas

3.2.10. Strategy and Idea Generation

One may ask: “how does a company’s strategy influence idea generation

activities?” This question was addressed in a limited way in surveys related to

product portfolio management (Adams-Bigelow 2005; Cooper 1999; Cooper,

Edgett, & Kleinschmidt 2006). To quickly review, product portfolio management is

very similar to managing a portfolio of stocks and bonds. In product portfolio

management the goal is to maximize the value of the product launches while

balancing the resource requirements of the commercialization and new product

development processes, and the risk associated with the projects.

In portfolio management, one tries to select and advance new product

projects based on assessment of its potential outcome, and its fit with the rest of

the projects being developed. In doing this, they may utilize many tools and

approaches, which can be categorized into general models: financial models

(net present value & ROI), probability models (decision trees), strategic

approaches (fit with a company strategy), mapping models (bubble maps and

Boston consulting group plots), and scoring models (qualitative scoring, and

check lists scoring), among others. Some of these tools may be more valid than

others, especially for specific industries. For example, Parnell, Lester, &

Menefee’s (1997) study of department stores found that using ROA was a more

preferable measure to ROI.

Cooper (1999) found 26% of the companies he surveyed used business

strategy in their portfolio management processes, and Adams-Bigelow (2005) in

chapter 36 of PDMA found 47% of the respondent have a “strategy and a

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portfolio management processes” (p. 69). This shows there is a large variation in

the level of impact strategy has on the overall innovation process. However these

surveys do not shed much light on how strategy solely impacts idea generation.

Adams-Bigelow (2005) surveyed companies about formally planned idea

generation and whether they were used to fill gaps or generate new ideas. Chart

7.1 below shows the results of this survey.

Figure 3.12. Statistical Results from Adams-Bigelow Showing How Idea Were

Generated

Interestingly, this survey showed 25% of the ideas were created with

prompting or without a strategic need. Still this does not shed much light on the

actual impact strategy had on the idea generation processes.

Flynn et al. (2003) is clearly in favor of strategy driving innovation in his

quote “innovation management involves coordinating a portfolio of development

projects within a clear innovation framework, informed by an overall business

strategy” (Flynn et al, 2003, p.32). Cooper (2006) also says portfolio

management should strongly involve strategy, as well his 1999 article shows

better innovation results when strategy approaches are integrated into portfolio

management processes. As well, Cooper and Kleinschmidt (1996) contend the

project targets must fit the product’s strategy.

33%

18%

11%

3%

13%

22%

Formal fill gaps in product portfolio

Formal because more idea areneededInformal activities to fill gaps

Informal activities because more ideaare neededIdea generation without prompting

Other methods

No strateg

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Rochford (1991) suggests that strategy should determine the process for

finding ideas. Interestingly, Stach, Lonsdale, & LaVenka (1992) define company

situations which spawn a search for new ideas as resulting from a: a) desire to

break into new market b) desired to improve market position c) desire to regain

market leadership, d) desire to remain a viable competitor. These desires can be

taken to be strategic objectives which can trigger and guide idea generation.

Guimares and Langely (1994) state new ideas must be consistent with

the company’s goals. Amabile (1998) suggests that idea generation teams must

share the team’s goals consistent with an appreciation of the organization

strategy. Of course, front end models like Khurana & Rosenthal (1998) directly

integrate strategy into the process. Understandably, all of the above references

argue idea generation should have a strong base in strategy, but there are others

who argue the contrary.

Researchers who propose that idea generation should be open and not

strategy driven include Lawson & Samson (2001) who state “radical ideas can

transfer business strategy or create new businesses” (Lawson & Samson, 2001,

p. 323). As Zien & Buckler (1997) state, “being truly experimental in the front end

means understanding that some new ideas are significant enough to redirect the

strategy of the enterprise” (Zien & Buckler, 1997, p. 32). Moskowitz (1997)

mentions a hap-hazard strategy where, metaphorically, you try a project by

“throwing stuff against the wall and hoping it sticks” (Moskowitz, 1997, p. 12).

Google has a similar strategic approach, where they try many different projects

(most outside the company strategy) in the hopes that some will be adopted by

the market (Lashinsky, 2006). Additionally, ideas created by the Blue Ocean

Strategy process are specifically meant to change the strategic direction of a

company.

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Given these findings this thesis posits three possible ways strategy can

affect idea generation, as illustrated by figure 3.13.

Figure 3.13. Strategy’s Possible Influence on the Idea Generation Processes

The first way strategy is thought to affect the process is by setting direct

objectives for the idea generation activities. This is supported strongly by the

33% of companies found in 2003 by Adam-Begelow (2005) who generated ideas

formally to fill in gaps in their portfolio. An example of this would be a company

setting the objective of generating ideas for new non-toxic paints in order to meet

the new strategic goal of becoming more environmentally friendly. This type of

influence is termed “strategically-driven idea creation” and it is hypothesized

that ideas resulting from this would fit most strongly with the company’s strategy.

The second way strategy is thought to affect idea generation is by

influencing the idea generation process and is termed “strategically-influenced

idea creation”. This can range from a very strong formal influence to a weak

informal influence.

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An example of a weak influence would be a company setting the goal of

entering two new markets in the next two years. The individuals in the company

notice this strategic goal and try to generate ideas for markets outside their core.

Whereas, an example of strong influence would be a company, in a similar

situation, openly rewarding and compensating individuals who generated ideas

which can be used to enter new markets.

Finally, strategy can have no impact on the idea generation processes

among others who state some idea generation is done to open up strategic

options (Zien, & Buckler, 1997; Moskowitz, 1997; Lashinsky, 2006). To some

degree Adams-Bigelow (2005) survey results which show 23% of the idea

generated came with no promoting hints at strategy not being a driver of idea

generation. Hence, the term “Strategy-less idea creation” denote that strategy

had no influence on the idea generation processes.

Figure 3.14. Strategic Idea Continuum

The strategic idea continuum, illustrated above in figure 3.14, was created

solely to discuss how strategy affects the ideas created during idea generation.

Now, the left side of the strategic idea continuum represents ideas which fall in

line with the company’s current strategy. It is hypothesized that strategically-

driven idea creation will on average produce these types of ideas.

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In the middle of the continuum are ideas which create new strategic

options. It is hypothesized that both strategically influenced and strategy-less

idea creation generate these types of ideas. Processes like Blue Ocean strategy

are specifically used to create ideas which open up strategic options for a

company.

Finally, the right side of the continuum shows ideas which are not viable

strategic options for a company. This may be because, these types of ideas may

require too much money, or are way outside the capabilities of the company.

3.2.11. Idea Generation’s Process Check Analysis

Now that a conceptual understanding of how to control the idea generation

process has been developed, one must look at the output of the processes being

the generated ideas, so that the process can be improved via feedback.

Figure 3.15. Control model for Idea Generation

It is hypothesized the feedback is critical in managing the full idea

generation processes. Figure 3.15 above shows the outputted ideas should be

examined so the idea generation process can be checked as meeting its

intended objectives. Additionally, extra feedback about the processes can be

captured by observing the idea generation activities. Active observation of idea

generation activities is used by companies like IDEO to insure activities are being

Managing the idea generation processes

idea

Idea Generation Activities Ideaidea

EventSource

Point of ControlThe source

Points of controlThe Event

Points of controlIdea Generation

Activities

Screen and filter

Points of controlScreening and

Filtering

Process Check AnalysisA. AttributesB. SourceC. Way it was created

Feedback from end of processes

idea

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executed correctly, the right tools are being used, and that the environment is

fruitful. However, to fully understand the feedback process one must first

understand what type of feedback is required to manage the processes.

3.2.12. Characteristics of Created Ideas

Total quality management taught manufacturing professionals to improve the

quality measurements must be made. So, if one wanted to improve the

tolerances of a piston diameter one must measure those features repeatedly.

Idea generation is not anywhereas precise as manufacturing, yet it shares a base

similarity in that the controls in the process very much affect the output.

Simply put, the ideas created by the process should provide the main feedback

required to manage the process. Thus, it is important to understand the

characteristics of the produced ideas. This requires the ideas to be analyzed.

When assessing an idea it was hypothesized that the following items are

of importance as feedback: a) the attributes of the idea, b) the source of the

ideas, and c) how the idea was created. Interestingly, Koen’s et al.’s (2001)

model and Montoya-Weiss & O’Driscoll’s (2006) front end models show idea

selections as being an integrated step, of which a rough analysis of the idea must

be performed. Consequently, this researcher recommends roughly assessing all

of the ideas generated on some base factors. Plus, as a deeper understanding of

idea generation grows so will the practitioner’s ability to control it. The attributes

of an idea will be roughly mentioned here, but will be greatly expanded upon in

the next section on idea banks.

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a) The attributes of the idea

o Driver of the idea (technology, market, customer-driven idea)

o Innovation category under which the idea falls

o Sawhney, Wolcott, & Arroniz’s (2006) cites 12 areas of innovation

o Continuous, discontinuous idea

o Risk & uncertain of the idea

o Financial aspect of the idea (potential revenue, investment

requirement)

o Resource aspects of the idea (management, tools, machinery

needs for the idea)

o Market aspect of the idea (what markets it can be used in)

b) Source of the idea

o Who created the idea

c) Way the idea was generated

o Customer understanding

o Event triggering the idea

o Strategy impact on the idea

o Screen affect on the idea

o Buy in of others

3.2.13. A Practical example of managing the idea generation process

A narrative example will be given, to illustrate how the feedback is vital to the

managing the idea generation processes. In this example, a company is trying to

generate disruptive ideas to fill their product portfolio. They use IDEO’s idea

generation processes described in section 2.7.3.3 and produce a batch of 5

ideas. The attributes of the ideas were roughly measured and are shown below.

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Table 3.1. Example of Idea from the Company’s First Attempt

Driver Innovation

Category

Continuous

Discontinuous

Risk Financial Resources Market

1 Technology Product Discontinuous High High High Current

2 Market Product Discontinuous Low Low Low Not-

served

3 Technology Product Discontinuous High High High Current

4 Technology Product Discontinuous Low High High Current

5 Technology Product Discontinuous High High High Current

Upon reviewing the produced ideas the new product development

manager realizes he can only take on projects which have (1) low risk projects

and (2) have low financial commitments. Further, based on experience, he

knows technology and market driven ideas for products are, on average, rejected

by his company, while customer driven idea, especially those ideas which are

submitted by customers are overwhelmingly accepted by upper management.

He realizes, to his dismay, that none of the ideas generated, will be able to make

it through to commercialization.

So, he decides to tune the idea generation processes based on the

feedback from his first attempt. First he selects a new source being 1) his core

customer and 2) his NPD team. He then selects outcome based innovation and

schedules a 2 week event where his NPD team will work with the core

customers. He also incentivizes his NPD team with monetary and social rewards

for ideas fitting his needs. He manages the idea generation activities and insures

the NPD team is focusing on the customer desired outcomes not their technical

needs. He also instructs the team to screen out ideas which are continuous in

nature. This process results in five new ideas as in table 3.2 shown below.

After reviewing the generated ideas, the new product development

manager is very please but would like to see more ideas which require low

amounts of resources. He also notices that the majority of the new product ideas

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require low amounts of resource while the service ideas require high amounts of

resources. Thus, he instructs the NPD team to concentrate on desired customer

outcomes which should be filled with new products, instead of services.

Table 3.2. Example of Improved Set of Idea Resulting from Second Attempt

Driver Innovation

Category

Continuous

Discontinuous

Risk Financial Resources Market

1 Customer Product Discontinuous High High High Current

2 Customer Product Discontinuous Low Low Low Not-served

3 Customer Product Discontinuous Low Low Low Not-served

4 Customer Service Discontinuous High High High Current

5 Customer Service Discontinuous High High High Current

3.2.14. Summary of Section

In summary, this section started with the intent of defining how the full idea

generation process could be controlled. First, both continuous and event driven

idea generation were reviewed, and idea generation events were examined in

detail. It was hypothesized that company could use ideation events to control the

output of the idea generation processes. The methods of controlling internal and

external events were then described.

Next controlling the idea generation process via the controlling the

sources of idea was described. Methods of controlling internal and external

sources were hypothesizes and proposed. After this, points of controlling the idea

generation processes were hypothesized and proposed. As well, points of

controlling the screening and filtering were hypothesized and proposed. Next,

strategy’s influence on the idea generation process was examined for which, the

strategic idea continuum was introduced to help analyze the influence of strategy

on the idea generation process.

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This was followed by a full model showing how idea generation processes

could be controlled. This model integrated feedback gathered by analyzing the

outputted ideas. It is hypothesized that ideas should be analyzed by a) their

attributes, b) their source, and by c) how they were created. Finally, a case

example of how to manage the idea generation processes was created to

demonstrate the points of control and the importance of feedback. Yet despite

the greater understanding which has been developed, the front end of innovation

requires a better understanding of how idea banks play into the innovation

process and flow of ideas.

3.3. Development of a Control Model for Idea Banks and Idea Management

This section proposes a control model for idea management and idea banks.

Also in the interest of expanding the knowledge in this area, This researcher will

look past the typical functions of capturing, storing, and diffusing ideas to uncover

new ways which idea management can aid the innovation process.

3.3.1. Major Functions of Idea Management

As has been identified in the literature review idea management and idea banks

have several major functions. First, This researcher considers idea banks as a

subset of idea management, in which, idea banks only perform the functions of

storing and distributing the ideas and opportunities. Many idea bank software

programs also perform additional functions of screening, analysis, and so on, but

they are in This researcher’s opinion also performing idea management

functions. For the purposes of this research, idea banks will be strictly limited in

definition to the storage of ideas.

Upon reviewing the literature on idea management the major functions

were identified being the: 1) capture of ideas, 2) storage of ideas, 3) organization

of ideas, and 4) screening of ideas (Flynn, Dooley, & O’Sullivan, 2003; Belliveau,

Griffin, & Somermeyer, 2002; Montoya-Weiss & O’Driscoll, 2006; Gorski,

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&Heinekamp, 2002; Bakker, Boersma, & Oreel, 2006; Heck, 2005; Fritz, 2002;

Dijk, & van de Ende, 2002; Koen et al., 2001). Additionally, idea management

can aid in analysis of ideas (Vandenbosh, Saatcioglu, and Fay, 2006).

Interestingly, much of the literature says that idea banks are a main

means of allowing employees access to ideas. Hardagon & Sutton’s (2000) work

has shown a major part of managing ideas is brokering them around the

organization. These acts of allowing access to ideas, and brokering ideas can

both be viewed under the major activities of “distributing and routing ideas.”

Finally, This researcher has added the major function of tagging to idea

management. Interestingly, some idea management software ask for information

related to, who generated the idea, how it was generated, and record the date

when it was submitted. This software then tags the idea with this identification

information. The value in these tags is that they allow for traceability and to some

degree allow for analysis of the idea generation process so that success can be

replicated or at minimum understood. This thesis suggests tagging as a major

activity of idea management and will take efforts to support this assertion in this

chapter. The list of activities for idea management is seen as the following.

1) Capture

2) Tagging

3) Storing and Categorization

4) Process Check

5) Diffusion and routing

The act of diffusion and routing were place together because it is felt they

are too similar in their nature to be spit into different functions. Routing is the act

of taking and idea which may be relevant to a particular individual and routing it

to them. For example, the operations department may love to have an idea for

reducing cost sent to them from a co-worker in upper management. The following

part of this section will look at each of these five functions in much more detail

and determine major points of control for each.

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Figure 3.16. Initial version of Glassman Model

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3.3.2. Capturing Ideas

Capture is the way which the ideas are literally captured by the company

into the organization’s collective consciousness. So companies which refuse to

listen to ideas from their customers, in a pure sense, are blocking capture from

that source group. Capture of ideas and opportunities can be performed formally

through suggestion boxes, emails, or even advanced idea management

software; or informally, through word-of-mouth, or other general means of

communication. Obviously, This researcher prefers formal means to capture

ideas and opportunities, but there are instances where informal means may be

effective, like in very small organizations.

The goal of the capture function is to extract ideas and opportunities from

the minds of those who possess them and put those ideas and opportunities in a

form which can be retained for the organization (for documentation purposes).

Ideas and opportunities can be captured from internal sources, but open

innovation has also shown great value in capturing ideas and opportunities from

external sources as well (Heck, 2005). Section 2.7.4 again has a detailed list of

sources, both internal and external, where ideas can be obtained from.

Finally, one should not forget that capturing opportunities is just as

important as capturing ideas. As shown in chapter 3 opportunities are the vital

fuel used in the idea generation activities to produce more ideas.

3.3.2.1. Controlling Capture

This research identifies three main ways to control the capture of ideas

and opportunities: 1) selection of the source which the ideas and opportunities

will be captured from, 2) controlling the method of capture, how it is done and

why that method was chosen, and 3) managing the execution of capturing ideas.

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3.3.2.2. Controlling Capture via Selection of Source

The first point of control for capture is the selection of the source where

ideas will be captured from. For example, a company may determine through

hard learned experience that ideas from suppliers are most always infeasible.

Thus, the company can reduce the number of infeasible ideas by blocking the

capture of ideas from the supplier sources. In addition, companies may not be

aware of the great value created by obtaining ideas from dissatisfied customers,

and thus should instruct customer service representatives to capture these ideas.

If anything, open innovation research has shown a tremendous power in

capturing ideas from outside sources, and that selecting and soliciting the correct

source can generate many valuable ideas. Therefore, determining the sources

from which ideas will be captured is one of the first inputs which must be

determined.

There is a benefit and cost to acquiring ideas from any source. However, a

company should not discount any source simply because they produce poor

ideas. As companies gain more knowledge as to how to control idea generation,

they may obtain the means to turn that source into an effective source of ideas.

In other words, you really cannot say a piece of machinery is useless until you

really know how to operate it. Tucker (2003) provided an example whereby

instead of asking for ideas from suppliers, they provide the suppliers with a

problem. They ask suppliers to work on a solution to the problem and their efforts

have generated a number of valuable ideas which were subsequently patented.

3.3.2.3. Controlling via the Method of Capture

Another means of controlling capture is the method in which ideas and

opportunities are captured. Idea capture methods include anything from the

simple oral description given at a meeting, to more formal idea written on paper,

all the way to fully integrated idea management systems. Idea management

software concentrates, in particular, on the method of capturing ideas. In some

odd cases, ideas are captured in their physical or visual forms like in IDEO’s

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Tech box, where they store the actual product or material idea along with a short

description. Again, Section 2.8 reviews the major ways of capturing ideas.

There is a trade off in idea submission between the detail and energy

required to submit ideas. The more energy required to submit an idea, the

greater the barrier to submission. For example, asking an unsophisticated

customer to fill out five pages of forms in order to submit an idea would

effectively block ideas from that source.

Hence, in selecting the method of capture, a company must balance the

energy required against the amount of detail and specificity needed. For

example, a law firm may want a very easy way to capture ideas over the phone

or voicemail whereas, an engineering firm may want a more elaborate way to

insure the capture of vital details.

3.3.2.4. Controlling via the Execution of Capture

Controlling the execution of capture is managing the ongoing process of

capturing ideas, and it is nowhereas simple as putting a box in the corner and

letting it collect ideas. Here are a few examples to prove this point.

If a secretary is assigned to capturing all ideas from employees in the

department after a while he may become complacent, or even worse, he may

dissentingly choose not to capture ideas from a particular employee that he

dislikes. Another example is that lonely suggestion box which people stopped

putting ideas into after they realized that no one was assigned to retrieve and

catalog the ideas.

Setting up the system is one thing, but running it and managing it is

another. Open idea management systems, are much better in the respects that

the submitter can actively see if their idea was captured. Therefore, this is one of

the reasons why employee-driven idea systems (EDIS) have high participation

rates (Gorski and Heinekamp, 2002).

Thus, in setting up capture one must ask, what can go wrong, and what

procedure or management efforts can be put in place to insure this part of the

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process operates correctly. This can get rather complicated when a company is

capturing ideas from several sources simultaneously, but yet it can still be

managed, and is much less complicated than running an assembly line in a plant.

Later in this capture process, this research posits that idea generation and

idea management should have a separate group managing it. In doing so, there

will be active control over vital parts of the process, like capture.

3.3.2.5. Capture Integrated with Screening and Filtering

In many cases, companies combine the acts of capturing ideas with the act of

screening and filtering. This is completely acceptable, and logical, because again

internal screening can reduce the number of poor ideas, whereas, ideas from

outside sources will not be screened in this manner. Capture adds a bit of detail

to screening. The following paragraphs will elaborate on screening with respect

to capture.

3.3.2.6. Capturing Ideas from External Sources

Interestingly, ideas from outside the company, can be a) used directly with little

or no modification, and or b) can be modified to suit the needs of the company,

and or c) can be used to seed people inside the company with stimulus to help

them generate their own ideas. In addition, ideas can be brought into the

company at different points in their concept lifecycle (Figure 2.1).

Some companies become adept at getting ideas from outside sources at

particular stages in the concepts development. For example, Cisco is adept at

obtaining market concept by acquiring small to medium companies for their

technology, and then integrating those technologies into their product and service

offerings. Other examples are large pharmaceutical companies (Pfizer, Merck,

and GSK) which only listen to solicitations from outside drug developers after

those drugs have passed FDA phase 2 trials.

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New product managers should know what level of concept development is

typically accepted and utilized by their company’s (see Figure 2.1). For example

some companies are culturally very skeptical and risk averse and may reject any

ideas which at a minimum has not passed a prototype test, whereas other

companies may have successfully employed ideas from any phase of the

concept life cycle.

Figure 3.17. An Example of a Company’s Receptiveness to Outside Ideas at

Respective Levels of Concept Development

Again there are many reasons why a company may not want to accept

ideas at certain levels of development. Like for instance an idea in the concept

phase may have too much risk or an idea in the pilot stage may be too developed

and will not be backed by the new product development group (again NIH

syndrome). Nonetheless, part of the strategy for receiving ideas from outside

sources should include the idea’s level of concept development.

Furthermore, ideas can be placed in different categories and a company

may have a different level of responsiveness to each category of ideas. Figure

3.18 shows an example of a company which is not responsive to brand or

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process ideas. Now for the sake of brevity, the remainder of this chapter will be

limited to sources of ideas for new offerings (being products and services) shown

as the first circle on Figure 3.18.

Figure 3.18. An Example of a Company’s Receptiveness to Outside Ideas in

Different Innovation Categories

3.3.3. Tagging

As shown in figure 3.16, tagging follows capture, and is the act of attaching

additional information to the idea, so that it can be used to a) refine the idea

generation and idea management process, as well as b) aid the later innovation

process by formalizing company biases.

Tagging an idea can be thought of as a product information tag on a food

product, which shows the origin of the food, manufacturer, content, shelf-life, and

so on. Tagging in manufacturing is a vital task because it allows for tracking, and

most importantly, accountability. If a bad batch of food goes out the door, the

quality examiner who authorized the batch can be identified via the tag and

therefore held accountable.

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In idea generation, tagging can be used in a positive light to improve upon

good or successful practices. Knowing how good and great ideas were created

allows the company to identify best practices, and gives them the opportunity to

reproduce the conditions that created those great ideas. Similarly, it is valuable to

know what activities, people, and process produced particular type of ideas, like

incremental, or disruptive, market-driven, or customer-driven.

For example, knowing that one product development manager was

associated with the creation of the company’s most valuable ideas, or knowing

that the most useful disruptive ideas came out of outcome-based-innovation is a

valuable insight. These insights can be used to refine the idea generation

process. Product development managers can be used to train others, and

outcome-based innovation can be applied to create ideas for other parts of the

business. The following paragraphs will explain how tagging is valuable to the

later innovation processes by dealing with unknown company biases.

3.3.3.1. Innovation Drivers

It seems companies can have cultural and process based bias toward certain

types of ideas. For instance, Nortel was only structured to develop ideas from

customers, while Volvo was clearly shown to have a bias toward technology

ideas (Montoya-Weiss & O’Driscoll, 2006; Backman, Borjesson, & Setterberg,

2007). Backman, Borjesson, and Setterberg (2007) write in some detail about

how companies can have natural biases toward ideas with different drivers. They

categorize ideas as being technology-driven, customer-driven, market-driven,

and value-driven (Backman, Borjesson, & Setterberg, 2007; Conway, &

McGuinnes 1986; Montoya-Weiss & O’Driscoll, 2006).

Research of Fortune 1000 companies by Jaruzelski, & Dehoff (2008)

presents a more thorough examination of these drivers. According to their

findings, these drivers result in similar innovation strategy, including: (1) need

seekers, (2) market readers, and (3) technology drivers.

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Need seekers actively seek customer needs, and use idea generation

activities which focus on gathering customer needs and ideating to meet those

needs. The innovation pipeline of need seekers are rigorously managed to track

return on innovation investment (Jaruzelski, & Dehoff 2008).

Market readers focused a cautious approach of reading market trends via

market research and competitive intelligence. “Market readers spend less on

R&D as a percentage of sales and tended to prefer incremental developments;

as a result, they were apt at bringing fast follower products to market. Market

readers were also mentioned to have pipelines which verified the products value

to customers” (Jaruzelski, & Dehoff 2008, p. 119).

Technology driven companies preferred to push the boundaries of

technology to met unarticulated customer needs, rather than innovation based on

customer needs or market trends. They used extensive technology mapping to

scout for new technology and understand where they should place their design

efforts.

In a sense, these drivers and bias may link to some unmentioned cultural

values. This researcher hypothesis that technology driven companies believe

they must lead in technology to be successful in innovation and that the risk of

failure is a direct result of this choice. On the other hand, market readers or

market-driven companies believe that careful understanding and following of

market trends can result in a lower risk approach to innovation and a better

return on R&D dollars.

Finally, need seekers or customer-driven companies believe that

customers are at the heart of the company’s revenues and that future success

required much attention be place on customer needs to be successful in

innovation. Interestingly, this research supports the assertion by Jaruzelski, &

Dehoff (2008) that no single strategy is best, and that a company should select

approaches which mesh with the company’s strategy, competitive environment,

and cultural values.

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This research revealed an additional category of solution-driven

companies is missing from the literature. Consultants often increase their offering

based on visible need for a solution in the market place. Thus, these consulting

firms spend money developing solution or solution packages which can solve a

particular set of problem. One known example is IBM, which shifted towards a

solutions-based company in 2002, and utilized their brand name and expertise to

offer consulting and implementation solutions to the general market. It is

hypothesized that solution-driven companies look for current or impending

problem areas in a particular market, or with technology (much like need

seekers) and are driven to offer solutions.

3.3.3.2. Idea Category bias

Similarly, companies can have biases toward particular idea categories like

products over services as shown by Sawhney, Wolcott, and Arroniz (2006)

innovation categories. Finally, Christensen (2003) showed how companies

structurally and culturally are un-able to develop disruptive and radical ideas

(Christensen, 2003; McDermott, & O’connor, 1999; Verworn & Herstatt, 2001;

Backman, Borjesson, & Setterberg, 2007; Bean, & Radford, 2002).

To remedy these natural biases, companies initially have to become

aware they have a natural bias. This can be first achieved through education by

books like Christensen’s (2003) The Innovator’s Dilemma and second be

achieved through making the innovation process more transparent. Again, the

proposed solution of tagging was hypothesized to help make the innovation

process more transparent. One proposed way to deal with the bias toward

certain types of ideas in the innovation process is by tagging an idea with

information. By initially tagging ideas one can track the progress of particular

ideas through the innovation processes and visibly see the bias of a company.

For example, you can compare how many ideas are tagged as being customer-

driven in the idea bank, then compare how many were selected for development

in the FFE, and NPD processes.

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50 of 150 (1/3) are customer-driven in the idea bank

10 of 50 (1/5) projects are developed in the FFE

1 of 20 (1/10) were developed in the NPD

1 of 12 (1/12) made it to market launch

The list above shows an example of a company’s innovation process and

the number of customer-driven ideas being pushed through to market launch. By

quickly reviewing the tags associated with projects in the portfolio an innovation

practitioner can quickly generate these numbers. One quickly sees that the

number of customer-driven ideas drops in the NPD, which might indicate a bias

of the NPD process against customer-driven ideas.

3.3.3.3. Controlling tagging

Tagging can be controlled rather easily by the input conditions: (1) the method of

tagging, (2) the attributes of the tag and (3) by the way tagging is executed.

3.3.3.4. Controlling via method of tagging

The method of capture also dictates the method in which the idea can be tagged.

So for example, if ideas are captured orally over the phone and then memorized,

one must also ask the submitter how the idea was created, what event triggered

its creation, and so on. If the idea is submitted in to a suggestion box the act of

tagging becomes much more difficult. However, if a standardized forum is used

along with a suggestion box, the required tag info can be integrated into the

forum.

Idea management software allows the greatest flexibility in terms of

tagging because they can ask follow up questions and then formally store that

information with the idea, and be recalled very quickly. Whatever form the tag

takes - written, computer based, or oral - it is just important that the information

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capture in the tag stays with the idea so it can be traced. So if the idea is

accepted as a project and then passes on into the development, management

should be able to quickly pull up the idea tag info associated with the project to

see what conditions lead to the ideas creations. Again, the innovation process is

a value chain, and tracking items as they proceed through the process is just vital

to improving the links in that chain.

3.3.3.5. Controlling via Attributes of the Tag

Again, the amount of detail captured for the tag must be balance against the

energy in obtaining it. Not every piece of information is vital, only a few are. Thus,

asking a submitter what time and day he had the idea is much less relevant than

what event triggered him to create the idea. Thus, this research concludes there

are a few required items which should be captured along with an idea. These

items are listed on the following page, and are broken up into process related

tags and idea related tags.

Collecting information related to the idea like financial potential, feasibility,

and so on is not required by the tag, because the tagging function is more

concerned with tracing the idea creation back through the process. Additionally,

capturing information like financial potential, required resources and so on at the

time of submission is a bit premature because, (1) you cannot estimate them

without having done a fair bit of analysis, and (2) because you want to take time

and develop the idea further to increase the financial potential and or lower the

required resources.

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Source Tag Info

• Who or what group of people generated the idea?

• What motivated the source to generate this ideas?

Event Tag Info

• What event triggered them to create the idea? (formal or informal)

• Was the event a formal event held by the company or dictated by

management?

• What incentive motivated them to generate the idea?

• When did the event occur?

Activities Tag Info

• What activities did they formally do to come up with the idea?

• What activates did they informally do to come up with the idea?

• What was the order of the activities?

• What tools or resources did they use during idea generation?

• Where or how was the environment for idea generation?

• Who managed the idea generation activities?

Screen and Filter Tag Info

• What screens did the idea pass through?

• Who told you not to submit the idea?

• Who managed the screening?

Capture Tag Info

• Who was the idea submitted to?

• How was the idea submitted?

• Who encouraged them to submit the idea?

• Was it hard to submit the idea?

Tags Related to the Idea

• Is this idea (technology, customer, market, value) driven?

• What category is this idea (product, service, process, marketing, ..)?

• Is this a disruptive or incremental idea?

• Is anyone committed to this idea? If so who?

• Who else is aware of this idea?

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3.3.3.6. Controlling via the Execution of Tagging

Tagging is highly linked to capture, because tag information is taken at the time

of capture. Hence managing the capture function can also include managing

tagging. Again, the execution of tagging is important. For example, if a secretary

captures an idea and fails to write down the associated tag information because

they were short on time, the benefits of tagging are forfeit. Hence, managers

much ensure that employees and others submitting ideas are capturing and

tagging ideas appropriately.

Interestingly, properly selecting the method of capture can reduce the

need to manage tagging. For example, idea management softwares can require

the user to fill out related tag information prior to submitting the idea, whereas,

the good old paper submission system can not. Yet, idea management softwares

cannot probe a submitter like a trained manager who can extract accurate tag

information. Hence, extra attention should be paid to the selection of the capture

method because it may greatly reduce the need to actively manage tagging.

3.3.4. Storage and Categorizing

The first part of this section presents a review of how the ideas and opportunities

are stored and how they can be categorized. This is followed by the second part

showing how to control storage and categorization.

3.3.4.1. Formal vs. Informal Storage of Ideas and the Concepts of the Idea Cloud

The following paragraphs will review several obvious attributes which This

researcher deems useful for the innovation process. The first is the form in which

the idea is recorded, being highly formal or informal.

Many ideas exist solely in the minds’ of the employees and have not been

recorded to paper. So to account for these ideas which exist in the larger

organizational consciousness the term “idea cloud” is being used. To help in the

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differentiation, the term “idea bank” is being used strictly as ideas recorded

formally on a fixed media (paper, computer disk, audio tape).

Figure 3.19. Illustration of the Idea Cloud, Idea Bank,

and Company Idea Bank

Figure 3.19 illustrates the idea cloud with two idea banks embedded in it.

Hence, an idea in a person’s mind would be contained in the idea cloud,

whereas, if it was written on paper (say in a lab notebook) it would exist in the

idea bank, and if it was submitted it would then exist in the company’s idea bank.

The value gained from splitting up storage this way is it highlights that

many ideas are kept in peoples minds’ and there are barriers which those ideas

must move across to become more formalized.

So given this, one can view ideas in the organization on a continuum of

formality as shown by Figure 3.20 below. Figure 3.18 shows informal ideas which

may exist in only a person’s mind whereas highly formal ideas may exist on

paper and computer, with fully detailed written descriptions with prototype

pictures and so on.

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Figure 3.20. Illustration of the Continuum of Idea Formality

Interestingly, some companies like IDEO store some of their ideas in a

Tech box which just keeps a physical sample of the idea with a short written

description (Hardagon & Sutton, 2000; Kelley & Littman, 2005). While other

companies may require ideas to be recorded in highly formalized forms (like

several written descriptions, with detailed summaries of the idea, technical

feasibility, required resources and so). An example of idea banks requiring highly

formalized idea submission may be Nortel’s “Galileo” idea management system

described by Montoya-Weiss & O’Driscoll (2006).

Evidently, having ideas in a more formal fashion helps later FFE activities,

but one must keep in mind that requirements for formality may stop individuals

from submitting their ideas. Thus, one must carefully balance the formality

requirements for the idea bank against the need to collect more ideas.

3.3.4.2. Categorization of the Idea Bank

Unfortunately, none of the literature on idea banks or idea management

highlights the diversity of ideas which exists in a formal idea bank. To quickly

illustrate how convoluted an idea bank can become, Figure 3.16 was created.

Figure 3.14 shows a huge diversity of ideas from new to old; analyzed or

unanalyzed; technology or customer driven; product or supply chain; and so on.

Of course, Figure 3.14 does not show the overlap among categories, so an idea

can be new, customer driven, and radical while another can be old, customer

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driven, and incremental. With this dizzying array of categorizations, it may seem

daunting to organize an idea bank. Yet these categorizations give one an

increased ability to search through and select ideas, and use their understanding

of the ideas in the idea bank to improve the innovation process.

For example, if one purely categorized the ideas in an idea bank by

incremental or radical ideas one might see what is illustrated in Figure 3.17.

Instantly, one can deduce that the company is not effectively capturing or

generating radical ideas and should place more effort on these tasks. Similarly,

by organizing ideas by their innovation category (as illustrated in Figure 3.18)

one would see the need for more service ideas.

Figure 3.21. Illustration of the Diversity of Idea Banks

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Figure 3.22. Illustration of Idea Bank Organized by Incremental and Radical Ideas

Figure 3.23. Illustration of Idea Bank Organized by Innovation Category

Of course, one can organize the ideas in an idea bank by almost any

factors like ideas with the shortest time to market, or lowest amount of required

resources. However, one must be careful not to use factors which in themselves

are useless, irrelevant, or can not be accurately determined. For example, one

should not sort new unanalyzed ideas in an idea bank according to those which

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are most appealing to customers or by total possible revenues, because those

factors will not be determined with a reasonable level of certainty until after they

are analyzed in later FFE activities.

Hence, one can see that ideas may have obvious attributes (like new or

old, or product or service) which can be easily determined even for new un-

analyzed ideas, and conversely, un-obvious attributes (like possible revenues,

required resources, competitive advantage, and so on) which require analysis

and work to uncover.

3.3.4.3. Examined vs. Un-Examined Ideas

It may not be directly obvious, but a quick review with the NPD or FFE team will

uncover which ideas have been formally examined verses which have not been

examined. Knowing this allows one to better organize their efforts in the late FFE

processes. For example, the FFE team may decide to spend three months

evaluating un-examined ideas in the idea bank to see if any great ideas can be

uncovered. Plus, keeping records of the number of examined versus

unexamined ideas in the idea bank will show if the FFE teams are effectively

examining ideas, or if there are too many ideas in the bank.

3.3.4.4. Temporary vs. Permanently Stored Ideas

IDEO’s idea generation process has shown that ideas can be created and stored

temporarily (Kelley, Littman, & Peters, 2001). Again, in IDEO’s process, ideas are

presented to the group, often in a very informal written form, and then used as

bases for the next evolution of the concepts. Ideas which do not make the final

cut are then trashed. The output of the IDEO process again is one or two well

developed ideas.

In companies like IDEO, which have so many diverse client projects, it

really does not make sense to permanently record ideas because, (1) the

chances of getting a similar client project are remote; and (2) the chances of

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using those ideas again are very remote. Thus, the benefit for permanently

recording ideas into the bank does not justify the required energy and time.

However, in other companies there is a much greater benefit to permanently

storing ideas. Hence companies should take note, that there can be cases where

either temporarily storing ideas or permanently storing ideas may be beneficial.

3.3.4.5. Awareness Continuum

Some ideas are known to many inside a company while others may be unknown.

For example, practically every employee in Apple’s competitors being Sony,

Nokia, and Motorola are aware of Apple’s touch screen Iphone; while many less

employees are aware of new ideas like new OLED displays for cell phones.

Obviously, some ideas may have higher levels of awareness than others.

Ideas which have higher levels of awareness may be more easily backed

by their organization and pushed through the new product development and

commercialization process. Having many more people, especially decision

makers like key executives, being aware of an idea may be very helpful in getting

a project noticed and funded. Hence companies should also consider the levels

of awareness associated with an idea (Conley, 2002; Flynn, Dooley, &

O’Sullivan, 2003).

3.3.4.6. Ideas and their Level of Development

Differentiating ideas by their level of development may also prove to be a useful

factor. Ideas which are undeveloped, in development, or developed have

radically different amounts of information associated with them, and may have

firm support which can help spread useful ideas across the organization. For

example, having a team which is currently developing a new process talk and

spread their process may provide the useful energy needed to jumpstart the

implementation of those ideas (like process improvements) in other areas of the

business.

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3.3.4.7. Commitment to Ideas

Ideas which have a high level of commitment behind them are greatly different

than similar ideas with low levels of commitment. For example, an ideas which

has the backing and commitment of the executives and upper management

stands a far greater chance of passing through the NPD process than those

ideas which do not have this support. Also, the employee-driven idea system

mentioned by Gorski, & Heinekamp, (2002) where employees became

committed to their ideas, showed to have substantially better rates of

implementation than those of ideas placed into suggestion box systems.

Thus, the FFE team should strongly consider the level of commitment and who is

committed to an idea when selecting ideas for development (Montoya-Weiss &

O’Driscoll, 2006).

3.3.4.8. Newness of the Ideas

Some companies are biased toward new ideas, but old ideas are also useful and

still hold great value (Vandenbosch, Saatcioglu, & Fay, 2006). Again a new idea

was defined as one which is new to the company as a whole. For example, in

organizing the idea banks by newness of ideas, one may uncover there is a lack

of old ideas being proposed and being analyzed. Or conversely, one may find out

that idea generation activities are producing old similar ideas and not enough

new ideas. Hence, having a map of the newness of ideas in the idea bank can

show front end practitioners where extra work is needed.

3.3.4.9. Controlling Storage and Categorization

There are two hypothesized ways to control storage and categorization: (1) the

method of storage and categorization, and 2) being the execution of storage and

categorization. There are several ways to store ideas as mentioned above, some

are formal and some are informal. Regardless of the method chosen or what is

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stored one must look at the main functions of the idea storage, which is a) to

store idea and opportunities, and b) to retrieve ideas and opportunities.

Viewing it in that light, one can see it is important to quickly store and

retrieve idea and opportunities. But this must be balanced against the need for

formality, and how much detail should be captured. So again, if the idea is for

and mechanical device much more info may be required than and idea for a new

customer group.

Interestingly, the quickest way to retrieve stored idea is through idea

management software programs; whereas, some of the quicker ways to store

idea can be via paper documentation methods. The benefits of idea management

software are that ideas can be easily appended to, and modified, as they

processed through development.

Categorization does take some energy especially if ideas are stored in a

paper form. Again, idea management software have major benefits because

categorizations can be quickly drawn up, edited, compared, and reviewed, on

many systems at once. When selecting the method of categorization one should

keep at minimum a few consistent categories so the results of the idea stored in

the bank can be compared overtime.

Again, the selection of the proper categories depends upon the business

but in general the categories which should be used are: level of development,

newness of the ideas, innovation category, disruptive versus incremental, and

idea driver.

3.3.4.10. Control the Execution of Storage and Categorization

Yet again, the system being used makes a huge difference in the amount of

management effort spent on storage and categorization. Computer software

systems can quickly store and retrieve ideas, but must be managed for uptime.

Conversely, paper systems may require a secretary to fetch the documents, and

management may have to take time to train and monitor the performance for

these tasks.

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Similarly, computer systems can perform categorization according to their

programming, and may provide resulting maps of ideas by category in the idea

bank very quickly. However, categorization in paper based system may be much

more tedious, and require much management to insure ideas are correctly

categorized. The amount of management required for any idea storage and

categorization system should be known at the time of implementation or

purchase.

3.3.5. Process Check and Feedback

As mentioned in the section on controlling idea generation, feedback on the

generated ideas is critical to improving the idea generation process, and idea

capture. Hence, the process check is a quick analysis to see if a) the ideas being

created by the ideas generation process are meeting their preset goals or b)

the ideas being captured from external sources are meeting the preset goals

set for capture of external sources.

For example, if the chief innovation officer (CIO) sets an objective of

generating twenty plus disruptive ideas and capturing twenty plus disruptive

ideas from outside sources. The company then goes off and generates ideas and

captures ideas from outside sources. The feedback from these activities shows

the company has created four disruptive ideas and captured twenty plus

disruptive ideas from outside source. The CIO then knows they need to rework

their current internal idea generation process.

As shown in the Section 3.2 “control model for idea generation”, the

process check “feedback” was placed at the end of that process. However,

because in this model, idea generation and idea management are combined, it

makes perfect sense to combine the process check into idea management

section. Hence, the process check function was placed after the storage and

categorizing not before it because, (1) the ideas are in a more permanent form

for a process check; and (2) one does not have to worry about the process check

blocking the storing of ideas.

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Controlling the process check to some degree depends on the systems

being used. Software idea management systems allow quicker access to ideas,

and analysis results can be tagged to a group of ideas which were created

through a particular set of idea generation activities. Hence, it make be quicker

and easier to use and idea management software for large groups of ideas.

Paper based process checks are still imagined to be effective, as long as the

individuals managing idea generation understand how their strategies are

affecting the outputted ideas.

3.3.5.1. Controlling the Process Check via the Selection of People

The people performing the analyses were shown to be a major factor in the

quality of the analysis performed. Steven, Burley, & Divine (1999) uncovered that

certain personality types enjoyed analyzing and distributing new ideas while

others quickly tired of this task. Their insight was that certain people are really

pre-disposed to this task and they would resemble a person like a technologists

who loves looking at new technologies, analyzing them, and talking about them,

or the business analysis guy who loves looking at and talking about new

business ideas. Hence, one should look for these personality types when

selecting individuals for the process check task.

3.3.5.2. Controlling the Execution of the Process Check

Like any process, the process check analysis must be monitored and feedback

must be given to the appropriate parties. Accountability can be created by

allowing the individuals who manage the idea generation process to hold those

individuals performing analysis and providing feedback accountable for their

reports and their quality.

Again, the process check analysis is not supposed to be detailed, it is a

quick overview to see if the ideas being generated by the idea generation

process are meeting their pre-set targets. Hence, if the initial goal is to create five

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disruptive product ideas, and it actually produces five incremental service ideas

the individuals managing idea generation can be informed quickly over the

phone, a detail report is not needed. One should not over complicate the

analysis, just get the rough info to the idea generation manager quickly, so they

can learn and refine their processes.

3.3.6. Diffusing and Routing

Diffusion is the act of spreading the ideas and opportunities through the

organization, and routing is sending a particular idea or opportunity to the most

relevant individuals. Diffusion was highlighted in the innovation value chain

model; however, diffusion in is this model is slightly difference. Diffusion here is

the act of taking anything from a rough idea to a developed concept and

spreading it around the organization so that a) future development projects can

be created from it or b) current or future development projects can be aided by it.

Again, to reiterate, ideas can be a) used directly with little or no

modification, and or b) can be modified to suit the needs of the company, and or

c) can be used to seed people inside the company with stimulus (see Figure

3.24).

Figure 3.24. Idea Management Feeding Idea Back into Idea Generation to Stimulate more ideas

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With this view, diffusing ideas does not only have to be about getting an

idea accepted as a project as mentioned by Hardagon, & Sutton (2000). As well,

there is value to having non-perfect ideas in the idea banks. To illustrate, that

ideas can be used to seed individuals in idea generation activities, this model

had a link linking diffusion to idea generation. However, before going into detail

about how to control diffusion, we discuss theories of diffusion. This research

views two distinct types of diffusion one being a) forced diffusion, where an

individual or group (internal or external) is pushing the idea through the

organization, and b) sought diffusion, where individual activity seeks new ideas.

The best example of forced diffusion is the executive product champion,

who uses every means possible to spread his idea through the organization. This

individual uses memos, speeches, conferences, meetings, emails, and face-to-

face communication to get his idea out to individuals in his organization. There

are other means of forced diffusion, like companywide memos, idea fairs, idea

discussions, promo video of idea, posters of new ideas, and so on. The many

ways they differ from each other is the amount of power they have to diffuse and

idea. Hence, to demonstrate this better the researcher has created a diffusion

power spectrum, Figure 3.25.

Figure 3.25. Diffusion Power Spectrum

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Note that ideas can be diffused by internal or external sources, so a large

competitor launching a new product has a lot of power to diffuse that idea to

other companies. Sought diffusion is different than forced diffusion because, here

an individual is seeking out the idea, not having it forced on them. This can entail

anything from and individual requesting ideas of others, scanning periodicals or

media, or searching databases or the internet for ideas or opportunities. Sought

diffusion is a different mindset than forced diffusion because of its structure.

Sought diffusion is allowing access to tools and resource which would

enable an individual to seek and find ideas relevant to their needs. The fields of

knowledge management and Informatics have shed much light on the way to

enable individuals to seek and find information. For example, GE and Mckinsey

both have elaborate knowledge management systems which would allow

individuals to access an expert, find relevant knowledge, or get solutions to

particular problems.

Hence, a company can create systems, tools, and resources which would

allow individuals to more quickly find ideas. It is hypothesized that company

culture has some effect on sought diffusion. This is because it requires a different

mindset, “I will find an idea”, instead of, “I will wait till an idea comes to me.”

Regardless of culture, structures and systems can be put in place to enable

sought diffusion.

For example, expert directories allow employees to search out relevant

experts and ask for new ideas which are relevant to their needs. Also, idea

management software enable employees to search the idea banks for ideas

relevant to their needs. IDEO’s Tech box, allow employees to physically search

for materials and products which could seed their idea generation activities. Idea

conferences allow individuals to talk about ideas and opportunities.

Unfortunately, no data exists on which types of diffusion are taking place

in companies or if sought or forced diffusion is more prevalent. Nonetheless, the

best strategy is to enable both forced and sought diffusion to occur.

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3.3.6.1. Controlling via Methods of Diffusion

There is great value in forcing the diffusion of select ideas in the organization,

and enabling systems and tools so sought diffusion can occur. To aid

practitioners in selecting methods which could be applied to their company, this

research offers a rough table of possible methods of diffusion.

Table 3.3. Diffusion Methods, Forced, and Sought Diffusion

3.3.6.2. Controlling Diffusion and Routing via Selection of People

Networking theory has shown that some people inherently like to distribute

information (Facilitators). In addition, some people like to distribute ideas. The

point can be quickly made, if one imagines the archetype technologist talking

relentlessly about the newest inventions, technologies, and product ideas.

Diffusion method ReferanceInternal Force Diffusion

Executive product championproduct champion Idea fairs & conference (3M) Hardagon & Sutton (2000) & (1997) Weekly new idea sessionIdea promo video Hardagon & Sutton (2000) & (1997) Idea posters Internal Idea blog Idea newslettersIdea booklets, cataloguesIdea memos, emails, calls, mailIdea retreats

Passive Forced diffusion methodsWork space design Kelley & Littman, (2005)Community areas (free coffee bars) Kelley & Littman, (2005)After work get together Kelley & Littman, (2005)Online idea forums or news groups Kelley & Littman, (2005)

Internal sought diffusionExpert networksIdea management softwareIdea databanksRecommended list of databasesRecommended list of search resourcesIdea booklets, catalogues

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Kelley, & Littman (2005) explained in detail that some individuals like

discussing new ideas and things they learned. They termed these people,

“Cross-Pollinators” and dedicated an entire chapter to them. They also assert

that not everyone likes this role.

Hence, it is easy to see that some people are much more inclined to be

good at distributing ideas and opportunities around the organization. Formally

assigning this task and providing them with the power to execute it can greatly

increase the degree to which ideas are distributed through the organization.

Allowing these individuals to select and conducted via any of the diffusion

methods from above will also help diffuse ideas across the organization.

A sign of an individual great at diffusion is that they can name off relevant

products, technologies, inventions, ideas, and show you were to go to learn more

about them, and they enjoy talking about this to others.

3.3.6.3. Controlling the Execution of Diffusion

Again, one must differentiate among forced and sought diffusion. Not everyone

needs to know about every idea in the idea bank; they only need to know about

the ones which are relevant to them at that particular time. As Hardagon & Sutton

(2000) showed their “idea brokers” distributed ideas in a just-in-time means to

solve problems relevant to the individuals they were helping.

However, Kelley, & Littman (2005) stressed that “Cross-Pollinators”

should spread ideas regardless of whether or not there was a need. Hence, one

can measure the effectiveness of forced diffusion by looking at the effectives of

a) getting idea solutions to people who have problems, b) spreading new or

useful ideas around the organization to the relevant individuals.

Opinions and metrics can be used to manage diffusion. If the development

team members feel they are not getting exposed to enough new ideas, then

possibly forced diffusion maybe failing to work. In addiction, measuring the

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number of events where new ideas are forced out and the number of people they

are distributed too can also give an indication of the effectiveness of forced

diffusion.

For sought diffusion, opinions and metrics can also be used. If employees’

feel they do not have access to easy methods of finding new ideas, then possibly

sought diffusion maybe failing-to-work. Also, if metrics on items like searches in

the idea banks, or use of expert networks are low, then sought diffusion may not

be used effectively.

3.3.7. Routing

Routing ideas is also an affective way to deal with this bias. Christensen

and Raynor (2003) proposed that disruptive ideas should be developed in

separate organizations. Similarly, Lockheed Martin is famous for their use of

skunk works to develop radical airplane concepts. By using idea management to

route disruptive idea to proper development groups like skunk works, internal

incubators, or spin-of-companies the company’s internal bias toward disruptive

ideas can be avoided. Similarly, by having market-driven ideas routed to the

marketing department for development can again overcome another company

bias.

The concept of routing ideas to the appropriate parties based on tagged

information is especially powerful for ideas of different innovation categories. For

example, a customer experience idea possibly should be routed to the customer

service department; whereas, a branding idea should be routed to the marketing

department.

Having a routing system also allows each particular department to have

their own idea bank, which can be linked to a company-wide idea bank. It is

imagine this could be rather easy, for example an employee may notice a

competitor using a new branding technique. That employee would then write-up

the idea, tags it, and then it is automatically routed to the marketing department

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by the idea management team. Additionally, tagging and routing also allows for

accountability in the front end of innovation because of the increase visibility

associated with the process.

3.3.7.1. Controlling via the Method and Execution of Routing

There are several methods of routing ideas, and they resemble the methods of

routing information. First, ideas and information can be routed to a particular

individual, group, or department. Second, ideas can be routed via email, memo,

document, meeting, or any other method of conveying information.

Additionally, Hardagon & Sutton (1999) suggest that “idea-brokers” route

ideas to the relevant individuals. Hence, the act of routing could be a formal task

assigned to a group of individuals. Interestingly, idea management software

could also be programmed to automatically route ideas to particular individuals in

a company. However, there is a benefit to having a personal idea-broker who

knows your needs and present the most relevant ideas at appropriate times.

As mentioned for diffusion, opinions and metrics can be used to manage

the execution of routing.

3.4. Linking Idea Banks to Portfolio Management

Similarly, idea banks and idea management can be linked to early portfolio

management. Typically companies determine their current portfolio of projects by

assessing the projects in the NPD process and commercialization process. Also

they determine their options for projects, by assessing the projects in the FFE

ready to move into the NPD process as shown by Figure 3.26.

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Figure 3.26. How Portfolio Management Determines Options for New Projects

Interestingly, by assessing the ideas in the idea bank product portfolio

managers can get an earlier understanding of options for their portfolio (Figure

3.27). As well, by analyzing the ideas in the idea bank, portfolio managers can

get a better understanding of the weakness in their company’s innovation

processes. Finally, portfolio managers can also selectively force fuzzy front end

processes to develop ideas particular for gaps in their portfolio.

Figure 3.27. How Assessment of Idea Banks can be Used by Portfolio Managers

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Figure 3.28. Late FFE Activities Linking to Screening and Filtering

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CHAPTER 4. RESEARCH METHODOLOGY

4.1. Purpose of Study

The purpose of this study is to answer the research questions as follows. First,

can the proposed control model aid in a conceptual understanding of idea

generation and idea management and, second can this control model be

supported as capturing the required factors needed to manage and control idea

generation and idea management?

4.2. Limitations Effecting the Selection of the Type of Study

Prior to discussing the study the factors limiting the study must be elaborated on.

This will greatly help in the selection of the appropriate study type and

methodology.

4.2.1. Lack of Metrics for Success in Idea Generation

Unfortunately, the lack of understanding of successful outcomes for idea

generation and idea management limits the number studies that can be perform

to support the research questions. The recent article by Hüsig & Kohn (2003),

had to go to great efforts to develop a set of criteria which they could measure

the success of front end activities. Unfortunately, neither idea generation nor idea

management has any metrics defining successful outcomes. As mentioned in the

previous chapter the output of the idea generation process can be generally

measured in: 1) the quality of ideas, 2) the quantity of ideas, and 3) the attributes

of ideas.

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Unfortunately, one company’s definition of successful idea generation can

vary greatly from another’s, and often vary based on that company’s needs and

situation. This researcher’s primary research has show that Siemens’ Power

Generation Division goals for idea generation are based on a quantity metric;

whereas, design firms like IDEO considers quality of generated ideas as being

most important (Kelley & Littman 2005). Finally, some companies consider

creating ideas of a very specific set of attributes (financial potential, feasibility,

required resources, and so on) as being a successful outcome of idea

generation.

Now, one way to test a control model is through the application of controls

and the monitoring of outputs. If the given control produces the required

successful output then the model is supported as useful. In a process, like

manufacturing, where quality is the main output this is a relatively straight

forward. However, for a process like idea generation where the outputs are so

variable and dependent upon a huge variation of needs, testing the impact a

control has on the output is tremendously more complicated, and may be to a

large degree futile because of the large interdependency amongst the control

variables.

Hence, the standard approach of testing control variables against their

outputs may help support this control model for a small set of instances, but will

not provide the needed evidence to support it broadly as a means of controlling

idea generation.

As for idea management, the process is so poorly understood that besides

not having models to describe its basic functions, there again is no metrics

describing successful idea management. Hence, a similar argument can be

made against doing causal studies to support specific control variables for idea

management.

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4.3. Study Type Which Will Not Be Used

The goal of this section is to make a rational argument for the selection of the

survey and interview based studies, by showing that the other optional studies

are inadequate.

4.3.1. Observational Based Support Studies

There are more limitations and downsides to conducting an observational study

than benefits. Observational studies are not going to be chosen for this research

because it:

• Is not economical and can be inefficient

• Will not allow the author to obtain a large enough sample size

• Requires extensive time to conduct

Additionally, because there are no particular behaviors which are trying to be

uncovered, examined, or validated, there is little need for an observational study.

Additionally, practitioners will accurately self-identify their current management

practices through tools like interviews or surveys. As a result, verifying this via

observations is redundant and inefficient.

4.3.2. Application Based Support Study

Testing this model was excluded from the research options because to truly test

a control model it must be applied in practice. This would require a company to

use the model to control their idea generation activities. Several companies have

expressed a willingness to implement this model; however, due to the time

required to gather results it will not fit within This researchers expected

graduation dates. Finally, application to a small set of companies will not provide

the evidence needed to support this model across industries. For these reasons,

an application based study will not appropriate.

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4.3.3. Laboratory Testing Base Support Study

Although, laboratory base tests are a common means to supporting a control

model, the author does not feel it would provide the needed support for this

study. First, practitioners will not see a laboratory reproduction of the idea

generation process as being an accurate representation of idea generation in

their companies, and often they scoff at laboratory studies. Again this is because

of the large disconnection between the complex worlds of actual business and

the idealized laboratory environment.

Finally, it is extremely difficult to reproduce the specific and changing

needs of a company, and the pre-set conditions of the business environment in a

laboratory setting. For example, asking a group of random individuals in a lab to

generate ideas for new cell phone technology will not accurately reflect a group

of telecommunication engineers with years of design experience producing ideas

in their own company environment. Hence for these reasons, laboratory tests will

not be performed.

4.3.4. Analysis of Secondary Research

Unfortunately, a secondary research study cannot be conducted because there is

no existing quantitative data on companies’ idea generation processes, practices,

or behaviors. Only, a few case studies on a company’s idea generation process

exist. Thus, the data must be generated through primary research.

4.3.5. Interview Based Support

Interviews will be used to support this model, however due to the limitation in

sample size they cannot be the only means of support. Additionally, interviews

can give detailed case examples of how companies manage idea generation and

idea management. However, interviewing requires substantial time and

resources if done over a large sample. Thus, interviews can be used in this study

but must be augmented with data from other supporting studies.

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4.3.6. Electronic Survey Study

A survey based study was chosen as the primary research design for this study.

This research design is appropriate because:

o It is economical and efficient

o Can capture a wide target population

o Can generate quantitative and qualitative data on practices, perceptions,

and needs.

There are several additional reasons why a survey was chosen as the primary

study instrument. First, the survey will be able to determine the practices and

satisfaction of the respondents with respect to idea generation and idea

management processes over a large sample size. Second, a large set of data

showing other companies best practices will be viewed a creditable and provide

the supporting evidence needed to develop broad acceptance of this model.

Third, surveying of practices, perceptions, and needs will show

weaknesses in current practices which may need to be addressed. Hence, solid

data on these weaknesses will help raise awareness of a problem area, and will

aid in the adoption of new practices.

Finally, by having the large pool of supporting evidence across several

industries will help the board acceptance of this control model. None, the less

surveying alone has weaknesses which are it:

1. Will not show if additional points of control can be used

2. Will not show if the model produces understanding

3. Will not show if the model accurately represent the idea generation

process?

To eliminate these weaknesses, this study will be combined with interviewing. In

particular, additional missed points of control may be uncovered through

interviewing with practitioners and researchers. Supporting evidence that this

control model generates understanding can also be obtained through

interviewing of a small sample. Finally, the weakness of accurate representation

cannot be solved through this study, and must be addressed in future research.

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4.4. Parts to the Study

To strengthen the support evidence for the research questions this study has

been split into two separate studies.

1. A series of case studies based on three very different companies

2. A normative and correlative study using an electronic survey with over

thirty respondents

4.5. Study Part One

The case studies consist of three companies with mature product development

processes in different industries. First, the company’s sponsors were asked to

identify the top three individuals in the company responsible for or most

knowledgeable about idea generation and idea management practices.

These individuals were sent an online survey (see Appendix C) of which

they collaboratively answered. The surveys answers were reviewed by This

researcher and sets of questions were formulated for the individual interviews.

Interview questions were based partially on areas of strength and weakness

determined from the survey responses. Each of the respondents was interviewed

for 1 hour, in which pre-determined questions were asked as well as follow-up

questions. Other interview questions revolved around the following topics:

A) Current company situation and strategy

B) Market served by the company

B) Current practices for idea generation and idea management,

C) Current needs for the early front end of innovation

D) Level of satisfaction with their current idea generation and idea

management practices

E) Detailed examples for use of each point of control.

All information captured from the interviews and online surveys were analyzed

and transformed into three case studies with recommendations for

improvements. The information was analyzed with the help of this researcher’s

proposed model.

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As compensation for their participation the companies’ sponsors will

receive the case studies and associated recommendations in a written report and

is considered a pro-bono consulting job.

Case study companies were selected from a pre-known batch of large

mature companies which was already personally contacted, and selected to

show diversity of size, situation, and industry.

4.6. Study Part Two

4.6.1. Description of Part Two

The second part of this study was structured into three elements. First the study

consisted of a (1) small number of interviewees, and then move to a (2) small

pilot survey study, and then towards a (3) full survey study. This format is a

variation on the total design study recommended by (Dillman, 1978). The

interviews will be conducted for the following purposes:

1. Test to see if the control model develops understanding and satisfies

the first research question.

2. Obtain case examples of points of control at specific companies.

3. Uncover points of control which should be included in the model, hence

further developing the model.

The interviews were first conducted with two expert researchers (Michael

Menefee and Kenneth Kahn) who were shown the model, and asked about the

overall setup of the questionnaire. The recommendations were integrated into the

survey instrument. This helped refine the structure of the survey and reduce

possible measurement errors.

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Next, the survey was sent out in a small pilot study to four or five company

respondents. The purpose of the pilot study was:

• To uncover confusion in the survey’s questions

• To get a rough estimate of measurement error

• Do a preliminary analysis of the data to see if the obtained data categories

provided the needed information for supporting the model

This preliminary pilot study obtained 5 respondents, and the data obtained

showed of 0.6 Cronbach which is good reliability for such a small number of

respondents. Further, post interviews with respondents showed no confusion

from the survey’s questions.

Finally, the full survey was sent out and data was received over a two

month period. This researcher used two web seminars to develop interest in the

survey. The web seminars were hosted by RYMA technologies and discussed

the idea generation and idea management process in a one hour long web

presentation during which one minute was devoted to promoting This

researchers survey. The attendees were primarily managers with product

development responsibilities. The attendees (122 individuals) were then emailed

an invitation to take the online survey which resulted in the highest completion

rate.

Additionally, web posts inviting individuals ‘to take the survey’ were posted

on Linkedin.com’s “front end of innovation group” and “product development

group”. These had very low completion rates.

4.6.2. Description of Survey Tool

The survey tool will have three main parts: a) identification questions, b)

satisfaction questions, and c) current practice questions.

Identification questions will be: who they are, how much knowledge they

have of their companies practices, the company they work for, industry,

revenues, number of employees, and so on. This will help qualify the

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respondents as a reputable source of data, and provide data to compare

respondents and their companies. All published data will be de-identified from the

company’s and respondent’s names.

Unfortunately, the best dependent variable which could be selected was

the satisfaction based variable. Many research studies have shown satisfaction

to have a strong correlation with output and results because respondents innately

have a sense of what works and what does not and correlate their satisfaction

respectively.

Dependent quantitative variables such as number of ideas, revenues

generated per ideas, number of ideas captured from the employees, number of

ideas captured from outsides sources, average revenues per idea were noted in

the case studies to vary greatly between industries and company size. Further,

respondent’s accounts of these numbers were found to be totally un-reliable

because they did not keep track of these numbers.

Other dependent qualitative variables such as: quality of ideas generated

quality of ideas captured from employees, and quality of ideas in the idea bank,

were found to be highly objective and mostly unknown amongst interviewees of

the case studies, and hence were deemed totally un-reliable.

Unfortunately, amongst all the reviewed literature no articles were noted to

measure output of the idea generation or the idea management process, or even

link idea generation to development output such as: revenues, or new product

releases. Consequently, there were no dependent variables to build upon. Only

one article was found to have a correlation linking idea generation to marketing

information (Husig, Kohn, & Poskela, 2005). Due to these problems, the only

logical and halfway reliable dependent variable was that of “satisfaction.”

The respondent’s level of satisfaction was split up with respect to the

outcomes of their companies, a) idea generation processes, b) idea management

processes, and c) development process. This allowed one to draw valuable

correlations between levels of satisfaction and actual practices.

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Questions regarding current practices looked for points of control which

are currently in use in their business. This will develop the needed support for

each control point mentioned in the model. More interestingly, this will give a

general understanding of how much control is placed on a particular activity.

Current practice questions were broken up into amount, and frequencies and all

used a five-point Likert scale (never, rarely, some-times, most-of-the-time,

always, don’t know, NA). The survey can be seen in Appendix C.

4.6.3. Description of the Respondent Pool

RYMA solution community consisted of 50,000 members of which 90% product

development managers from companies all over the world. On average, 100

members read the blog daily, and over 150 members on average attend their

web seminars.

4.6.4. Data Analysis

This survey tool output all responses in an excel file format. Exported data from

the survey was automatically organized by the survey tool by respondent. The

analysis of the data was rather straight forward, and required comparing data by

respondent companies, industries, satisfaction, and so on. Graphs were created

showing results of the data, and all data were de-identified from the

respondent companies. Comparison and correlations were drawn, and

examined to determine statistical significances.

Normative data, graphs, and charts were created showing the current

practices and methods controlling the idea generation and idea management

process. Finally, this research shows the practices most associated with

satisfactory outcomes for idea management and idea generation. The resulting

data gave a strong base for future researchers to attack and make great strides

in idea generation and idea management.

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4.7. Human Subjects

For the purposes of this research, human subjects’ approval was sought and

obtained prior to the study’s commencements, as required by the Purdue

University, and consistent with current research standards. The study’s reference

number is 0808007117.

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CHAPTER 5. RESEARCH RESULTS

The following chapter presents the research findings for both the case studies

and the qualitative survey. The research findings are broken up into two sections

being: (1) case study results, and (2) quantitative survey findings, which each

section including a respective discussion and conclusion. The duel research

study approach would lend more support for the proposed model and help in

answering the second research question. The first research question was

answered in Chapter 3.

5.1. Summary of Case Study Results

These three case studies show distinctly different companies and their respective

idea generation and idea management processes. These companies provided an

adequate diversity, with the first company being a multinational large cap

company with products in every geographic market. The second being a small

cap company with products mainly in the US, and the third being a small

company marketing a new software technology to a pre-adoption marketplace.

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Table 5.1. Attributes of the Three Companies Company Name Alpha Company Fairbank's Scales Cartêgraph

Company size Large Cap Mid cap SmallEmployees 125,000 500 80Revenues $5 billion + $100 mill + $30 to $50 mil

Product area Consumer Food products Scales - machinery Software managementMarket Age Highly Mature Highly Mature Pre-adoption

Business ModelSells products to food retail chains Product manufacturer

Subscription based business model

SituationLack of capturing ideas from outside sources Need disruptive ideas Needs help crossing chasm

Major Recommendation Reorganization of process

Broader perspective of their business

Have idea generation create ideas to help cross the chasm

5.1.1. Benefits of the Case Studies

There was a great benefit to conducting these detailed case studies. First, the

detailed analysis allowed this researcher to probe deeper into the situation than

the simple online survey would have allowed. This probing uncovered company

situation and market age played a large role in all case studies. Further, the case

studies uncovered motivations and underlining issues which would not have

been picked up by the survey. Simply put the detailed analysis through

interviewing allowed for much more detailed analysis and a rich learning

opportunity.

5.1.2. Analysis of the Company

To aid in this analysis, company Alpha’s idea generation and idea management

practices were compared to this researcher’s idealized (Glassman Model) idea

management model. It was found that these comparisons allow the author to

quickly identify areas of weakness & strength and in detail and see how the

minor differences in their practices affected the overall process.

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5.1.3. Brief Summary of Each Case Study

In order to highlight the lessons learned, each case study will be summarized

and it’s associated lessons will be briefly discussed. Again, each detailed case

study is listed in the following section. Please note that each case study contain

recommendations made to the company’s sponsor which are interwoven into

body of each study. As mentioned previously, all companies were analyzed with

the assistance of the Glassman model.

5.1.3.1. Summary of Company Alpha

Company Alpha (de-identified) presented an interesting case of a large multi-

national with multiple dedicated research facilities. This case study focused only

on one of their research facilities located in Europe which concentrated on

developing food products: hot drinks, chocolates, coffees and employed 500

researchers. This R&D center had a 2007 $110 million R&D budget.

This research center had great difficulties in capturing, storing, and

diffusing ideas generated by their large number of employees. Unfortunately,

researchers did not use the idea management software offered by the company

because it was cumbersome and lacked major features. The main lesson learned

here was that an effective idea management software system is needed for idea

management inside of large companies which handle large number of ideas.

Second, the company only practiced a limited range of idea generation

activities and did not conduct any more beneficial idea generation activities

involving customer research. This major error was found to limit the number and

quality of the generated ideas.

Third, the company did not capture or accept ideas from outside sources

being: partners, suppliers, customers, inventors, or universities. Because of the

size and visibility of the company they could easily receive many dozens of ideas

per day. Not the having means to capture ideas from these sources was an

error.

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5.1.3.2. Summary of Fairbanks Scales

Fairbanks Scales is a small capitalization company with revenues around $100

million, and 500 employees, of which only 16 are involved in R&D. Fairbanks

Scales strictly produces scales and weighting equipment.

Interestingly, their strict adherence to the “scale” concept seemed to have

stalled their idea generation process. Their multiple markets for scale products

are highly mature and attempts by Fairbanks to generate “scale” ideas for these

very saturated markets resulted in fruitless ends. As a result, Fairbanks Scales

rely interiorly on capturing ideas from a multitude of sources: partners, lead

users, customers, suppliers, universities, and on.

To avoid stalling the idea generation process, this researcher

recommended (based on Levitt’s Marketing Myopia article) that they broaden

their strategic view to “being in the business of providing assurance and

information on any physical attributed” instead of “being in the business of

making scales.” In addition, this research recommended that they look at the

whole job process of their customers so they can generate product ideas which

integrate other functions and functionalities in addition to weighing. For example,

a potato chip bagger can also integrate a scale into one machine to assure the

proper product weight.

Associated idea generation activities were recommended based on this

larger strategic view and they should bring about many fruitful ideas.

5.1.3.3. Summary of CartêGraph

CartêGraph is the smallest company studied at $50 million in revenues and 100

employees and produces software management tools for local governments to

manage maintenance on items like: roads, streetlights, sewage pipes, and so on.

Interestingly, only 1% of local governments use software to aid in managing their

infrastructure, hence this technology can be considered a pre-adoption market.

Given the pre-adoption status of their market and that the bulk of their future

profits lie in the mass market adoption of this technology, this researcher thought

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it best if the idea generation activities focused exclusively on creating ideas

which specifically helped the mass market in adopting this technology. As well,

this researcher highly recommended integrating “crossing the chasm strategy” by

Moore into the strategy and development decision processes of the company

(Moore, 2003).

CartêGraph’s idea management process was very haphazard and many

recommendations were made for improvement. In all, it was interesting to see

how important it was to tie idea generation into the larger company strategy.

5.2. Case Study 1: Company Alpha

5.2.1. Background on the Company

Company Alpha (cover name) is a large company with consumer food products

in every major geographic market. Company Alpha’s R&D divisions are spread

out into individual R&D centers around the world. Because of the R&D center

approach, innovation efforts are decentralized which allow the company to

specialize in particular markets/country preferences. This study concentrated

only on one R&D center located in Europe, employing more than 250 workers

and with a R&D budget larger than 50 million.

5.2.2. Sources of Ideas for Idea Generation

Company Alpha always uses employees in idea generation activities.

Unfortunately, customers, universities, suppliers, independent inventors, &

partners are rarely asked to participate in these activities, and it is strongly

thought that efforts should be made to include these groups.

It is thought that the company’s use of social awards is a very weak way of

incentivizing employees to participate in idea generation activities, aside from the

activities which require participation. Handing out strong incentives like larger

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monetary, tangible, and much more publicized social incentives would be much

more effective in creating participation in idea generation activities and events.

Food was found to be an incentive boosting attendance, but it was unclear if this

aided in active participation in the idea generation exercises. The company may

find the total cost associated with these incentives initially high, but respectively

they may be low per idea.

5.2.3. Events and Activities Used to Generate Ideas

Employees are the main group that participates in Company Alpha’s idea

generation events, which mainly entail a short half day brainstorming session.

Unfortunately, more effective idea generation activities like: contextual /

ethnographic research, lead user innovation, portfolio analysis, and blue ocean

strategies were not mentioned to be used. There is clearly a very strong need for

idea generation activities which generate ideas from a depth of consumer

understanding, like contextual / ethnographic research.

It was also found that company Alpha has no or very few customers

participating in idea generation activities; hence, there is a very strong need for

customers to participate in idea generation. Interviewees mentioned in-house

customer focus groups are used; however, research has shown that these are

not as effective in extracting ideas from customers as other activities, and in

many cases merely extract opinions and preferences.

More valuable ideas and opportunity areas can be uncovered by holding

sponsored events like idea competitions (Pillsbury’s bake-off), idea fairs (recipe

fairs), and ethnographic / contextual research studies. This researcher strongly

feels that money should be put into sponsoring, hosting, promoting, and

incentivizing these events with awards and prize money. This has been shown to

be effective in generating new ideas in the food products category, as well as,

has helped increasing consumer loyalty (Stach, Lonsdale, & La Venka, 1992).

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Intellectual property concerns should not be a factor for these public

events, mainly because patents are a weak form of protection in the food

industry. Also the benefits of finding new opportunity areas, like finding a need for

longer-keeping ice-cream, are much greater than the IP risks.

In-house competition and idea fairs use only employees are a great way

for the company to build their expertise in holding these events. As well, in-house

competitions can be conducted for a minor cost and does not have the

intellectual property issues or liability issues of a public event.

During the brainstorming sessions the company seemed to offer

participants adequate resources; such as, samples from the competition,

competitors TV commercials, magazine ads, paper, pencils, whiteboard space,

and food to eat as snacks which seems to provide a substantial incentive to

participate. Without too much more effort the company could use more effective

idea generation activities like: 6-3-5, visualization experiments, scenario

activities, experimentation activities, during the time used for the traditional

brainstorming session. Additionally, any customer site visits should be combined

with idea generation activities so more value can be extracted from the visit.

Interestingly, employees usually did not scan the idea database prior to

attending idea generation activities. This leads this researcher to believe there is

a need for more idea seeding activities taking place prior to the idea generation

activities. Hence this researcher would recommend employees perform some of

the following activities prior to participating in an idea generation session:

scanning the idea database, reviewing new competitor ideas/products, attending

conferences (if possible), review trends affecting the food industry or the

consumers food preferences, review market research reports. Other seeding

activities like food fairs where employees show off new food ideas in a close

internal forum (say once every 6 months) are a fun, effective, & low cost way to

seed ideas across the research center’s employee base (Hardagon & Sutton,

2000).

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5.2.4. Screening Ideas upon First Submission

Screening of ideas usually is applied correctly at Company Alpha, with ideas

being submitted to team leaders or project directors and then screened using a

strategic screen before being entered into the idea database. The decision

results of the screen are a) yes store idea, b) hold idea, & c) reject idea, and

usually are performed by the employee’s team leaders.

The innovation support officer mentioned that some ideas may be rejected

for technology feasibility reasons, this is a mistake First because the first screen

is strategic not technical, and Second because the technically infeasible ideas

may become feasible in the near future or are unknowingly feasible, and should

be stored in the idea database and used as seeding ideas.

Proctor & Gamble showed that many good ideas should not be limited by

technical feasibility, for example they had the idea of printing words and funny

phrases on potato chips but no clear way of doing so. After soliciting their

solution network it was found that a company in Italy had the technology to make

this idea technically feasible. If the first screen was a technical screen, this

valuable idea would have been lost.

Hence, ideas which are technically infeasible but strategically appropriate

can be accepted, but it is recommended that they be tagged and stored in the

idea database as technically infeasible this way the can be revisited or

researched further in the future, as well as be used as a seeding idea in other

idea generation activities.

5.2.5. Capturing Ideas from Internal and External Sources

There are several major issues associated with capturing ideas and formally

placing them in the idea database which are severely limiting this activities

effectiveness, being: (1) energy required to capture an idea, (2) the lack of

functionality of the idea management software, and (3) the limitations in feedback

associated with submitting an idea.

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All interviewees agree the act of capturing ideas is very weak and

consequently is severely hurting the “buy-in for the idea management system” at

their research center.

There are fifteen key people in the research center which are tasked with

capturing ideas. An idea may be submitted to these individuals in person, on

paper, over email, or directly entered into the idea management software which

is called “Accolades.” The idea coordinator receives the bulk of the submitted

ideas from these fifteen key people or other employees so that they can be

entered into the “Accolade” system or routed to the appropriate department

heads.

All individuals tasked with receiving ideas should be specifically trained

not to criticize ideas, and instead should talk and search for the valuable

parts/aspects of the idea with the submitter. Those points of value may later be

combined with other ideas to create a truly valuable product, and quickly judging

and idea looses that valuable information. For example, a poor idea like a hot

energy coffee drink with extra ginseng, was combined with the idea of a cold

coffee to make Rockstar Roasted coffee drink.

Interviewees mentioned employees do not like “Accolade” because it

takes too much time/energy to submit an idea, and would prefer to submit ideas

to their team leader for instant feedback or approval. Further the “Accolade”

system does not allow for pictures or attachments to be submitted with the idea.

Food products very much need visual representation; hence this researcher

deems this idea management software to be useless.

Finally, the software does not allow for feedback on the idea. This goes

back to prior research which mentioned the social & developmental benefits of

talking about ideas, prior to entering them into some type of idea management

system. Many newer idea management systems allow for feedback and

conversations to take place around an idea. The act of talking about and refining

the idea is a vital frontend activity and can be done over software or in-person.

Bean, & Radford (2002) talk about a free in-house coffee bar to make employees

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meet to talk about new ideas, and found it was effective. Accolade’s feedback

limitation also limits it usefulness. In all, “Accolade” severely limits the

acceptance of the idea management process inside this research center. Thus

other software solutions should be sought.

5.2.6. Sources Tapped for Ideas

Currently company Alpha is only capturing ideas from employees and is

unfortunately not receiving ideas from consumers, suppliers, partners,

universities, or independent inventors. Great efforts should be made to capture

ideas from consumers; however for this to occur, a large deal of companywide

decision making must take place.

Consumers must be aware that company Alpha is open to ideas, and for

this to occur the company’s websites, product packaging, customer service

representatives, and sales people must have mechanisms & processes to solicit

and capture ideas. Because of the difficulties associated with capturing ideas

from all consumers, it is recommended that company Alpha focus first on lead

consumer and thus approaches and solicits specialist clubs or groups for ideas,

like a chocolates cooking group which are pushing the boundaries of their craft

(Von Hippel, Tomke, & Sonnack, 1999).

Partners and suppliers are deemed much easier to solicit and capture

ideas from since they can be made to contact one person; however, they must

be properly incentivized. A generic licensing or royalty agreement should be

enough to entice patentable products, and an idea submission bonus should be

put in place for submission of justified opportunity areas. One noted method of

gathering ideas from a partner or supplier is to describe a problem area or

particular problem and request the partner to submit ideas. This was shown to be

effective in P&G’s open innovation network (Von Hippel, Tomke, & Sonnack,

1999).

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Interestingly, company Alpha has a detailed competitive intelligence

process which notes their competitor’s newest products; however, these product

ideas and opportunities areas are not being placed into the idea database.

Company Alpha noted intellectual property is a concern when accepting

ideas from outside sources. However, the IP process should be made to check

on the IP concerns for submitted ideas not limit the ability of the company to

accept ideas from outside sources. They have demonstrated limited IP risk in

their open innovation practices by restructuring their IP process to check IP

concerns throughout the process not to mitigate risks upfront as would be the

case in most companies. This goes back to the old adage “lawyers are not there

to make business decision.”

5.2.7. Tagging Ideas during Capture

The company is properly tagging ideas by recording upon capture “who created

them”, “when they were created”, and “who else participated in their creation”;

however, they are not capturing what “activities lead to the ideas creation.” This

is valuable because as more advance idea generation activities are used, the

ability to track which activities generate a particular idea will be very valuable in

selecting future idea generation activities and recording ROI for a particular idea

generation activity.

5.2.8. Storing and Categorizing Ideas

Currently, the idea management software “Accolade” is not allowing for effective

storing and categorizing of ideas. Ideas should be stored with pictures and other

media as mentioned. As well, categorizing of ideas is in-adequate. Ideas are

currently categorized by product category, exploratory, & technical. But this

researcher recommended that they should also be categorize by, date, batch

number, associated submitters, detailed source (consumer, partner, supplier,

employee), opportunity area, reviewed or not-reviewed, technical feasibility, and

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developed or not-developed. More categories help employees in quickly

reviewing ideas prior to participating in future idea generation activities, and help

the innovation directors to see where the gaps are in the idea database.

5.2.9. Process Check Used to Improve the Idea Generation Process

Luckily this company’s research center has at least three individuals dedicated to

refining and improving the idea generation and idea management process. The

interviewees were mentioned to sometimes review the process based on the

outputted ideas. Ideally the open innovation director should review ideas

submitted during a period of time to see if the past changes had the desired

effect and if the idea generation activities are having a positive ROI. These

reviews would be best made every 4 or 6 months.

5.2.10. Diffusing Ideas to Employees inside the Company

Again there are two reasons for diffusing ideas being: (1) to get ideas to turn into

new product development projects, and (2) to use the ideas to seed employees

brains so they are more able to generate new ideas. At Company Alpha, much

work needs to be done in diffusing idea to employees. Sought diffusion (allowing

employee to freely scan the idea database) is mentioned by interviewee not be

effective since very few access the database. Employees in particular groups like

chocolates or hot beverages should be made aware of newly submitted ideas in

their area via forced diffusion. Force diffusion can be performed by email

notification of best ideas every week or month, or newly submitted ideas can be

diffused to employees in batches a mandatory bi-weekly meeting.

Further, a culture should be developed where ideas are sought from

internal and external sources and discuss frequently, the best way to start this is

to force lots of ideas on employees till they get used to discussing ideas on a

regular bases. The fifteen individuals responsible for receiving ideas in this

research center should be also responsible for distributing these idea emails or

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idea memos to respective employees. Routing of ideas is being performed

correctly by the idea coordinator and seems to be the only way which ideas are

currently being distributed.

5.2.11. Comparison with Measures of Satisfaction

The satisfaction variables in the survey were compared across the three

interviewees and it was found that their opinions differed. The minor differences

were mainly due to the responsibility areas of the interviewee and knowledge in

that area, for example the open innovation officer was dissatisfied with their

ability to capture ideas from outside the company, whereas, the idea coordinator

had a neutral opinion on this matter. The results for the satisfaction variables are

shown in tables 5.2 and 5.3 below. Note number 1, 2, 3, are the number of

interviews which responded at that particular level of satisfaction for the given

question.

Table 5.2. Idea Generation Satisfaction Variable Results for Alpha

Satisfaction Variables Very

Dissatisfied

Dissatisfied Neutral Satisfied Very

Satisfied

1. Quality of ideas 3

2. Number of ideas 1 2

3. Generating idea with a

specific set of attributes

1 2

4. Time for generating ideas 2 1

5. Ability to fill frontend portfolio 3

6. Overall idea generation

process

3

Interestingly, overall satisfaction with the idea generation process (being

dissatisfied) was much lower than the dependent satisfaction factors mentioned

above. This initially led the author to believe the first five factors are not

substantial factors in determining overall satisfaction.

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Table 5.3. Idea Management Satisfaction Results Variables for Alpha

Satisfaction Variables Very

Dissatisfied

Dissatisfied Neutral Satisfied Very

Satisfied

7. Capturing ideas from

employees

3

8. Capturing ideas from outside

sources

3

9. Storing & capturing ideas 3

10. Amount, quality, & type of

ideas

3

11. Ability to distribute and route

ideas

3

12. Ability of ideas bank to fill

frontend portfolio

3

Interestingly, interviewees seem dissatisfied with three out of the five

activities in the idea management process. This researcher hypothesizes that the

interviewee’s satisfaction with the overall idea generation process is taking into

account factors which are associated with idea management. Since both idea

generation and idea management are very new areas of research with very new

terminology, it is reasonable to suppose that the interviewees consider idea

generation to include the factors 1 to 5 & 7 to 12. Hence, one can hypothesize

that above satisfaction factors can, in sum, correlate to overall satisfaction with

idea generation.

5.2.12. Late Front End Activities at Company Alpha

Through out the interviews, additional insights were gain into Company Alpha

Late Front End activities which are note worthy. Interviewees noted that after an

idea is captured and screened, the ideas are usually rushed to a second screen.

This researcher feels this is an error, because the ideas need time to be

developed before being placed in the second screen. Coopers Stage gate

process demonstrates this well. By looking at the Figure 2.9 and Appendix B one

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can see that ideas are scoped before the second screen, then have a business

case build for them and then proceed to a third screen. This insures that work is

put into the ideas to develop them and that proper kill/proceed decision are

made.

5.2.13. Recommendations for Late Front End Activities

To avoid ideas from being rushed into a second screen, this researcher

recommends some initial work be performed on raw ideas to turn them into more

refined concepts. This can be done by assigning a batch of ideas to a group of

researcher and requesting that 2 to 3 concept ideas be developed, regardless of

the quality of the ideas in the batch. This will force researchers to be more

creative and seek out better ideas from the idea database if their batch is full of

poor ideas.

5.3. Case Study 2: Fairbanks Scales

5.3.1. Background on the Company

Fairbanks Scales was established more than 150+ years ago has 500 employees

and creates scales of all types. Their scales range from small doctors scales all

the way to large truck scales, and they have 5000 product model variations and

over 100 scale product lines with all product lines being strictly scales or

weighting equipment.

The company has a typical centralized organizational structure, with sales,

service, manufacturing, development, and admin/finance departments all located

at the US headquarters. The development department has 16 engineers with 10

of those individuals involved in R&D, and a R&D budget of less than $2 million.

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Fairbanks Scales’ has a manufacture/sales business model and generates

additional revenues via servicing scales and 2007 revenues were $100 million +.

Technical details of their products will not be discussed because they were not

found to be relevant to the analysis of Fairbanks Scales’ innovation process.

The VP of development stated that Fairbanks Scales, as well as, the rest

of the scale industry has been waiting for the next major development in scales,

and consequently they have been actively looking for the next disruptive

technology, product, or major market application.’

Evidently, the scale markets are extremely mature. Case study evidence

and market theory shows that extreme segmentation only occurs in highly mature

markets. Evidence of market maturity is Fairbanks Scales’ highly segmented

product portfolio and the general age of the product markets many of which are

more than 50 years old.

5.3.2. Overall Situation & Broader Strategic View

Prior to discussing the details of the idea generation and idea management

process this researcher would like to discuss a larger and more urgent issue

which affects the greater innovation process at Fairbanks Scales. This section is

of interest to the CEO and board because it suggests a broader view of the

company’s strategy.

Research on Fairbanks Scales’ current markets and offerings and

interviews with the VP of engineering/development and director of development

have lead this researcher to “question if Fairbanks Scales narrow view of “scales”

as their core business will provide them with the required future growth?”

Aside from entering new major geographic markets like Asia, or South

America, growth will come mostly from developing new products for their

currently served geographic markets. As the VP of engineering/development put

it “we are looking for the next big thing.”

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This researcher’s initial thoughts were that Fairbanks Scales was narrowly

concentrated on developing “scales” for a highly mature and highly saturated

scale markets which has limited innovation opportunities remaining. In other

words, Fairbanks Scales had taken the scale concept, to what seems to be, the

current limits of the technology and customer needs for their currently served

geographic markets. Again, their extreme segmentation (130+ product lines &

1,500 product variations) and the multitude of application areas were evidence of

this thought. Reaching the application limits of any market is, in itself, an

accomplishment any company should be proud of!

There are many companies, existing both currently and in the past, which

have reached the limits of their current business applications and for the most

part have stalled in developing new products in categories like: pens, tables,

doors, windows, silverware, to name a few. Some product categories like “trolley

cars and horse carriages” have even been superseded and no longer exist. The

trick to getting unstuck in these instances is viewing product innovation through a

larger view, instead of a narrower product based view.

For example, trolley car manufacturer throughout 1800’s and early 1900’s

made tremendous value for their shareholders; unfortunately, they did not see

they were in the “business of providing transportation” and with the advent of

cars, & trucks, lost market share and now are in total obscurity. Hence, thinking

in line with your current product category can limit the company’s ability to

expand as famously noted by Dr. Levitt in his Harvard Business Review article

Marketing Myopia (Levitt, 2006).

Again Fairbanks Scales should consider it a great accomplishment to

have fulfilled their customer’s needs with regards to scales. Unfortunately, it

seems that Fairbanks has limited their development thinking purely to the “scale

concept.” Their manufacturing, engineering, sales capabilities and their

distribution channels would definitely allow them to expand outside of the pure

“scale” concept, into related areas.

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The lessons learned from Levitt’s Marketing Myopia article (read this

article listed on page one before proceeding) can be directly applied to Fairbanks

Scales. However, recent discussions of Levitt work mentioned that he neglected

company resources and core competencies in his theories. For example Kodak

saw the arrival of digital camera technologies but was unable to make the

transition successfully due to their lack of electronics knowledge.

Applying Levitt’s lesson to Fairbanks Scales one would have two new

perspectives on their products which will help them generate new products being

(a) broader view of their core business and (b) a broader understanding of how

their products fit into the job process

5.3.3. Adopting a Broader View of Their Core Business

As for (a), Fairbanks should understand that they are not in the business of

providing “scales” but actually in the business of ‘providing assurance and

information on a physical item.’ Again people don’t buy drills; they are buying the

ability to make a hole. Following this logic, Fairbanks has been ‘providing

information and assurance on “weight’ for a multitude of physical items for more

than a century through their scales.

Remember weight is only one physical metric of an item which a customer

may want information or assurance on. Here is a list of other aspects of a

physical item:

1. Number of items

2. Volume

3. Dimensions

4. Density

5. Hardness

6. Color

7. Odors

8. Temperature

9. Pressure

10. Orientation

11. Integrity

12. Item information (serial #)

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Take for instance a food quality assurance lab, in testing their food

products they weigh them, measure density, and in many cases test hardness or

taste. A small scale that weighs, counts average number, and measure density

and weight simultaneously may be valuable especially if it can be integrated

directly into a production line.

Similarly scales that can automatically measure dimensions & weights

may be valuable to some customers who must determine shipping costs or figure

out how to effectively pack a semi-truck. Hence, one can use the above list, and

a broader view of ‘providing assurance and information on physical items’ in

formal idea generation activities to create many new product ideas which would

build on the core strengths and sales channels of Fairbanks.

5.3.4. A Broader Understanding of How their Products Fit into the Job Process

Fairbanks should adopt a broader view of how their products fit into the larger job

process when generating ideas for new products. For example, the vertical

bagging machines shown in figure 1 below weighs but also bags and seals items

like food. This machine provides assurance that the correct portion size (by

weight) is dispensed but also performs the next step in the job process which is

bagging the product. Performing this additional step greatly increases the value

of the machine, and it is no longer just a scale but a larger and more valuable

piece of equipment.

Figure 5.1. Vertical Packaging Machine with Integrated Scales

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Hence, looking at the steps before and after the weighing in the job

process will help one generate more new product ideas. For example, look at a

ranch hand that is tasked with weighing cattle. First the hand must round up the

cattle and bring them home. Then the hand must read the cattle’s ear tag

number, put it on the scale, write down the weight, compare the weight to the old

weight (to assure the cattle is growing properly), then calculate the weight

increase, and release the heifer if it is the appropriate weight. If it is sick they pull

it aside to quarantine it so the veterinarian can check it out.

Thinking more broadly one can integrate the scale forward and backwards

into this job process and hence create a more valuable product. For example the

cow’s ear tag could be scanned by the computerized scales by a simple RFID

chip embedded in the cow’s ear tag or bar code printed on the ear tag. The

scale’s memory would then pull up the cow’s old and new weights. With this

information in the memory the scale could print out metrics valuable to the

rancher like, pounds gained, average pounds gained over last 3 scans, average

pounds gain per month, and so on. The scale could even beep loudly or marked

a cow with spray paint if it lost weight, so the rancher can inspect them or

quarantine them.

There is great value in looking at the whole job process and seeing how

weighing fits in, and then using that understanding to generate ideas. Best of all

these new product ideas should fit into the sales channels and build on the

strengths of the company. With these two new perspectives discussed, this

thesis moves on to details of the idea generation and idea management process.

5.3.5. Idea Generation

It was found that Fairbank Scales’ did not have a process for, or conduct any

activities for idea generation. More specifically, they did not hold idea generation

activities, host idea generation events, or select individuals to generate ideas.

This finding was confirmed among both interviewees, where one interviewee

mentioned “we conducted several brainstorming activities and found that they

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produced very mediocre ideas which were already present in our idea bank.”

Thus they stopped all idea generation and rely presently on capturing ideas from

internal and external sources.

This researcher hypothesizes that many companies experience similar

frustrations from a lack of success in idea generation. It is thought this is partially

due to a lack of expertise in effectively conducting idea generation activities. This

is understandable given the large gap in the literature on how to effectively

conduct idea generation activities.

In the case of Fairbanks Scales, it is even more likely that frustrations and

fruitless results would arise using the narrow “scale” concept to direct idea

generation activities especially given the maturity and saturation of the scales

markets.

5.3.6. Recommendations for Idea Generation

Again, it is recommended that Fairbanks Scales take a broader view of their

business so they can venture into related products and grow successfully. Their

narrow view of producing just “scales” has stalled all idea generation activities,

and it strongly felt that shifting perspectives, as elaborated on, will reinvigorate

the company’s idea generation process and produce worthwhile new product

ideas.

To do this, the new perspectives must be discussed and infused within the

larger company, being sales, service, engineering, and development. As well, the

intent for these new perspectives must also be discussed.

Next the management inside of Fairbanks Scales namely the VP of

engineering and development and the product development director must

familiarize themselves with the recommendations for the idea generation

process, namely because they will be the parties managing and conducting this

process.

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To generate ideas, Fairbanks Scales should use formal idea generation

events where a set of employees are assigned and required to generate ideas,

obviously the most observant and creative employees are preferable for these

activities. The exact mix and number of employees is based upon the selected

idea generation activities.

The VP of development/engineering desires large revenue ideas, which

can be classified as A) disruptive ideas or B) new opportunity areas. Strictly

speaking disruptive products are those which are set to supersede a preceding

product and utilize some major shift in function, technology, or use. For example,

flat screen TVs were a disruptive product when compared to tube televisions. A

new major opportunity area maybe a new application for a product like

integrating scales into medical beds or GPS for cars, where previously no

product or technology was filling the need.

One should note that the idea generation activities used to generate

disruptive or new major opportunity areas are much different than the activities

used to generate incremental product ideas. Hence, this researcher is

recommending idea generation activities which will primarily generate disruptive

ideas or new opportunity areas.

Table 5.4 shows a list of idea generation activities which fill the prior

mentioned goals, remember each activity requires a moderator or director who is

trained (self-training possible) on how to properly conduct that activity. Further,

the company should not spare budget on particular idea generation activities, for

this will greatly affect their output. Note that idea generation techniques are used

inside of idea generation activities. For example, a scenario games can be used

to augment a brainstorming activity; whereas, problem inventory analysis is a 1

hour long activity in itself.

As well, the list above shows several idea generation activities, and the

cost and time associated with each activity will vary based on that activity. It is

recommended that at least 3 to 5 activities (with one of them being a large

budget activity) be conducted per month till a sufficient number of new ideas and

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opportunity areas are discovered. Remember an opportunity area only highlights

a particular customer need, and that further idea generation activities should be

used to generate specific new product ideas which can capitalize on that

opportunity. As a result, many more than three activities should be conducted per

month if a valuable new opportunity area is discovered.

Table 5.4. Recommended Idea Generation Techniques and Activities

The list above also focuses heavily on activities which require customer

visits or observation of customer activities. This is because the company is

looking for areas where (1) they can provide additional assurance and

Idea Generation Techniques Experimentation Measure, tests, validate, via physical, virtual, or thought experimentation

with the goal of confirming a hypothesis or gathering data

Charting and plotting Helps visualize unknown or un-seen relationships

Use this technique in problem inventory analysis

Scenario games Create scenarios and play them out to their logical end Adaption Adapting a solution, offering, or process to suit a companies need by

modifying it as needed

Reduction Reducing the amount, functionality, or features of a particular thing Elimination Eliminating a particular, feature, attribute Raise or increase Increasing a particular feature, attribute or factor above the norm Division of parts Breaking up the whole into smaller and smaller features, functions, or

pieces

Perspective shifts Using a perspective or view to aid in generating new ideas Removing boundaries Removing boundaries, and retesting base assumptions, do not assume

restriction unless strictly told

Detailed observation Looking closely at something, trying to understand every facet, function, and behavior

Idea Generation Activities

Brainstorming Creating ideas in open discussion, (typically many techniques are applied)

Use hybrid using each one of the above techniques

Contextual research See appendix B

IDEO process IDEO Idea Generation Process see appendix A

Job Mapping See the article “the customer centered Innovation map” on page 1

Hybrid-Brainstorming

Brainstorming using techniques above and using the two (2) suggested views on page 3 & 4

Customer Focus groups

A collected group of individuals (customers) focused on giving feedback on a particular product, service, or process

Problem Inventory Analysis

Generating a list of negatives or problems with an offering, product, or process, and then finding solutions to eliminate those negatives

Critical path mapping

Graphically representing activities their duration and fining gaps and problems with their flow

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information on physical items outside of weight, and (2) analyze the greater job

process to identify steps where they can add additional value. Not conducting

customer visits is a major error!

Innovation managers must keep in mind that employees are busy, and for

them to dedicate time to idea generation there must be an incentive in place.

Fairbanks’ did not have an incentive system for patents or new ideas; hence this

researcher recommends that using a $5K bonus for identifying a fruitful new

opportunity area, and $10K for new profitable products will help incentivize

employees. Additionally, having moneys awarded only after a new product hits

market launch will help motivate employees to do additional market research and

push possible wining products through the development process.

5.3.7. Screening of Ideas

Screening of ideas created from formal idea generation activities should be done

differently than ideas which are captured from internal and external sources.

Ideas created as a result of a formal activity should be submitted to one

individual inside the company, where a high level strategic and capability screen

is applied. For example, a contextual research activity may generate an idea for

integrating a dimension monitor into a production line weighing system, in which

case it would pass a strategic screen and a company capability screen. Note that

a feasibility screen was not applied.

Screening of ideas captured from internal and external sources should be

also done by one individual inside the company, but instead a capability screen

should be applied. One goal of capturing outside ideas is to identify new

opportunity areas, and using a strategic, or feasibility screen may inadvertently

throw away a valuable opportunity area.

As well, there is little harm in storing poor ideas, and turning down poor or

low quality ideas submitted by employees too promptly will make them less likely

to submit ideas in the future. For example, an employee may relay that a

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customer wants’ a very cheap scale for cooking. This may highlight a larger

opportunity which is integrating scales into kitchen appliances like microwaves.

5.3.8. Capturing Ideas from Internal and External Sources

Fairbanks Scales strength is capturing ideas from any source possible. The

survey shows that Fairbanks Scales always captures ideas from: employees,

customers, universities, external research labs, suppliers, consultants,

partners/alliances, in-direct competitors, independent inventors, & media

magazines by phone, email, in-person, or through the idea management

software. As well they monitor direct competitors for new product releases.

The large number of sources which they capture ideas from was confirmed to be

the result of a (1) strong need to obtain ideas for new applications, (2) the lacking

of an idea generation process, and (3) the lack of any one source providing an

adequate number of ideas.

One recommendation for improvement may be to further incentivize the

sources so that they can submit more ideas. This can be done with small royalty

agreements or bonuses to the submitters think of it as incentivizing someone

who refers you a customer. Additionally, the solutions group should advertise that

they can assist in developing ideas in-order to obtain more submissions.

5.3.9. Tagging Ideas during Capture

The company is tagging ideas by always recording upon capture “who created

them”, however, they sometimes record “when the ideas were created”, “who

else participated in their creation”, and “what activities lead to the ideas creation.”

Always recording this information is valuable because as more advance idea

generation activities are used, the ability to track which activities generated a

particular idea will be useful in selecting future idea generation activities and

recording ROI for a particular idea generation activity.

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5.3.10. Storage and Categorization

Fairbanks Scales refers to their idea database as an “Idea vault” and has a mix

of formal (software) and informal means (computer documents) for storing ideas.

Their idea management software is called “quick base” and can store images,

documents, and text. An interviewee noted that metrics and categories can be

added to help store and evaluate ideas.

This researcher recommended that Fairbanks Scales categorize ideas by:

date, batch number, associated submitters, detailed source (consumer, partner,

supplier, employee, …), opportunity area, reviewed or not-reviewed, technical

feasibility, developed or not-developed, and finally idea driver (technology,

market, customer, solution driven).

More categories help employees in quickly reviewing ideas prior to

participating in future idea generation activities, and help the innovation directors

see where the gaps are in the idea database. Finally, idea should be stored all in

one place, the idea management software or a document, not both.

5.3.11. Process Check Used to Improve the Idea Generation Process

Fairbanks Scales sometimes performs process checks on ideas and refines the

idea generation process as a result of these checks. Because all ideas will be

captured and screened by one individual (being idea manager) the act of

performing a process check becomes much simpler. By keeping a tally of the

results of each idea generation activity the idea manager can quickly discern

which activities are working and which are not, and modify the activities

accordingly.

5.3.12. Diffusing Ideas to Employees inside the Company

There are two reasons for diffusing ideas across the company: (1) to seed

employees with ideas so they can generate more ideas, and (2) to have an idea

developed and converted into a new product.

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Diffusing ideas across the company’s employee base will greatly help in

the awareness of new ideas and help in the generation of other ideas. Foster the

author of How to Get Ideas says ‘new ideas are a recombination of old ideas’, so

being aware of more ideas helps in idea generation (Foster, 1999).

Because of the company’s size, shorter monthly meetings with the larger

employee base of sales, services, and engineering employees should be used to

discuss new ideas and ask for input on each idea. Remember buy-in of the larger

organization may be required for a successful product launch and pre-exposing

them to ideas will help in absorption. Great efforts should be taken during these

meetings to insure an open atmosphere where ideas are welcomed and not

adversely criticized.

As well, an idea newsletter can be emailed monthly to the employee base

with a long list of new and popular ideas. This newsletter should also contain

reminders of incentives and upcoming idea generation events.

Because the development department is so small, it is assumed that a

decision to develop a new product will be determined solely by the VP of

development/engineering and director of product development. If the buy-in of

the board or other executives is required for development, diffusion of ideas to

those individuals should take place as those ideas progress.

5.3.13. Late Front End Activities

The VP of development/engineering has requested that other parts of the early

innovation process be examined and the following section is a result of that

examination. This researcher has determined that three major items should be

improved in the early innovation process (late front end of innovation being:

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1. Two separate processes should be created, where one should be used to

a) select, develop, and appropriate funds to new product ideas which are

exploring new opportunity areas, and the other should be used to

b) select, develop, and appropriate funds for new product ideas which are

filling a proven opportunity area (like an existing product line).

2. A skunk works team should be created to generate new ideas and quickly

explore the feasibility and opportunity those ideas offer Koen’s recent article

“Providing clarity and a common language for the fuzzy front end” differentiates

between new products which are for (Koen et. all., 2001):

1) Exploring a new applications or opportunity areas termed ‘exploratory’, and

2) Exploiting a known and proven opportunity.

Interestingly, Clayton Christenson highlights that larger company’s

process of selecting and prioritizing new product projects inadvertently prefer low

risk and high return projects, and mostly reject projects which are seeking to

explore new application areas which usually have unknown risk levels and

unknown returns (Christenson, 2003).

Hence, as Koen recommends there should be two different new product

development processes one for exploring new applications (like drilling for new

oil fields) and one for exploiting a proven area (like adding extra rigs to a proven

oil field). Both processes should include a means of A) evaluating, B) selecting, &

C) prioritizing projects for new products; however, the exploratory process should

be pushed toward rapid exploration and testing and not worry as much about

return on investment.

For example, consider a new product which can measure the density and

weight of a food item on a production line at the same. This new product idea

would be an exploratory idea because it combines a new feature unknown to the

company. In evaluating this new product idea traditional metrics like ROI and

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payback time should be forgone. Instead the idea should be evaluated on its’

ability to: a) expand the skill set of the company; b) stimulate a market reaction to

this new feature or product category, and c) its’ ability to uncover new market

applications or new opportunity areas.

Selecting exploratory ideas to continue in development can be done in

steps so to limit investment and risk. A first stage could be to gain market insight

by doing preliminary concept testing (helped by sales) and roughly determine

how the product may be engineered. The second stage may include two or three

preliminary mockups to demonstrate functionality and to learn which

configurations seem to be best. The third stage could be to push the products

into development.

Prioritizing exploratory new product ideas should be based on a future

vision for how these products may help the greater market and how they rate on

the prior mentioned metrics.

5.3.14. Skunk Works Team

To insure the exploratory process is absorbed into the organization a group

called the “skunk works team” should be responsible for executing ideas entered

into this process. This group should include two or three engineers, two or three

sales/marketing, and service employees. Individuals selected for this group

should be those which fundamentally love new products, talk about new

products, and are creative and observant. These individuals should be

incentivized with large bonuses (more than 10K for product successes), and

several of these members should participate in any idea generation activities

especially customer visits.

Further, these individuals if properly motivated will push exploratory

products through an often resistant organization, and quickly, test, evaluate,

experiment on, and iterate on these new product ideas. Remember, departments

like sales are often not motivated to sell a new and unproven small revenue

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product. Hence having a skunk works team pushing new exploratory products

through development, sales, and manufacturing will greatly help in exploratory

product successes.

5.3.15. Comparison with Measures of Satisfaction

The satisfaction variables in the survey were compared across the two

interviewees and it was found that their opinions were exactly similar. The

interviewees were “very dissatisfied” with the quality of their ideas because they

were primarily searching for large opportunities and were receiving incremental

ideas. This would relate to why they were “dissatisfied” with their ability to fill the

frontend portfolio as well.

Table 5.5. Idea Generation Satisfaction Variable Results for Fairbanks

Satisfaction Variables Very

Dissatisfied

Dissatisfied Neutral Satisfied Very

Satisfied

1. Quality of ideas 2

2. Number of ideas 2

3. Generating idea with a specific set

of attributes

2

4. Time for generating ideas 2

5. Ability to fill the frontend portfolio 2

6. Overall idea generation process 2

The inconsistency in their “satisfaction” in being able to generate ideas

with specific set of attributes, is strange and was attributed to a miss

understanding of the question as noted during interviewing.

Overall, “dissatisfaction” with the idea generation process seems to

correlate well to the depended variables 1 to 5.

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Table 5.6. Idea Management Satisfaction Results Variables for Fairbanks

Satisfaction Variables Very

Dissatisfied

Dissatisfied Neutral Satisfied Very

Satisfied

7. Capturing ideas from employees 2

8. Capturing ideas from outside

sources

2

9. Storing & capturing ideas 2

10. Amount, quality, & type of ideas

2

11. Ability to distribute and routing

idea

2

12. Ability of ideas bank to fill frontend

portfolio

2

Interviewees seem dissatisfied with four out of the six activities in the idea

management process. Obviously Fairbanks’ strength in capturing ideas relates to

high satisfaction in this area. The other factors 9 to 12 were listed as

“dissatisfied” and this researcher sees this as reasonable given the improvement

required in these areas. The “dissatisfaction” with the amount, quality, & type of

ideas in the idea bank and the ability of the idea bank to fill frontend portfolio is a

direct result of noted poor idea generation and the in-ability to capture disruptive

ideas from inside and outside sources.

In all Fairbanks was dissatisfied with the idea generation and idea

management process, and this was reasonable given the state of their process

as assessed by this researcher.

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5.4. Case Study 3: CartêGraph

5.4.1. Background on the Company

CartêGraph has around 100 employees and produces management software

which allows public governments (towns, cities, & counties) to managed things

like: public signs, streets, street lights, road markings, bridges, storm sewers,

waste sewers, water distribution, and public lighting. They were founded less

than 12 years ago, and are currently one of four major software producers for this

market. The combined customer based for local government asset management

software is small, at less than 1% of US local government entities, and thus can

be considered to be in a pre-chasm market (Moore, 2006; G. Moore, 2004). The

company is split into sales, service, marketing, product development, and

finance/admin with 30 employees roughly in development.

CartêGraph generates money via the subscription based business model,

and needs only a few customers to justify the ROI for investing in a new product.

Development times take any where from one month to seven months per product

line extension. Currently, 90% of product in their pipeline are: feature ideas

(1000+), and 2% being product line extensions, and another 8% being new

product lines. Technical details of their products will not be discussed because

they were not found to be relevant to the analysis of their innovation process.

5.4.2. Idea Generation

It was found that CartêGraph did not have a process for, or conduct any activities

for idea generation. More specifically, they did not hold idea generation activities,

host idea generation events, or select individuals to generate ideas. This finding

was confirmed amongst all four interviewees.

One interviewee noted that management were unclear how to conduct an

idea generation activity, and all interviewees noted that their company captured

enough ideas from customers, or customer service. Preliminarily, this researcher

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supposes that companies which capture adequate ideas through their idea

management process do not see a need for conducting an idea generation

process.

5.4.3. Technology Adoption

Obviously, not having an idea generation process is an error; hence this

researcher will recommend the following structure for the idea generation

process. First, the officers of the company should note that the bulk of their future

revenues will not come from releasing new products to their current customer

base (which is 1% of total market size), but will come from expanding their

customer based to new adopters of this technology.

For the company to effectively encourage the adoption of their new

technology across the broader local government market (i.e cross the chasm)

they must integrate future product releases in closely with mid-&-long term

strategies targeted at crossing the chasm.

For example, the personal accounting software market was taken across

the chasm by Inuit softwares. This was done by making the current accounting

softwares, which were very complex, difficult to use, and feature rich, to a more

simple, easier to use software with fewer features, and more elaborate help

guides. Inuit realized that for mass adoption to occur these changes had to be

made, and hence they adapted their idea generation process to output new

features, new products, and new product lines, which targeted the major factors

which they believed were required to cross the chasm.

Again, because Inuit was first to cross the chasm and effectively launch

into the tornado (which triggered mass adoption of their technology market) they

became the market share leaders and captured the lion share of revenues.

Moore again showed that the company first to market does necessarily win; it is

the company that gains market leadership during mass adoption (i.e. wins the

tornado) that wins market leadership in the long run (G. Moore, 2004).

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CartêGraph is in a similar position; interviewees noted they were in a pre-

chasm market (mass adoption has not occurred). Unfortunately, interviewees

were not aware of the major factors required to cross the chasm nor did they

have any market research to suggest what factors were required. One

interviewee took a guess that one factor was “ease of installation and

maintenance” because the current customers mentioned that installing and

maintaining servers was a very tedious process.

Thus, this researcher recommends that CartêGraph conduct a formal

research study, contacting prospective customers (pragmatic and conservative

customers not current customers) which have not adapted this technology yet,

and determine which major factors are needed for these customers to seriously

consider adopting this technology.

For example, contacting 20 pragmatic and 20 conservative customers

may reveal that the major factors required to adopt this software is: 1) no

installation requirements, 2) no new personnel requirements, 3) and up and

running in less than 2 weeks with training and support. These factors should

then be converted to measurable metrics which new products can be compared

to. For example installation times should be measured in hours and compared to

the uncovered metric for adoption which was noted by customers to be around 4

hours (half day installation).

Given this, CartêGraph should push a large percentage of its offerings

(say 30% of their product portfolio) toward meeting factors required to cross the

chasm. To achieve this, idea generation activities must be run to identify new

features, new products, and new product lines which can meet these factors.

Then after the company can confirm that one or two product lines have the major

factors required to force adoption, they should launch a large marketing

campaign targeted at forcing adoption for these product lines as described in

Moore (2006), G. Moore (2004).

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5.4.4. Types of Idea Generation Activities

Ideally, a small part of the idea generation activities should be put toward

generating new ideas for the current customer base; while the bulk of the

activities should be dedicated toward generating ideas toward meeting the

factors needed to cross the chasm. This requires the idea generation activities to

be more problem solving based and use normative creativity patterns.

Idea generation activities should be held once to three times a week, at

least 1 hour long each, and reduce in frequency when a sufficient set of solution

ideas are obtained. Creative employees from marketing, sales, engineering, and

support and some customer groups should be required to participate in idea

generation activities, at least 10 creative employees per department. Incentives

such as reduced future or free subscriptions should be given to prospective

pragmatic customers for their participation.

This researcher has recommended a long list activities and techniques

which should be conducted to provide new features, new products, or new

product lines which meet the factors required to cross the chasm. See the list of

recommended idea generation activities and techniques below. Note techniques

are used inside of activities, for example a scenario game can be used to

augment a brainstorming activity; whereas, problem inventory analysis is a 1

hour long activity in itself.

5.4.5. Idea Management

Much can be improved in CartêGraph’s idea management process, but their

strength definitely is capturing ideas from customers and successfully converting

those ideas into products.

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5.4.6. First Screen of ideas

It was not clear what type of screening criteria CartêGraph used for their first

screen of ideas. However, because ideas submitted from the idea generation

activities will be mainly directed towards solving the factors needed to cross the

chasm, a strategic screen is redundant, and a rough feasibility screen should

instead be applied. Ideas directed to current product lines may also be put

through a very rough feasibility screen.

5.4.7. Capturing Ideas from Internal and External Sources

CartêGraph’s strength is capturing ideas from customers, in particular their

current customer base. However, to cross the chasm, the pragmatic and

conservative customers in their markets must be tapped for ideas which, in

particular should be those which will help those customers adopt this new

technology. Their current customer bases should definitely be tapped for feature,

product, and new product line ideas, but keep in mind that the needs of their

current customers (being technologists and visionaries) are often different than

the needs of the mass market being pragmatic and conservative customers.

CartêGraph does not seem to tap partners, inventors, consultants,

universities, or suppliers for ideas. Interviewing could not determine if they

monitored competitor’s offerings for new product ideas, but it seems reasonable,

given their small market, that they would.

The company captures ideas from employees, but it seems like a large

percentage of these ideas were ideas from customers communicated to sales or

service employees. Development engineers do submit ideas but most ideas are

feature based with very few being new product, or new product line ideas.

The capturing of ideas seems to be done haphazardly, sometimes ideas

are submitted to their department heads, sometimes they are submitted to the

marketing manager, and sometimes the customers submit ideas to sales or

support employees, which may or may not pass the ideas forward.

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Sharing of captured ideas between those who capture the ideas seems to

be done haphazardly. It also seems that ideas for new products and new product

lines are sometimes written down in a excel document, and that the many feature

ideas are entered into a database associated with development. Ideas are mainly

submitted in person.

5.4.8. Recommendations for Capturing Ideas

This researcher recommends that all ideas should be submitted to one or two

main personnel, and that ideas from customers should be submitted to their

associated sales or support person. Then those sales or support personnel are

responsible for submitting that ideas (orally, or over email) to the two main

personnel. This will help organize the capture of ideas, and given the relatively

small number of submitted ideas (less than 1000), this structure is reasonable.

For example, new product ideas or larger could be submitted to the

marketing manager, and feature ideas could be submitted to the product

development manager in person or through the database. Given, the relative

small number of ideas it is reasonable to store the ideas in an excel sheet.

Interestingly, CartêGraph seems to have an internal favoritism toward

accepting customer driven ideas (ideas which are driven by a strong customer

expressed need). This is reasonable considering that their subscription based

business model only needs a few customers to justify a ROI decision for a new

feature or product. However, one must remember that the internal favoritism

toward customer driven ideas may be damaging efforts to crossing the chasm.

To cross the chasm, very often companies must make development

decisions and support products which meet the factors needed to force adoption,

and hence market driven ideas are more appropriate. Market driven ideas are

those which are more appropriate given the larger context of the market, for

example cereal companies develop ideas which try to gain market share

percentages instead of concentrating on satisfying a small group of customers.

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Gregory Moore speaks about the transition that companies must make to

cross the chasm, and notably mentions that products change from meeting the

needs of technologist and visionary customers to matching the needs of a

broader pragmatic customer base, i.e shifting to more market driven products in-

order to cross the chasm (Moore. G, 2004).

5.4.9. Tagging Ideas during Capture

The company is tagging ideas by recording upon capture “who created them”,

however, they are not capturing “when the ideas were created”, “who else

participated in their creation”, and “what activities lead to the ideas creation.”

Recording this information is valuable because as more advance idea generation

activities are used, the ability to track which activities generated a particular idea

will be useful in selecting future idea generation activities and recording ROI for a

particular idea generation activity.

5.4.10. Storage & Categorization

The CartêGraph stores feature ideas in a development database and ideas for

new product, new service, and new product line ideas in a excel document.

These means of storage are adequate for the current size of the company;

however, some tagging criteria (mentioned in the above paragraph) should be

added to the storage of feature ideas in the development software system.

Unfortunately, CartêGraph is not categorizing ideas in storage.

Categorizing of feature ideas is very valuable because of the great number of

feature ideas (1000+) and will help direct a particular feature idea to the

appropriate development team. As well, categorizing new product, and new

product line ideas will help in the selection and evaluation of these ideas.

This researcher recommends that CartêGraph should categorize ideas by:

date, batch number, associated submitters, detailed source (consumer, partner,

supplier, employee), opportunity area, reviewed or not-reviewed, technical

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feasibility, developed or not-developed, and finally idea driver (technology,

market, customer, solution driven). More categories help employees in quickly

reviewing ideas prior to participating in future idea generation activities, and help

the innovation directors see where the gaps are in the idea database.

5.4.11. Process Check Used to Improve the Idea Generation Process

CartêGraph did not perform process checks on ideas or refined the idea

generation process as a result of these checks. It is recommended that an

“Innovation manager” knowledgeable in idea generation and idea management

be assigned and accountable for reviewing ideas captured by the company, and

ideas generated by the company. In doing so, they should check that the idea

generation activities are producing the desired ideas. For example, the

innovation manager should check that an idea generation activity such as “whole

product solution analysis” produced ideas which will help the company cross the

chasm.

5.4.12. Diffusing Ideas to Employees Inside the Company

CartêGraph also seems very poor at diffusing ideas across the company and it

was mentioned that ideas are not getting spread across the company. As well,

monthly development & sales progress meeting are being used to talk about new

ideas. It is hypothesizes that these new idea conversations must compete for

time against the more pressing sales and development conversations, and

inevitability lose priority.

Ideally, given the small size of the company (70 to 90 employees) there

should be a separate monthly or bi-monthly meeting dedicated to discussing new

ideas. A group of ideas should be selected and assigning ideas to individuals to

conduct preliminary market research. The result of their market research will be

used in the next idea meeting to select ideas. As well, meeting to discuss new

ideas should be combined with, and held right before idea generation activities.

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5.4.13. Late Front End Activities

This researcher noted that there were several issues with CartêGraph’s

Innovation process which need urgent attending to. These issues are:

a) The need for a portfolio management process, and

b) The need to integrate crossing the chasm strategy into the company’s

development process and company strategies.

Portfolio management is a vital process which is the act of selecting,

managing, and prioritizing the mix of development projects (a portfolio of

projects) so to manage the risk, returns, and strategic implication of the

company’s future product offerings. Metaphorically think of it, as managing a

portfolio of stocks & bonds that will mature anywhere from three months to five

years out. Having a detailed and sound process for selecting and managing the

portfolio will greatly increase returns when compared to a haphazard investing

strategy.

Currently, CartêGraph does not have a portfolio management process,

and all interviewees requested a process by which new products can

systematically be selected for development. Hence, this researcher recommends

that all executives should download and read the portfolio management articles

from the page. From those teaching the executives should structure their own

portfolio management process and communicate it to the boarder company so to

create alignment and understanding.

As previously mentioned the books Crossing the Chasm and Inside the

Tornado highlighted that companies in pre-adoption markets should integrate

company strategies towards forcing market adoption. In doing so they can force

themselves into market leadership for their emerging markets. This was true for

HP in the desktop printer market, Intuit for accounting software, Nikon for digital

cameras, and so on.

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This researcher recommends that the prior mentioned marketing research

project be carried out to determining the major 4 or 5 crossing the chasm factors.

The portfolio manager should then collaborate with the board and other

executives to push a part of their company’s product portfolio towards meeting

those factors, maybe 20% of next years products.

Again, sales will not be able to cross the chasm without a massive push to

do so, thus, preliminary sales and market responses for these products will, most

the time, be false indicators of their actual ability to cross the chasm without a

massive push to do so.

However, great efforts should be taken to uncover if these new products

are: a) lacking factors preventing pragmatic customers from adopting, or b) the

pragmatic customers are not adopting because they lack confidence in the

market and need to see their friends adopt it first.

If (a) is the case, more product development work needs to be done to

ready the products for chasm crossing. If (b) is the case, work must be done to

prove to the market that these products are ready and a small portion of the

pragmatic customer must be forced into adopting and providing references to the

greater market (i.e. running the market crossing battle mentioned in Moore

2006).

Again, no market research study is ever 100% correct, and hence pushing

the whole product portfolio towards the factors needed to cross the chasm is

risky. Hence some portion of the product portfolio should be dedicated to

crossing the chasm, while the remainder of the portfolio should generate

revenues from the current customer base.

5.4.14. Comparison with Measures of Satisfaction

The satisfaction variables in the survey were taken from only one interviewee

(marketing manager) and were found not to be reliable. After the survey was

completed, the respondent was interviewed, during which point he noted that the

levels of satisfaction were in retrospect much lower than that entered into the

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survey. For example, the levels of satisfaction with the overall idea generation

process was (satisfied; however, during the interview he mentioned to be very

dissatisfied because no process for idea generation existed. Hence this

researcher must discount all measure of satisfaction from CartêGraph from this

case study.

5.5. Case Study: Discussion of 2nd Research Question Based on Case Study

Evidence

The following section discusses the supporting evidence (obtained from the case

studies) that the model satisfies the second research question. Again, the second

research question is: “Can the developed control model be supported as

capturing the required factors needed to manage and control idea generation and

idea management effectively?”

This section supports the purpose model through evidence of its useful

application in analyzing and making recommendations for the case study

companies’ idea generation and idea management process. The supporting

evidence for this model is its: (1) aid in a quick analysis, (2) systematic analysis

of the information, (3) aid in performing a detailed analysis, (4) help in uncovering

major problem areas, (5) aid in making recommendations, and (6) aid in

comprehending the information. One major factor (strategy) was found to have

been missing from the model and will be discussed in the following “lessons”

section.

First, the proposed model aided in a rough analysis of the companies

processes. Again, the interviewees first answered the online survey which was

created directly from the proposed model. Then this researcher reviewed the

survey answer. From a 20 minute review of those answers, this researcher had a

very good understanding of areas of strength and weakness in their process.

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Second, the Glassman Model helped this researcher systematically

examine the vital points of the idea generation and idea management process

and according to the interviewee help create a very detailed set of

recommendations.

Third, it was found that the Glassman model resulted in a superior

analysis when compared to simple interviews conducted around general

activities such as generating ideas, screening ideas, capturing ideas, storing

ideas, and diffusing ideas.

The resolution offered by the Glassman model’s point of control for each

activity directly helped create many interview questions which uncovered a great

deal of valuable information which otherwise would not have been uncovered.

The Glassman model also guided interviewing questions to follow a logical flow.

Fourth, the model uncovered major and minor problem areas in the

companies’ idea generation and idea management processes. The model and

comprehensive list of factors and points of control helped in uncovering major

problem areas in their company’s process that otherwise may have been missed

during un-guided interviewing. The case studies highlight the many problems

uncovered for each company, and attest to the models value in these areas.

Fifth, the proposed model definitely aided in making recommendations.

The model’s comprehensive factors and points of control insured that a

comprehensive list of recommendations was made to each company. Without the

model, it would be very easy to forget to include a recommendation for a

particular part of the process.

Lastly, all information gathered from the interviews, both solicited and

unsolicited, could be fully understood in the context of the proposed model. This

is considered to be a major step because prior to this model interviewing often

uncovered information which did not result in an understanding of the process or

was information too difficult to piece together. The purposed model aided in

mapping and understanding of the companies processes which were previously

convoluted and difficult to comprehend.

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5.6. Case Study: Major Lessons Learned

The case studies again provided a rich learning opportunity, and from this many

major lessons were learned, the following section discusses the major lessons

being: (1) a need to integrate company strategy into idea generation, (2) the

structure of idea management, (3) process dependence and (4) the need for an

idea manager.

In all three of the case studies, this researcher used the structure of the

Glassman Model to recommend changes to the companies’ idea generation

process. But the specific options for each company varied based holy on their

strategic need.

For example, CartêGraph required an idea generation process which

assisted their major strategic goal of forcing market adoption of their technology

by generating ideas which assisted in market adoption. As well, Fairbanks

Scales strategically sought large opportunity areas, and hence had to change

their strategic scope and idea generation process to follow suit. Company Alpha

also required a process to better utilize their researchers in generating ideas.

All cases demonstrated that the idea generation process relies heavily on

company strategy. This is logical considering that the process can output a great

range of ideas. In-order to focus its’ output, the company strategy must be well

known and used to select the specific options for the idea generation process.

This lesson highlights a major weakness in the Glassman model which

must be addressed. The Glassman model does not contain the factors needed to

align the idea generation process with a company strategy. Hence, the model

must be appended to include activities for strategic alignment such as: 1)

reviewing the company strategy, 2) determining major areas which ideas should

be generated for based on the strategy, 3) confirming these areas, and 4)

aligning the process. Two examples will be used to explain these activities.

In the CartêGraph case study, this researcher was told the major strategic

goal was to gain market share, from their currently paltry 1%. Given the state of

their market it was obvious that they needed to force adoption of their

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technology. This contradicted their request to generate incremental ideas for their

current customer base. Consequently, this researcher recommended that they

shift toward generating ideas to aid market adoption and forgo generating idea

for their current customer base.

On the other hand, Fairbanks Scales strategy was to grow in scales, but in

confirming these areas (step 3) it was convincingly determined that the “scale”

concept would not provide adequate opportunity to generate the needed growth.

Consequently, this researcher recommended that broaden their company

strategy (step 1), and use this researcher’s suggested areas to generate idea

(step 2). In all, it is believed that the mentioned factors and activities can be

easily integrated to improve the Glassman model.

5.6.1. Structure of Idea Management

In reviewing the case studies, it was determined that the structure of the idea

management process did not depend upon company strategy, but rather it

depended upon the number of captured ideas.

One can imagine the idea management process as a logistical process

much like a post office, where ideas/packages are: captured, tagged, stored,

categorized/sorted and diffused/delivered to the appropriate people. In this view,

the particular options for each activity depend holy upon the number of ideas

going through the process.

For example, Fairbanks Scales which only required a few ideas could

feasible perform an idea management process conducted mostly on paper;

whereas, Company Alpha which received many thousands of ideas required an

elaborate idea management software system.

From this conclusion it should also be noted, that companies which

capture large numbers of ideas most likely will need an idea management

software to conduct this process effectively. This is because a paper system, or

email system cannot feasibly deal with a large number of ideas.

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5.6.2. Situational Dependence on Idea Generation or Idea Management

Fairbanks Scales had a highly evolved set of idea capture activities which tapped

every available source of ideas known to the company. This was a direct result of

a stalled internal idea generation process. Conversely, Company Alpha captured

very few ideas from outside sources and relied entirely on their R&D staff to

generate ideas. Both these cases highlight that a company can become

dependent upon either idea generation or capturing idea via idea management.

Nonetheless, this researcher believes that both processes can be fruitfully

utilized together regardless of the company situation.

5.6.3. Assigned Idea Manager

In all of the case, this researcher recommended an owner/manager of the idea

generation and idea management process. It is believed that having and single

or set of individuals responsible for obtaining ideas imparts needed internal

accountability on getting ideas into the pipeline. As noted by the literature, the

lack of clarity of this process and lack of accountability was responsible for many

problems. Given the proposed Glassman model and the review of material

presented in this dissertation, it is very reasonable that a manager could learn to

effectively manage these processes and be accountable for their results.

5.6.4. Expertise is Needed

Although the above information supports that the model contains the factors

needed to manage both processes, it was found that some expertise is required

to use this model to manage these processes. In particular, an innovation

practitioner requires the expertise to knowledgeably select amongst the options

presented for each point of control. For example, the selection of the appropriate

idea generation activity for Fairbank’s Scales required a general understanding of

all activities and the output for each activity. Only then could an innovation

practitioner effectively select the appropriate idea generation activities.

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5.7. Survey: Method of Cleaning the Data and Analysis

Several actions were taken to prepare the survey data for analysis. The first was

scanning the data to remove incomplete surveys. The survey had a completion

rate of 60%; however, this would have been higher if the survey links were not

put on online forums. Interestingly, an 85% completion rate was associated with

individuals who were invited to take the survey after watching this researcher’s

online presentation. Surveys which were 85% complete were left in the data set.

Next, the reliability of the data was checked for all the dependent

satisfaction variables and found to have a Cronbach Alpha of 0.91, the reliability

for the activity variables were found to have a Cronbach Alpha of 0.91.

All variables were measured on a single item scale so individual measures

of Cronbach could not be computed. Although this may reduce reliability, many of

the questions were thought to be so straight forward that repeating them would

annoy respondents, as well as, lengthen the survey time to an unreasonable 50 +

mins. The average time to complete this survey was 25 minutes with some

individuals taking up to 40 minutes. Nonetheless, the correlations in the following

section show some strong evidence of reliable data.

Next the respondent groups were compared amongst themselves using

Cronbach Alpha and some of the uncovered correlations. It was noted that

respondents who identified themselves solely as “support”, “researcher”, or

“advisors” introduced substantial error into the data set and greatly offset all of

the correlations, hence these groups were removed. If an individual selected any

of the following roles they were kept: project manager, division manager, R&D

manager, VP of R&D. Keep in mind an individual could be a “R&D manager” and

a “researcher” in which case their response was kept. This left 40 respondents

from the total sample of 60 completed surveys.

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It was determined that management responsibilities produced more

reliable responses than those individuals which were solely “support”,

“researcher”, or “advisors.” This is obviously due to the higher amount of

exposure and familiarity management has with the process when compared to a

line worker (like researchers, advisors, or support) who may be only exposed to

small parts of the process.

Unless otherwise noted all correlations in the following section were

found to have two tailed significances to 0.001, with the critical value for N=40

being 0.393. In most cases, the correlation R squared value was even above the

critical value of 0.393.

These author only considered correlations, of 0.6 or greater to be of

interest because, 1) 40 responses is a very small sample population of the

millions of businesses in existences, 2) this researcher wanted to avoid making

weak correlations which could lead to faulty conclusions, 3) many correlation

existed in the data between 0.4 to 0.6 and rationalizing each of these for such a

small sample size would be to cumbersome and most-likely unfruitful. This

researcher considered a correlation of 0.8 or above to be very strong, 0.64 to

0.8 to be strong, and 0.6 to 0.64 to be moderate.

A Pearson’s correlation calculation was used for all correlations.

Satisfaction items were converted to ordinal scales as shown in figure 5.2 and

denoted by a number followed by an S as such “#S.” Questions about the

frequency, amounts, or degree of an activity were converted to ordinal scales as

shown in figure 5.2 and denoted by a number preceded by a V as such “V#.”

Figure 5.2. Conversion of Answers from Likert to Ordinal Scales

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Please note many of the correlation sum one or more factors, this is a

simple procedure. For example, if a particular respondent answers “sometimes”

or 3 for V45 and “always” or 5 for V46, then the sum is 9. This calculation is then

computed for all respondents, and the resulting 1x40 matrix can be used in a

simple Pearson’s Correlation.

5.8. Survey: General Demographic Statistics for the Sample

The following section presents the demographics of the respondents who were

kept in the survey for analysis. IRB dictated that all companies and respondents

names be de-identified.

The respondent companies range greatly across several industries,

revenue size, employee size, but the vast majority seem to be located in the US,

with a majority in Ohio (see Figure 5.5). Figure 5.3 shows the distribution for the

respondents amongst their respective industries. Software and chemical seem to

have a large number, but the software & chemical companies varied greatly

within the sub-industry, hence, a very even distribution of company industries

was sampled.

Figure 5.4 shows respondent companies by both revenues and by number

of employees. The sample seems to bias larger revenue companies; whereas,

the number of employees seems to be bias toward companies larger than 501

and between 101-300 employees. Thus, this sample’s results should be strongly

applicable to large to mid size companies measured by number of employee and

revenues; however, it is unclear how applicable the results of the survey would

be to companies with less than 500K in revenue.

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Figure 5.3. Distribution of Respondents’ Companies amongst their Respective

Industries

Figure 5.4. Distribution of Respondent’s Companies by Revenues and Number of

Employees

Respondents' Industry Distribution N=40

1 1

6

1 1 1 12

12

1 1 1 1 1 1 1 1

6

21 1 1

2

01234567

Academic/university

Business Consulting

Chemicals

Consulting

Electronics

Energy

Finance

Healthcare

HVAC

Industrial Equipment

ITLaboratory Equipem

ent

Life Sciences

Manufacturing (Autom

otive, Aviation, Heavy Duty Construction eqpt.)

Marine

Office Products

Pow

er Generation

Publishing

Software

Software Consulting

Software Vendor

Telecom

Think Tank

Travel

Number of c

ompan

ies

sampled in

that in

dustry

Respondent Company Organized Revenues

1

2

3

4

5

6

7

8

0 2 4 6 8 10

less than $100K

$100K to $500K

$500K to $1M

$1M to $50 M

$50M to $500M

$500M to $1B

$1B to $5B

$5B +

# of Respondents

Respondent Company Organized # of Employees

5

4

1

9

2

4

3

9

0 2 4 6 8 10

1-20"

21-50

51-100

101-300

301-500

501-1000

1001-5000

5001+

# of Respondents

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Figure 5.5. Distribution of Respondent’s Companies by Locations

Aside from companies, the respondents were also analyzed on their

project responsibilities, company roles, and years of experience in that company.

Figure 5.6 shows the respondents organized by their roles, again the sample is

purposefully bias toward management.

Out of the respondents, 1 respondent managed one project, 24 managed

two or more projects, 14 managed one division, and 16 managed the whole

company (see appendix D). This again shows a purposeful bias toward

management responsibilities.

The average years of experience within their current company for

respondents were 6.03 years, with a standard deviation of 5.73 years, with one

respondent having 28 years experience. On the low end seven respondents had

2 years experience and six had 1 year of experience. Keep in mind this has no

relation to the actual years of experiences of the respondents.

Distribution of Respondents Country & States

21 1 1 1 1 1

32

3 3

7

1 1 1 1

3

1 1 1 12

1 1

012345678

Califorina

Idaho

Illinois

Iowa

Maryland

Massachusetts

Michigan

Missouri

New

Jersey

New

York

North Carolina

Ohio

Oregan

Texas

Virginia

Pennsylvania

UK

Spain

Norway

Italy

India

France

China

CanadaNumber of Compan

ies

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Figure 5.6. Respondents Organized by their Roles

5.8.1. Sample’s Relation to the Greater Population

No statistical tests have been conducted to determine this samples relation to the

greater population. Because the survey was promoted in conjunction with a web-

seminar on idea generation and idea management, it is thought that the vast

majority of the respondents were interested in this topic which may be due to: (1)

a need they see in their company for improvement in these areas, or (2) a

general interest in these subjects. Product development managers are typically

fairly busy and it is thought the first explanation may be the main reason for

taking this survey.

Hence, it is thought that the sample is bias toward respondents who see a

need for improvement in these given areas for their companies. However,

question 21S shows a normal distribution of satisfaction for respondents with

their overall idea generation process, suggesting no bias. But questions 51S to

56S suggest that respondents are more dissatisfied with their idea management

processes. Question V132 shows 85% of respondents are interested in learning

Respondent Roles for N = 40

1615

98 8

6 65

43 3 3

2

0 0 00

2

4

6

8

10

12

14

16

18

Project Manager

R&D manager

Advisor

Researcher

Chief Innovation Officer

VP of R&D

Consultant

Division Manager

Engineer

Developer

Supervisor

Assistance

Support

No Role

Technician

Minimal Role

Num

ber of Respondent w

ho selected that role

Note a respondents can select more than one Role. Also,respondents who solely selected "assistance", "support", or "Research" were removed from the data set.

256

more about this topic. This researcher is unsure if this sample is representative of

the greater populations, and would lean toward it representing individuals who

see a need for improvement in these areas in their companies and have a

general interest in this subject area.

5.9. Survey: Correlations between Satisfaction Variables

It would be helpful to start the discussion of the data obtained from the survey

with an analysis and discussion of the satisfaction variables. In this section the

dependent satisfaction variables were compared with each other to see if any

logical correlations could be developed. Figure 5.7 below shows that out of the

sixteen variables only one (61S) could not be correlated with the others.

Figure 5.7. Correlations of the Satisfaction Variables

5.9.1. Idea Generation

The first most important correlation found in this group was the correlation that

49S (Overall Satisfaction with the Idea Generation process) had with the sum of

factors 44S, 45S, 46S, 48S, 54S, shown in Figure 5.8.

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The correlation in Figure 5.8 was found to have a Pearson 0.833

significant to 0.01, and is of extreme interest because it encompasses 70% of the

variation in an individual’s overall satisfaction with their companies idea

generation process.

Figure 5.8. Correlation for Overall Satisfactions with the Idea Generation Process

This is a logical correlation because the quality, number of ideas, time to

generate ideas, and ability to generate a specific set of ideas are in sum the

major outcomes of the idea generation activities and should obviously be tightly

correlated with overall satisfaction with the idea generation process. The factors

of 54 (quality and amount of ideas in the idea bank) and 48 (the ability of idea

generation process to fill the front end portfolio) are also the result of the output

of idea generation process, and should also be tightly correlated with overall

satisfaction.

The true importance of this correlation is that a consultant can use a single

question (What is your overall satisfaction with your company’s idea generation

process?) to fairly accurately gauge an individual’s sum satisfaction with

important outputs of their company’s idea generation process.

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Figure 5.9. Correlation of V48 Ability to Fill Front End Portfolio

Figure 5.9 shows the correlation between the satisfaction of 48S (ability of

your company’s idea generation process to fill the front end portfolio needs) and

56S (the ability of your company’s idea bank to fill the front end portfolio’s needs)

to be 0.678 significant to 0.01. A high correlation is logical given they both relate

to the front end portfolio needs. The variation can be primarily attributed to the

difference between the “ideas” created from the idea generation process and the

“ideas” located in the idea bank (which also included ideas captured from outside

sources).

5.9.2. Idea Capture

Another impressive relationship is the strong 0.728 Pearson correlation between

51S (the satisfaction with the company’s ability to capture ideas from employees

at all levels) and the sum of (53S the company’s ability to store and organize

captured ideas, and 55S the company’s ability to distribute or route ideas across

the company), show in figure 5.10. The following hypothesis is offered to explain

this relationship.

As shown in the initial version of Glassman’s model (Figure 3.16),

capturing ideas comes before storing, organizing, and distributing ideas, yet they

are all connected in a continuous linear process. If any one part of the process

(capture, storing, organizing, or distributing) is inefficient, obviously the whole

idea management process will be inefficient. This is further back by all three

variables having strong correlations between each other of 0.61 or greater.

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This correlation can be used as supporting evidence for this researcher’s

idea management process as being linear.

Figure 5.10. Correlation of 51S Ability to Capture Ideas from Employees

The next correlation, which seems to be less useful, relates satisfaction

variable 52S (company’s ability to capture ideas from outsides sources) to the

sum of 49S (overall satisfaction) and 54S (quality and amount of ideas in the idea

bank), shown in figure 5.11. This moderate correlation (R2 = 36%) is less obvious

and may be rationalize by an innovation director being satisfied with ideas in his

idea bank, and thus being satisfied with his idea generation process and by their

ability to capture ideas from outside sources. Remember some confusion still

exists in the term “idea generation process” where many innovation practitioners

also take it to include many activities in idea management like “capturing ideas.”

Figure 5.11. Correlations of 52S Ability to Capture Ideas from Outside Sources

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5.9.3. Development Outcomes

Satisfaction variables dealing with development outcomes (58S, 59S, 60S) were

compared and found to have a strong correlation as shown in Figure 5.12. This is

an obvious correlation and just verifies that the survey is acting correctly. The

variation in this correlation can be attributed to the difference between comparing

a ratio and the ability to convert a single idea.

Figure 5.12. Correlation of Dependent Development Variables

Interestingly two unexpected correlations were noted as shown in figure

5.13. Given these correlations are moderate ones, one explanation is that an

innovation director is more satisfied with their development department’s use of

resources when they see their department can create a number of quality ideas

with these given resources.

Figure 5.13. Correlations with Company Resources

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5.10. Survey: Discussion of Correlations Between Satisfaction Variables and

Measures of Activities

The following section will discuss the correlations found between the dependent

satisfaction variables and the independent activity variables. The section will be

arranged by the descending order of activities as shown in the author’s proposed

model.

Figure 5.14. Correlations of Activities to Quality of Ideas Generated

The strongest and most significant correlation uncovered in this study is

0.851 Pearson R correlation shown in figure 5.14. The sum of the variables in the

left side of this correlation can be thought of as the “quality of the output from the

idea generation process.” A high quality idea generation process produces large

numbers of quality ideas for a specific purpose. Obviously, high quality ideas are

going to be stored in the idea bank as shown by 54S in the left side of Figure

5.14.

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The right side of this correlation shows several things. First it shows that

selection of creative people (which equate to selection of the source in

Glassman’s model) is an important factor in generating a quality output. Alone

V73 (selection of creative people) had the highest correlation (0.61 moderate)

with 47S (time to generation ideas). Again, this supports the author’s model.

Next, having, hosting, and managing events are very important in

generating a quality output. Alone V75 (actively holding events) had a 0.67

(strong) correlation with quality of ideas (44S) and a 0.6 (moderate) correlation

with (49S) overall satisfaction with the idea generation process, and a 0.59

correlation for both V45 & V47. This shows the importance of having formal

events to generate ideas. Actively managing these events V76 had a moderate

0.45 to 0.48 individual correlation with factors 44S, 45S, 47S, and a high

correlation (0.58) with 54S the amount and quality of idea in the idea bank.

The idea generation activities V80, V81, V82 together showed the highest

correlations to satisfaction variables 44S, 45S, 46S, 47S, 54S. What this says is

that selecting, managing, and providing tools & resources for idea generation

activities is the most important thing one can do to generate a number of quality

ideas. This is logical considering that these activities are the ones which actually

create the ideas. All 12 internal correlations between these variables had

correlations above 0.49 with the average being 0.6.

Out of this group V81 had the highest correlation to 45S of 0.75. This says

that managing the idea generation activities accounts is require to obtain a

satisfactory number of ideas (accounts for R2=56% of the outcome).

The importance of selecting, managing, and providing tools for idea

generation activities cannot be understated and should be central in ones efforts

to generating a number of qualities of ideas quickly.

Together the variables on the right of figure 5.14 have a strong 0.695

correlations with (49S) the overall satisfaction with the idea generation process.

This greatly supports that these activities are vital additions to Glassman’s

proposed model.

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Figure 5.15. Correlation 0.851 Comparison with Model

The right hand side of Figure 5.14 shows that those activities are highly

interrelated. Thankfully, this strongly supports the author’s proposed model for

idea generation shown in Figure 5.15 as having these activities occurring in an

interrelated linear process. Again, the linear process is the only one which makes

sense as discussed in Chapter 3, development of a control model.

Unfortunately, several points of control shown in Figure 5.15 were not

tested for in the survey due to length requirements. Interestingly, providing

incentives for events showed no notable correlations, but providing a general

incentive for submitting ideas created a 0.53 correlation with 44S (satisfaction

with quality of ideas), and a weak 0.48 correlation with 45S (satisfaction with

number of ideas). This provides weak support, but support Nonetheless for

incentives in Glassman’s proposed model.

Amazingly, screening in Glassman’s model showed no notable

correlations with the variable on the left of Figure 5.15. Later in this section, one

will see that screening plays an important role in idea management. Hence, one

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can tentatively conclude that screening activities must be removed from idea

generation and placed in the idea management part of Glassman’s proposed

model.

Satisfaction with the ability of their company's idea generation process to

fill the front end portfolio's needs (48S) at best had a weak correlation 0.58 with

V75 the degree to which one actively holds events. The low correlations that

(48S) has to other satisfaction variables is weird and un-explained considering in

figure 5.9 it helps the correlation with overall satisfaction.

Again the resulting correlations developed from the survey, show strong

support for the points of control proposed in the author’s idea generation model.

5.10.1. Correlations for the Idea Management Process

5.10.1.1. Capturing and Screening Ideas

The next set of correlations are those dealing with the activities described under

idea management, starting with capturing of ideas from employees.

Figure 5.16. Weak Correlation for Capturing Ideas from Employees

It was thought that 51S, satisfaction with capturing ideas from employees,

would have correlated strongly with V88, the degree by which their company

accepts ideas submitted from, or by observing employees, see Figure 5.16. In

reviewing the data it was found that several activities combined together created

a very strong correlation with 51S, as shown in Figure 5.17.

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The correlation shown in Figure 5.17 displays a strong relationship

between 51S and the ten activities on the right which were clumped into similar

groups. The screening activities all had individual correlations of 0.5 with V85

having a 0.55 correlation with 51S. This says, that screening is important part of

capturing ideas from employees.

Next, the capturing activities, V88, V98, V104, V105, had correlations of

0.433, 0.59, 0.56, 0.60 with 51S, respectively. It was interesting that V98

(capturing ideas from media) correlated with 51S. Consider this, the only ways

ideas are captured from magazines or media source are if employees read or

watch them, then submit the ideas. Given this, one can deduce that to be better

at capturing ideas from media sources, they must be effective at capturing idea

from employees.

Figure 5.17. Strong Correlation for Capturing Ideas from Employees

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Interestingly, V105 (actively managing capture from outsides sources)

increased satisfaction with capturing ideas from employees. This may be

because companies which are effective at capturing ideas from employees are

also effective at capturing ideas from outside sources? Or this may be because,

the respondents considered many of the ideas captured from outsides sources

(like media sources) to be observed and submitted by employees. Nonetheless,

the strength of this correlation (0.60) suggests that companies should also

actively manage the capture of ideas from outsides sources in their efforts to

capture ideas from employees.

Finally, idea management activities being V114 (actively managing the

system for storing ideas), V115 (degree of formality of this system), and V116

(use of idea management software) have individual correlations with 51S of 0.58,

0.51, 0.64, respectively. Obviously, actively managing the system for storing

ideas is important. But it was surprising for V115 that a more formal system for

capturing ideas increased satisfaction. During the case studies, this researcher

learned that employees (especially at large companies) are often confused about

how to submit ideas, so clearly having a more formal system reduces this

confusion. In hindsight this is logical because the more formal the system is the

more employees would be aware, and knowledgeable in how to submit ideas.

As was mentioned in the conclusions of the case studies, the idea

management process is highly logistical and idea management software are

ideal for dealing with high volumes of ideas, and the strong 0.64 correlation

shows this. As well, idea management software are really tailored toward

capturing ideas from employees.

Most importantly, the strong correlations in figure 5.17 provide support for

the importance of the management activities described in Glassman’s model for

idea management. In particular the activities of: screening, capturing, storing,

and organizing ideas were shown to be interdependent. As mentioned in chapter

3, only a linear process makes sense for these activities.

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Figure 5.18. Correlation for Capturing Ideas from Outsides Sources

Figure 5.18 shows a very strong correlation for capturing ideas from

outside sources relating to the sum of the five variable V123, V125, V126, V127,

V128, having individual correlations of 0.62, 0.58, 0.63, 0.66, 0.71 with 52S,

respectively. This correlation validity is further backed by the correlations shown

in Figure 5.10.

It seems that refining the process using outputted ideas, is important in the

satisfaction with capturing ideas from outside source, this can be due to

companies needing to adjust the selection and method of capturing ideas from

outsides sources to optimize the process.

Interestingly, diffusion is vitally important in satisfaction with capturing

ideas from outsides sources. One idea for its importance is the innovation

director’s satisfaction when employees receive and proposed ideas from outside

sources. Obviously, employees would mainly receive ideas from the idea bank or

be routed the ideas. In fact, routing ideas had the highest individual correlation of

0.71 with 52S.

Another thought for its importance is because the innovation director, or

product development managers mainly see the end results of capturing ideas

from outside sources being the diffusion activities, and they attributed much

satisfaction to the quality of those visible activities, placing less weight on the

screening, capturing, and storing activities.

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Yet another explanation for this correlation may be this. In some

companies employees are responsible for capturing ideas from outsides sources,

and if they notice that higher quality ideas in the idea bank are coming from

outside sources they may be more inclined to tap those outside sources for ideas

in the future.

Regardless of these correlations, this researcher still feels that capturing

ideas from outside sources is only efficient when the whole idea management

process is effective. Further this researcher feels that variable 52S “satisfaction

with capturing ideas from outsides sources” as measured does not reflect

accurately the actual effectiveness of capturing ideas from outsides sources.

5.10.1.2. Tagging Ideas

Moving on, one correlation was found for tagging ideas of 51S (satisfaction with

capturing ideas from employees) and V107 (who submitted the idea) of 0.465.

Obviously innovation directors are going to be satisfied with capturing ideas from

employees when they no who submitted them. The fact that no other tagging

activities had correlation should not detract from the importance of this activity.

Again, when new practices are recommended they are usually not practiced and

this was very much the fact with tagging (see Section 5.12.2 for details on

tagging).

Very few companies practiced recording tag info other than who created

an idea. So it is no surprise that there was no correlation found for the tagging

activities. Nonetheless, this researcher still feels that tagging is a vital and easy

to perform activity, which gains great importance as process checks are

conducted.

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5.10.1.3. Storing & Categorizing Ideas

Figure 5.19. Correlation for Storing and Capturing Ideas

There were substantial correlations found for storing of ideas in figures

5.15. Outside of that, figure 5.19 shows a moderate correlation between 53S and

V114 and V122. Alone, V114 correlated to 53S with a 0.61 Pearson which can

be obviously explained by increase quality associated with increase management

activity. Interestingly, there was no notable correlation found between 53S and

V115 degree of formality of this system. This researcher thought there would be

a strong correlation, but in review this lack of correlation may be due to small

companies not needing a formal system for storage. A weak 0.5 correlation was

found for this correlation using only large companies (more than 500 employees),

thus this researcher is unsure how formality alone affects satisfaction with storing

and categorizing ideas.

5.10.1.4. Process Check Activities

Process check was found to be important in figure 5.19 as well, in figure

5.20 below. The rational for this correlation was already mentioned to be due to a

innovation director needing to review the ideas to see which outside sources are

producing ideas.

Figure 5.20. Correlation for Process Improvement

53S. Satisfaction with Storing & Categorizing Ideas V122. How often does your company

refine the idea generation process?

V114. To what degree does your company actively manage the system for storing ideas?

Pearson 0.648

R2=0.41

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5.10.1.5. Diffusion Activities

Satisfaction with diffusion was correlated to activities shown in table 5.7. Out of

these the V114 (degree to which a company actively manages the system for

storing ideas) had a weak 0.493 correlation, saying that 25% of the satisfaction is

due to this activity. Amazingly, all diffusion activities had poor or no correlations

with 55S; therefore, this result cannot be explained. Again Figure 5.18 shows the

diffusion activities related to satisfaction with capturing ideas from outsides

sources.

Otherwise, V127 (exposing employees to ideas from the idea bank)

showed the highest but weak correlation with 56S. Rationalizing this, one would

say that more new product projects can be made if employees are exposed more

to ideas from the idea bank.

The weak correlation developed for diffusion activities, except for that of

Figure 5.18, seem to understate the importance of these activities. Again, idea

management is a linear process and it makes very little sense to be efficient in

the rest of the process yet be poor in diffusion. As well, the literature review on

diffusion in this dissertation stresses the importance of these activities.

There seems to be some weak correlation between 54S (quality and

amount of ideas in idea bank) and V126 (staff referring to idea bank), V127

(exposing employees to ideas from idea bank), and V128 (routing ideas to

employees), as shown in Table 5.7. Again, the more employees are exposed to

ideas the higher the chance that ideas are created serendipitously. As well, many

idea generation activities (like IDEO process) recommends that employees to

review the idea bank prior to participating in idea generation activities. Hence,

these correlations follow predicted logic.

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Table 5.7. Correlation for Diffusion Activities

54S. The amount, quality, type of ideas in your company s idea bank or idea pool?

55S. How satisfied are you with your company s ability to distribute or route ideas across the organization?

56S. The ability of your company's idea bank to fill the front end portfolio's needs?

V114To what degree does your company actively manage the system for storing ideas? 0.400 0.493 0.351

V122How often does your company refine the idea generation process? 0.402 0.426 0.418

V123

How much does your company use the outputted ideas to refine the idea generation process? 0.382 0.188 0.349

V125

How frequently does your company’s employees search the idea bank when they need new ideas? 0.280 0.357 0.381

V126

How frequently does your product development staff refer to or search the idea bank during idea gene... 0.422 0.208 0.432

V127

To what degree does your company actively expose its’ employees to ideas from the idea bank? 0.519 0.354 0.523

V128

To what degree does your company actively route particular newly submitted ideas to the employees wh... 0.547 0.287 0.412

5.10.1.6. Development Activities

As an additional measure the survey tested satisfaction with respect to four

development activities. Out of these only one 60S (satisfaction with their

company’s ability to convert an idea into a marketable product) was found to

have a moderate correlation of 0.6 to V126 (a diffusion activity) as shown in

figure 5.21. It does not make sense that later development activities are

improved by referring to the idea bank. Instead, one can hypothesize those

employees which refer to the idea bank more, purposefully create ideas that are

more in line with the needs of the company and create ideas which have higher

chance making it to market launch. The other two correlations shown in figure

5.21 support this thought.

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Figure 5.21. Correlation for Development Activities

5.10.1.7. Idea Management Software

Idea management software is an upcoming tool to aid idea management, and

again, this researcher’s case studies concluded that idea management software

is almost necessary for companies with large number of employees. Table 5.8,

shows the correlation that the use of idea generation has to levels of satisfaction.

Table 5.8. Correlations for Idea Management Software

51S

How satisfied are you with:Your company s ability to capture ideas from employees at all levels? 0.643 strong correlation

52S

Your company s ability to capture ideas from outside sources like competitors, suppliers, consultant... 0.389 No correlation

53SYour company’s ability to store and organize captured ideas? 0.293 No correlation

54SThe amount, quality, type of ideas in your company s idea bank or idea pool? 0.268 No correlation

55SYour company s ability to distribute or route ideas across the organization? 0.203 No correlation

58S

How satisfied are you with: The development outcomes of ideas that enter into your pipeline? 0.105 No correlation

49SOverall idea generation process of your company? 0.092 No correlation

60SYour company s ability to convert an idea into a marketable product or service? 0.084 No correlation

56SThe ability of your company's idea bank to fill the front end portfolio's needs? 0.047 No correlation

61S

Your company s ability to use resources during development in an effective manner? -0.013 No correlation

59S

The ratio of ideas that make it through to market launch? -0.025 No correlation

V116. To what degree does your company: Use Idea management software for storage?

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Again, Idea management software’s main goal is to capture ideas from

employees and hence that correlation 0.643 supports that point.

Interestingly, the use of idea management software did not correlate with

any other activities. Now, this is by no means conclusive, because idea

management software is evolving greatly in effectiveness and functionality, even

over the last year (2008). It is totally reasonable not to see any correlations with

idea management software until they gain wider market acceptance, and have a

common level of functionality. Keep in mind not all idea management software

have the same functionality, some companies even used Microsoft SharePoint

which is a knowledge management program, and claim it to be their idea

management software, which in reality it is not! From this one can conclude that

the correlations in table 5.8 can be deemed totally inaccurate for future

reference.

This researcher sees much potential in the use of idea management

software to formalize and stream line the idea management process. But again,

one should understand the process before using a tool to manage it.

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5.11. Survey: Discussion of Support for Proposed Model

Table 5.9. Support Found for the Author’s Proposed Model

Level of Support Figures or Table location of supporting correlation

Supporting Activity Question

Screening ideasMethod of screening (input) Strong 5.15 84Attributes of the screen (input) Strong 5.15 85Execution of screening (process) Strong 5.15 86

Capturing IdeasMethod of Capture (input) Strong 5.15 116Sources of Capture (input) Strong 5.15 88,98,104Execution of capture (process) Strong 5.15 105

Tagging Method of Tagging (input) Not Tested for in surveyAttribute of the Tag (input) Weak 107Execution of Tagging (process) Weak 107

Storage and CategorizationMethod of Storage & Categorization (input) Strong 5.15 115, 116Execution of Storage & Categorization (process) Strong 5.15 114

Process Check Methods of Process Check (input) Strong 5.16, Table 5.7 122, 123People performing the Process Check (input) Not Tested for in surveyExecution of Process Check (process) Strong 5.17 122, 123

Diffusion Methods of Diffusion & Routing (input) Strong 5.16, Table 5.7 127People executing diffusion & routing (input) Not Tested for in surveyExecution of Diffusion & Routing Strong 5.16, Table 5.7 125,126,127,128

Support found for points of control in the author's proposed I-Gen model (Idea Management part of model only)

Table 5.9 compiles the support for the points of control in Glassman’s

model. One can see that all points of control but the tagging had strong support.

To reiterate, this researcher feels that the lack of proper tagging is a systemic

error in the practices of companies that will be remedied when these companies

start doing detailed process checks.

One can also see in table 5.9 that several points of control were not tested

in the survey. This was done because these questions were either too redundant

to ask, not important enough to be asked, or could not be formulated. Methods of

tagging seem not important enough to ask because it was based on the way

which idea were recorded. It was difficult to formulate a question regarding the

“people performing the process check” and “people performing diffusion or

routing” because this researcher was unclear if he wanted frequency, selection,

or the role of these individuals.

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In all the supporting correlations discussed in this section lend great

validity to the authors proposed idea management model. Combining this with

the support for the points of control listed in figure 5.15, the combined model of

idea generation and idea management is well supported.

5.12. Survey: Discussion of Normative Results

The results for all of the questions of the survey were summarized in graphic

form and are displayed in Appendix D, so please refer to it often while reading

this section.

For the satisfaction questions a higher “mean” resulted in higher

dissatisfaction and for the activity questions a higher “mean” resulted in higher

frequency, of amount of that activity occurring. Very few of the questions had

normal distribution of answers (44S, 47S, 54S, V115), the bulk of the questions

were double humped or skewed left or right with a few having flat distributions.

For the sake of brevity, the most interesting findings will be discussed below.

5.12.1. Normative Results for Satisfaction Questions

Out of all the questions dealing with satisfaction with idea generation outputs only

questions 46S had a high skew where 49% of the respondents were satisfied

with their company’s ability to generate a set of ideas with a specific set of

attributes. Most of the questions had slight double distributions with only 45S,

46S having right skews towards being more satisfied.

Three of the questions for dealing with satisfaction with idea

management’s outputs produced interesting results. Question 52S showed that

51% were satisfied or very satisfied with capturing ideas from outside sources.

Yet the activity questions V63-V72, & V87-V97, shows that most companies did a

poor job of tapping a variety of outside sources for ideas. One may hypothesize

that (1) respondents only need to tap a small number of sources to be satisfied,

or *2) respondents are not aware of the number of outside sources and outside

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ideas they are missing, and thus are content. The second hypotheses would also

explain why the activities associated with capturing ideas from outsides sources

are missing Figure 5.18.

Question 53S shows a hard skew to the left with 48% dissatisfied and

53% very dissatisfied or dissatisfied with their company’s ability to store and

organize captured ideas. Obviously, the respondents in this sample have a

systemic problem with storing and organizing ideas.

Question 55S shows a light skew to the left with 43% being very

dissatisfied or dissatisfied with their companies’ ability to distribute or route ideas

across the company. This may be part of the reason why no strong correlations

were found (outside of Figure 5.18) with diffusion activities.

Question 58S showed that 51% of respondents were satisfied or very

satisfied with the development outcomes of the ideas that enter their pipeline.

This shows that the sample is from companies which, on the majority, are

effective at developing products.

5.12.2. Normative Results for Activity Questions

Moving on to activities, question V75 showed that the bulk of the respondents

(79%) did not frequently hold events to generate ideas, where only 4

respondents (10%) always held events to generate ideas, and to that questions

V76 showed that 61% of the respondents undermanaged these events.

Not hosting and managing events is a systemic problem in this sample,

and should be improved upon because the correlations in Figures 5.12, showed

that holding and managing events is vital factor in generation a number of quality

ideas.

Another systemic problem was found in V77 and V78 in the lack of

incentives across all respondents. It seems companies go cheap, and expect

employees who often have other major responsibilities outside of generating

ideas, to take the time and generate and submit ideas. Incentive theory showed

that for employees to make something a priority they must be incentivized rightly.

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Questions V80, V81, V82 highlight that the bulk of the respondents do not

select the idea generation activities, manage them or provide adequate

resources and tools to these activities. Once more the correlation shown in

Figure 5.14 highlights that this is a major error!

Screening shown in question V84 is one of those simple activities which

every company seems to do, again this is only a minor part of the whole process.

Amazingly, there is a flat distribution in responses amongst V85 setting the

attributes for the first screen and V86 managing the first screens.

Questions V87 to V97, and V63 to V72 show that outside sources like:

customers, partners, and the media sources are often tapped for ideas; while,

universities, external research labs, suppliers, consultants, indirect competitors,

and independent inventors are much less frequently tapped for ideas. Open

innovation experts should take note of these graphs for these questions because

it lends them much support. Obviously, companies should be frequently tapping

all sources for ideas.

Question V100-V103 shows that an “individual” and “email” is the most

prevalent form of capturing ideas, followed by suggestion boxes and voice mail,

and lastly idea management software. Using an individual to capture ideas is

very acceptable as long as they are trained in how to apply the screens

appropriately.

Questions V107-V110 showed a systemic problem with tagging, that

although respondents are recording who submitted the ideas, they are failing to

record other via tag information. As mentioned, this researcher believes this will

change when more rigorous process checks are adopted, and responses in

question V122, V123 show that only 5 respondents frequently perform process

checks.

Diffusion of ideas seems to be practiced poorly amongst the respondent

companies as shown by questions V125, V126, V127. Out of these activities

routing V127 had the highest mean of 3.28 with 36% of the respondent “always”

or “most-of-the-time” routing ideas to employees. This hints at possible systemic

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problem with routing and diffusion which may be due to the lack of importance

placed on this activity in the literature. Nevertheless, the correlation in figure 5.18

and correlations in table 5.7 state the importance of diffusion activities.

5.13. Survey: Major Lessons Learned

There were several major lessons learned from conducting the survey research

study. The first and most important lesson was that most of the correlations and

normative data supported Glassman’s model for idea generation and idea

management. Once more, table 5.9 and figure 5.15 showed a summary of

support for the model. This helps to answer the second research question

further. Combined with the case studies there is substantial evidence that the

proposed model will be effective in managing and controlling the idea generation

and idea management processes.

The second major lesson was that screening activities are really

considered by respondents to be part of the idea management process. This

lesson is applied in the following chapter 5 Updated Control Models.

The third major lesson is the importance of people, events, and idea

generation activities in creating a number of quality ideas in a timely fashion. This

lesson was highlighted in detail in the discussion surrounding figure 5.14.

Unfortunately, the normative data in appendix D showed that a majority of the

respondents did not host or manage idea generation activities correctly.

The forth major lesson is how satisfaction with capturing ideas from

employees is greatly affected by the screening, capturing, and storing activities,

see the discussion surrounding figure 5.17. The fifth major lesson is how

satisfaction with capturing ideas from outside sources depended highly on

diffusion activities as shown by figures 5.18 and table 5.7.

The last major lesson was the systemic dissatisfaction with: capturing

ideas from outside sources, storing and categorizing of ideas, and diffusion and

routing of ideas, amongst the respondents. Yet again, this may hint at a larger

systemic issue with these items for the greater population.

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CHAPTER 6. UPDATED CONTROL MODELS

This very short chapter presents improvements made to the proposed Glassman

model based on lessons learned from the case studies and survey study.

Appending to this model is believed to strengthen it further, and lend it additional

creditability as being an effective means of controlling the idea generation and

idea management processes. The improvements to the model will be discussed

sequentially.

6.1. Screening Moved into Idea Management

The first improvement to this model was the movement of screening activities

into the idea management portion of the model. Section 3.28 discusses

screening in detail but fails to mention that most of the screening occurs during

the capturing of ideas, in addition, to screening occurring during idea generation.

The importance of screening as part of the idea management process was

established from the very strong correlation in Figure 5.17, in which all three acts

of screening V84 (degree to which a company does screening), V85 (setting the

attributes for the screen), and V86 (actively managing the screen) had 0.5 or

better correlations with 51S (satisfaction with capturing ideas from employees).

Screening is an activity which all respondents of the survey seemed to

understand and perform (V84), yet actively managing the screen (V86) and

setting the attributes for the first screen (V85) were not as well performed with

only 43% respondents “most-the-time” or “always” performing these activities.

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To keep an emphasize on screening activities they will be separated from

capturing activities, even though in practice they can be conducted at the same

instance. For example, an innovation director would capture an idea via a phone

call and be simultaneously screening it.

Screens can be applied before capturing, in which case it prevents certain

types of ideas from being submitted. Or screening can be practiced after

capturing in which case it prevents ideas from being stored. Out of the two

options, this researcher feels it is much worse to inhibit the capturing of ideas via

a pre-screen.

The rationality for this is simple; (1) there is very little harm in capturing a

poor idea then screening it out later, (2) it gives one the option to screen a

potentially valuable idea, and (3) it allows the employee or outside individual to

feel satisfied with their aid, and (4) it allows the screen to be malleable and post-

adjusted to allow potential great ideas (which may initially not meet the first

screen) to be captured.

The harm in having the screen before capture is (1) significant loss of

revenues and competitive advantage associated with screening out good or great

ideas, (2) it is difficult to tell if the screen is eliminating good or bad ideas, and (3)

the de-motivating effects a pre-screen would have on employee or outside

sources who would like to submit an idea.

For these reasons, screening was put after capturing in the updated

management model. Once more, individuals applying a screen should be trained

in how to apply it correctly and how to avoid de-motivate individuals while

screening ideas.

6.2. Strategic Alignment Activities

The case studies clearly demonstrated that the idea generation process requires

strategic alignment to focus its outputs; whereas, the idea management process

is purely logistical. Given this, the idea generation part of the model was

appended to include four activities designed to align the outputs of the idea

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generation process with the company’s strategic needs, and they are: (1)

reviewing the company strategy, (2) determining major areas which ideas should

be generated for based on the strategy, (3) confirming these areas, and (4)

aligning the process.

During strategic reviews companies often identify opportunity areas, areas

of strategic importance, or general areas to grow business. These strategic

initiatives are often dedicated much resources and are hopefully well thought out.

Focusing the outputs of the idea generation process toward meeting these

strategic needs is only smart. Having an idea generation process which

generates random ideas which may or may not meet strategic needs can be a

major waste of resources, and unfortunately produce great dissatisfaction with

the idea generation process.

The first activity (strategic review) should be performed by the innovation

director, VP of R&D, or chief innovation officer. Next these individuals should

determine the major areas which idea should be generated for, then these areas

should be confirmed.

The act of confirming an area can be the same as confirming an

opportunity area, but in many cases it is more high level. For example, say a

bedding company has selected bed liners to be an area to generate ideas for

because this is a major weakness of their competitors and this can be a way to

gain market share. The company would then look at that area and determine if

there is suitable room to generate ideas.

In the case of Fairbank’s Scales, one learned that their market of industrial

scales was highly mature, highly saturated, and contained limited number of new

product opportunities. Even the best idea generation activities would have had

much trouble generating ideas under these circumstances.

Interestingly, there seems to be this unspoken notion that smart

individuals or geniuses can create great ideas no matter how old or saturated the

market is, this is simply not true. This researcher has seen brilliant individuals

and even geniuses’ stall in their efforts to generate ideas for super saturated

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markets. Further, some markets just do not need new category of products, or

new functionality because the current offering, as segmented as they are, come

close to totally satisfying the needs of their customers, and short of creating a

blue ocean market nothing of real consequent can be introduce. Remember, the

purpose of a market is to satisfy the needs of that segment of customers, and

there is only so much one can do to create demand, outside of that additional

efforts would result in a waste of money.

So during the third step of confirming an area, one should take an honest

look and determine if the selected area has room to generate and introduce new

products or services. Remember, choosing incorrectly could completely stall the

idea generation process. Conversely; keep in mind that for some opportunity

areas, customers may be satisfied with the current product offerings until a new

disruptive product arrives and shows there is much room for improvement. An

example of this is the recent improvement in windshield wipers where they are

now one solid piece, and the advancement of tube televisions to LCD flat panel

televisions.

Once the areas are confirmed, the idea generation process can then be

aligned and adapted towards generating ideas for those areas. The

understanding of which areas to generate ideas for would then be used to select

amongst the many input controls to focus the process on which people, events,

idea generation activities, or screens to select. The process controls are used to

continually insure that the idea generation process is creating ideas for those

areas.

The appropriate employees must be selected for (1) reviewing the

company strategy, (2) selecting areas to generate ideas for, and (3) confirming

these areas. Most-likely a VP of R&D, innovation director, or Chief innovation

officer is appropriate for these tasks. A different set of people can be used to

perform the forth task of aligning the idea generation process. In addition, tasks 1

to 3 must be executed correctly (process control).

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6.3. Final Version of the Glassman Control Model

Idea Generation Processes (External or Internal)

Idea Management & Idea Banks (Internal)

Event

Source AKA

People

Ideas Ideas

Capture

Diffusion & Routing

Opportunity

Process Check

Tagging

Idea Generation Activities

The source

The Event

Idea GenerationActivities

Capture

Tagging

Storing & categorizing

Diffusion & Routing

Process Check

Selecting the sources (input) General incentive (input)

Event timing (input) Promotion (process) Event Execution (process)

Selection & combination of activities (input and process) Execution of activities (process)Tool & Resources (process) Environment (process)

Method of screening (input)Attributes of the screen (input)Execution of screening (process)

Method of Capture (input)Sources of Capture (input)Execution of capture (process)

Method of Tagging (input)Attribute of the Tag (input)Execution of Tagging (process)

Method of Storage & Categorization (input)Execution of Storage & Categorization (process)

Methods of Process Check (input)People performing the Process Check (input)Execution of Process Check (process)

Methods of Diffusion & Routing (input)People executing diffusion & routing (input)Incentives (input)Execution of Diffusion & Routing

Screening and Filtering

Storage & Categorization

Process check needed to tune idea generation

Using ideas as stimuli for idea generation activities

Major Activity Points of control over that major activity

Late FFE Activities (or NPD process)

Screen and filter

Strategic Aligment

1. Review Strategy2. Select General Areas to Generate Ideas for3. Confirm Areas4. Align Idea Generation Process Inputs

Figure 6.1. Updated Glassman Model

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APPENDICES

301

Appendix A. Concept Life Cycle

By C. Merle Crawford in New Product Management 5th Ed

Opportunity concept – a company skill, or resource, or a customer problem

Idea concept – The first appearance of an idea

Stated concept – a form or a technology, plus a clear statement of benefit

Test concept – it has passed an end user concept test, needs have been

confirmed

Full screened concept – tested and found to fit with the company’s situation

Protocol concept – a statement (product definition) of the intended user,

including the perceived problem, the benefit to users

Prototype concept – a tentative physical product or system, including features

and benefits

Batch concept – first full test of fit with manufacturing, specs are written, on

what product features will be along with their characteristics and standards

Process concept – the full manufacturing process is complete designed

Pilot concept – passes a pilot production run where the product is produced in a

small quantity and used with a small test group of users

Market concept – increased to full levels of productions

Successful concept – it meets the goal set for it at the start of the project.

302

Appendix B. Details of Stage Gate Process

Appendix B: Table showing the tasks and activities in each stage of the stage-

gate processes

Adapted from Borja de Mozota (2003)

303

Appendix C. Survey Instrument

V1 Welcome to a Research Survey on Idea Generation and Idea

Management held by Brian Glassman a Ph.D student in Innovation Management

at Purdue University, and distributed by Ryma Technology Solutions

V2-V9 This survey was designed to obtain data on current management

practices in idea generation and idea management, and is expected to directly

benefit respondents.

Here are the benefits of the survey:

1. It is a valuable self-assessment of your company's idea generation and

idea management processes. A similar assessment would cost $5K +

from a consultant

2. It will roughly show the respondents where they strong or weak in

controlling their idea generation and idea management processes.

3. It will give the respondents new ideas about how to improve their own

idea generation practices.

4. All publications, white papers, and learning’s will be email to

respondents who provide their email addresses.

V 10 This survey will take 25 mins, so please set aside sometime, or remember

to come back to when you have time. We feel this survey will be beneficial

so please strongly consider taking it. Thanks

V11 I have read and understand the terms of the information sheet and the

purpose of this study. (Html link to information sheet ) (Yes to continue)

V12 I consent to participating in this study. (Yes to continue)

304

Demographic Questions

V13 Name (optional) _________ (not disclosed)

V14 Email (optional) _________ (not disclosed)

V15 Company’s name _________ (not disclosed)

V16 Please enter the position & title you hold at your company? ________

V17 Please enter the department or functional areas you work for? ________

V18 Please enter the department or major functional area you work for? _____

V19-V33 What role do you play in your company's innovation process?

check all that apply: (No role) (project manager) (support) (technician) (division manager)

(R&D manager) (engineer) (researcher) (developer) (VP of R&D) (chief innovation officer)

(advisor) (minimal role) (supervisor) (assistance) (consultant)

V34 What part of your company’s new product or new service development

process do you manage?

(None) (1 project) (2 or more project) (One division) (The whole company’s)

Company’s Demographic Information

V37 What are the approximate revenues of your company this year?

(>100K) (100K to 500K) (500K to 1M) (50M to 500M) (500M to 1B) (1B to 5B) (5B +)

V38 What is the number of employees in your company?

(1-20) (21-50) (51-100) (101-300) (301- 500) (501-1000) (1001-5000) (5001+)

V39 What specific industry or service sector does your company operate in?

V40 What city & state is your branch of the company operating in?

V41 What is the approximate R&D budget of your company this year?

305

All of the following satisfaction questions use the following scale

(Very Dissatisfied) (Dissatisfied) (Neutral) (Satisfied) (Very Satisfied) (Do not know) (NA)

Satisfaction with Idea Generation

How satisfied are you with the:

44S Quality of the ideas produced from your company’s idea generation

process?

45S Number of ideas produced from your company’s idea generation process?

46S Ability of your company to generate a set of ideas with a specific set of

attributes? An example of this is creating ideas for a specific market, or product

ideas that can create at least 1 million in revenue and be implemented in six

months.

47S Time it takes to generate ideas?

48S Ability of your company's idea generation process to fill the front end

portfolio's needs?

49S Overall the idea generation process of your company?

Satisfaction with Idea Management

How satisfied are you with:

51S Your company’s ability to capture ideas from employees at all levels?

52S Your company’s ability to capture ideas from outside sources like

competitors, suppliers, consultants, customers, and partners?

53S Your company’s ability to store and organize captured ideas?

54S The amount, quality, & type of ideas in your company’s idea bank or idea

pool?

55S Your company’s ability to distribute or route ideas across the

organization?

56S The ability of your company's idea bank to fill the front end portfolio's

needs?

306

Satisfaction with Development

How satisfied are you with:

58S The development outcomes of ideas that enter into your pipeline?

59S The ratio of ideas that make it through to market launch?

60S Your company’s ability to convert an idea into a marketable product or

service?

61S Your company’s ability to use resources during development in an

effective manner?

Activity Questions

All of the following activity questions use the following multi-chose scale

(Never) (Rarely) (Sometimes) (Most-of-the-time) (Always) (Do not know) (NA)

Idea Generation Process Points of Control

Sources of Ideas

How frequently does your company:

V63-V72 Actively select the following groups to participate in generating ideas?

V63 Employees

V64 Customers

V65 Universities

V66 External Research Labs

V67 Suppliers

V68 Consultants

V69 Partners/Alliances

V70 Direct competitors

V71 In-direct competitors

V72 Independent Inventors

V73 Actively select participants for idea generation based on their level of

creativity or previous success in generating ideas?

307

Event Questions

To what degree does your company:

V75 Actively hold events to generate ideas? For example, idea competitions,

ideas fairs, idea campaigns, & formal requests?

V76 Actively manage these events?

V77 Provide incentives specific to these events?

V78 Provide general incentives for generating ideas? (For example a patenting

bonuses)

Idea Generation Activities

To what degree does your company:

V80 Actively select the type and mix of activities use to generate ideas.

V81 Actively manage the idea generation activities?

V82 Provide tools and resources specifically for idea generation activities?

Screening and Filtering

To what degree does your company:

V84 Screen newly submitted ideas prior to storing them, in say an idea bank?

V85 Set the attributes of the first screening for newly submitted ideas?

V86 Actively manage the first screen and filter to insure the screen is applied

correctly?

308

Capturing Ideas

To what degree does your company:

V88-V98 Accept ideas submitted from, or capture ideas by observing the

following groups?

V88 Employees

V89 Customers

V90 Universities

V91 External Research Labs

V92 Suppliers

V93 Consultants

V94 Partners/Alliances

V95 Direct competitors

V96 In-direct competitors

V97 Independent Inventors

V98 Media (magazines, publications, trade journals)

V99 Use the following methods to capturing ideas from internal or external

sources?

V99 Idea management software

V100 Idea suggestion box

V101 Particular person for capturing ideas

V102 Email

V103 Voice mail

V104 Actively manage the capturing of ideas from employees?

V105 Actively manage the capturing of ideas from outside source?

309

Tagging Ideas

V107-V112 To what degree does your company record the following

information when a new idea is submitted?

V107 Who submitted it,

V108 How it was created,

V109 What event triggered it,

V110 What activities lead to its creation

V111 Who was involved in its creation

V112 If it was created formally or Informally

Storage and Categorization of Ideas

To what degree does your company:

V115 Have a formal system for storing ideas?

V116 Actively manage the system for storing ideas?

V117 Use of the following idea storage systems

V117 Idea management software

V118 Idea data bank

V119 Idea data bank (print or physical form)

V120 Categorize ideas in the idea bank?

Process Check & Process Improvement

V122 How often do you refine the idea generation process?

V123 How much do you use the outputted ideas to refine idea generation

process?

310

Diffusing and Routing of Ideas

V125 How frequently does your product development staff refer to /search the

idea bank during idea generation activities?

V126 How frequently do your company’s employees search to the idea bank?

V127 To what degree does your company expose its’ employees to ideas from

the idea bank?

V128 How frequently do your company’s actively route particular newly

submitted ideas to the individuals who could best use them? (For example

sending a new idea about a consumer product submitted by a customer to the

consumer product director)

V132 Would you like to learn more about how to conduct and manage the idea

generation and idea management? (Yes or No)

311

Appendix D. Normative Survey Results

The following section summarizes the results obtained for the questions of the

survey. The sample was cleaned as mentioned in “Method of Analysis and

Cleaning” in chapter 5 and included 40 respondents, variations in the number of

responses are due to respondents not answering a particular question.

Additional Demographic Questions

Again the demographic of the survey sample are located the respective

section title in Chapter 5.

1 = Never2 = Rarely3 = Sometimes 4 = Most-of-the-time 5 = Always0 = Do not know0 = NA

1 = Very Dissatisfied2 = Dissatisfied3 = Neutral 4 = Satisfied 5 = Very Satisfied0 = Do not know0 = NA

1 = There is no system2 = Highly Informal System3 = Mix of Formal & Informal 4 = Mostly Formal 5 = Highly Formal0 = Do not know0 = NA

Scale for V115. OnlyScale only used for Satisfaction Questions

Scale only used for All other questions (V#)

312

44S

45S How Satisfied are you with the:

46S How Satisfied are you with the:

313

47S

48S How Satisfied are you with the:

49S How Satisfied are you with the:

314

51S

52S How Satisfied are you with the:

53S How Satisfied are you with the:

315

54S How Satisfied are you with the:

55S How Satisfied are you with the:

56S How Satisfied are you with the:

316

58S

59S How Satisfied are you with the:

60S How Satisfied are you with the:

317

61S How Satisfied are you with the:

V63, V64, V65, V66, V67, V68, V69, V70, V71, V72

318

V73

V75

V76 To what degree does your company:

319

V77 To what degree does your company:

V78 To what degree does your company:

V80

320

V81 To what degree does your company:

V82 To what degree does your company:

V84

321

V85

V86

322

V87, V88, V79, V90, V91, V92, V93, V94, V95, V96, V97

323

V100, V101, V102, V103

V104

V105

324

V107, V106, V107, V108, V109, V110

V114

325

V115

V116, V117, V118, V119

V120

326

V122

V123

V125

327

V126

V127

V128

328

V132

VITA

329

VITA

Brian Glassman Brian.Glassman@Gmail.com 321-543-7165

Entrepreneurial & Consulting Activities • Small business development consulting for 10 businesses • Personally started 8 business

Purdue University West Lafayette, Indiana Ph.D., in Technology, Department of Organizational Leadership and Supervision GPA 3.88

• Specializing in commercialization of technology & innovation management • Generalizing in management and strategy

Duke University Durham, NC Masters of Engineering Management GPA 3.750

Graduate with Honors May-2006 no class ranking was given

• Concentration on New Product Development & Innovation Management

GlaxoSmithKline a consulting project • Facilitated GSK’s in implementing RFID in to their supply chain

NASA a consulting project • Consulted for NASA’s technology transfer

Prestigious national business plan competition • 2nd winner for pitched business to licensing executive society

University of Central Florida Orlando, FL Masters of Science in Mechanical Engineering GPA 3.635

Graduated with honors: 2nd in class (for Mechanical Eng. Masters)

US AirForce Research Labs (work experience)

• Researched and designed cooling systems for laser weapons • Publications: 3 publications in total

Florida Institute of Technology Melbourne, FL Bachelors of Science in Mechanical Engineering GPA 3.62

• Graduated Magna Cum Laude • Graduate 2nd in M.E. class out of 45 students