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An exclusive survey and report on: Midmarket companies moving fast toward big data reliance Larry Marion Spring 2014 Presented to Prepared by Midmarket interest in Big Data and data analysis rivals that of enterprise firms. Budgets are rising, with IT and sales and marketing taking the lead.
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survey and analysis of Big Data use in large mid market organizations around the world. Research report available upon request.TRANSCRIPT
An exclusive survey and report on: Midmarket companies moving fast
toward big data reliance Larry Marion Spring 2014 Presented to
Prepared by Midmarket interest in Big Data and data analysis rivals
that of enterprise firms. Budgets are rising, with IT and sales and
marketing taking the lead. Agenda Introductions Survey Objectives
Methodology Demographics Universal agreement on Big Datas
importance Improving quality currently the biggest benefit Data
volumes, budget limitations top Big Data challenges Strong ties
between business and IT critical to success Best practices Next
stepsreport themes 2 Team background 3 Triangle Publishing Services
Co. Inc. (TPSC) is a leading provider of content about information
technology for business and technology publications and vendors. It
has produced hundreds of research reports, web sites, feature
articles, case studies and other forms of content. Triangle
consists of a team of 60 business and technology journalists,
designers, audio and video experts around the world. Beacon
Technology Partners LLC helps leading companies better understand
the needs of their customers and prospects. The company's client
base includes both business-to-business and business-to-consumer
companies in other sectors. It offers both quantitative and
qualitative research methods, depending on the client's need to
know for their strategic decision-making as well as additional
research on brand positioning, communications architecture,
customer satisfaction, pricing strategy, market segmentation,
marketing effectiveness and employee engagement. Survey Objectives
Understand business drivers and anticipated results for Big Data
initiatives in midmarket companies. Document technical and business
challenges the midmarket faces with Big Data. Explore tools and
technologies midmarket firms need to implement Big Data projects,
and lessons learned. 4 Methodology Triangle Publishing Services Co.
posted a 15- question questionnaire on a website accessible only to
executives in midmarket companies familiar with Big Data Survey
conducted over 4 days in November, 2013 300 responses received 5
Commentary: +/- 5.5% margin of error We only highlight data that
clearly have statistical significance , i.e., exceed 6 percentage
point deltas Executive Summary 80% agree that they need Big Data
41% have one or more big data projects in place; another 55% are
starting one Budgets on the rise Biggest drivers of success:
IT/Business collaboration, proper skills, and performance
management Biggest causes of failure: Lack of IT/Business
cooperation, lack of tools and skills Most effective suppliers:
Best of breed and integrated full service providers Most
influential in Big Data projects: IT closely followed by
sales/marketing 6 Overview Biggest and MostKey Highlights
Commentary: Improving quality of products/services a bigger driver
than cost cutting Sentiment analysis and social media not yet
important Wide variety of data types, data volumes and budgets are
big challenges today Respondent Profile Functional Areas 7 Title
300 Respondents 67% 33% IT Involvement Business 50%50% C-Level or
VP Director or Manager Responsibilities Application performance
management, including cloud- based apps IT security systemsIT
governance and policies, including budgeting 55% 47% 42% Growing
adoption 8 Commentary: Over half of midmarket companies are just
getting started 55% in Asia have one or more projects, followed by
41% in NA, only 26% EMEA EMEAs relative paucity of Big Data
activity is a recurring theme through the results Question 5.
Please select the ONE best response below that most accurately
describes whether your organization currently has a Big Data
initiative in place. 55%41% 4% My organization is just getting
started with a Big Data project. My organization has one or more
Big Data initiative(s) in place. My organization has no Big Data
initiative in place but has discussed implementing such a program
in the foreseeable future. Picking the low hanging fruit comes
first Question 1: How important is Big Data to meeting the
following strategic or tactical goals in relation to meeting the
business goals of your organization? (% responding very important)
Commentary: Note prominence of tactical, near-term goals Weakness
of understand constituent sentiments implies Big Data analysis of
social media not yet a strong use case among mid-market companies 9
Improve quality of our products and services Obtain better and
deeper understanding of customer needs Identify and take advantage
of business opportunities Improve quality and speed of decision
making Quickly respond to competitive threats or other inputs
Improve effectiveness of our marketing programs Predict future
trends that may imperil business goals Reduce operating
expenditures Better understand constituent sentiments 51% 51% 50%
45% 44% 44% 44% 43% 41% 38% Enable managers to have a better
understanding of the profitability - and profit potential of each
customer, product and line of business Real-time processing,
predictive analytics are most valuable tools 10 Question 15: How
valuable are each of the following tools or technologies to help
your organization optimize its Big Data initiative(s), now and in
two years? Commentary: Real-time processing not surprising due to
trend toward more timely analysis Data cleansing, data dashboards,
visualization see significant uptick in two years Financial
Services (64% answering extremely valuable) values real-time
processing the highest of all industries right now In two years,
Manufacturing ranks data dashboards the highest at 64% 57% 51% 56%
61% 58% 60% 49% 50% 53% 56% 58% 60% % Responding "Extremely
Valuable Now" % Responding "Extremely Valuable in Two Years"
Real-time processing of data and analytics Predictive analytics
Data visualization to convert processed data into actionable
insights Use of cloud computing to provide anytime, anywhere data
and applications access at lower cost Data aggregation that spans
multiple databases, including Big Data platforms such as Hadoop
Data dashboards (desktop self-service data integration) Big Data
proves its worth once deployed 11 Question 16: What impact, if any,
has your organizations Big Data initiative(s) had on improving
decision making? Comparing answers of respondents in development
vs. production 89% 49% 10% 42% 2% 9% Big Data system in production
BD initiative in development but not yet in production Improved
decision making Not yet improved decision making Not sure
Commentary: Of the 123 mid market in production with at least one
Big Data system, overwhelming endorsement of benefit How Big Data
Was Successful 12 Question: How well do you currently perform this
task? Respondents saying very well without BD vs. with BD 23% 20%
27% 32% 23% 44% 40% 46% 49% 50% Quickly sense and respond to
competitive threats or other inputs Reduce capital or operating
costs Understand customer needs Improve product quality Quality and
speed of our decision making In production In development
Commentary: Larger the customer, the more satisfied they are with
Big Data. Manufacturing reports higher satisfaction in most Big
Data areas. Consistent gap of 10-20 points between improvement and
considerable improvement in all areas. Data volumes, budget
limitations top Big Data challenges Question 3. Which of the
following are among the biggest challenges facing your organization
in using data and analytics tools to achieve its business goals? (%
responding) Commentary: Top two concerns related to data and
infrastructure, big areas for IT Concerns over sheer volume of data
point to need for scalable tools Number One, with unusual
consistency across geographies, was, wide variety of new data types
and structures C level almost as aware of it (35%) as director
manager (40%) and business (33%) not too far behind IT (43%) Number
Two is sheer volume of data slows processing, cited by 30%-40% of
respondents across all geographies, and between 31% and 36% of both
business and IT respondents 13 24% 25% 25% 25% 26% 27% 29% 32% 34%
40%Wide variety of new data types and structures Determining what
data (both structured and unstructured, and internal and external)
to use for different business decisions Getting business units to
share information across organizational silos Inaccurate data
Understanding where in your company we should focus our Big Data
investments Not enough trained staff to analyze the data Analytics
tools are lacking and many potential users do not have access Lack
of easy-to-use, cost-effective data cleansing tools Sheer volume of
data slows processing Budget limitations to improve our data
analysis capabilities Strong ties between business and IT a path to
success 14 Question 9: In general, what are the top three reasons
why, in your view, Big Data or data analytics projects succeed.
Please select up to three reasons Commentary: Note, top two reasons
for success and failure are organizational speak to business/IT
alignment Importance of link between data analytics/performance
management especially strong for those with experience, rising from
17% to 41% While not in the top three, business requirements are
complete and accurate also showed strong jump with experience, from
17% to 34% EMA ranked user adoption of tools, complete business
requirements more important than other regions 29% 30% 32% 33% 37%
41% Data center tools are quite capable Server and storage capacity
is readily available Business requirements are complete and
accurate Required IT skills, such as data scientists, are readily
found in the organization Strong connection between data analytics
and performance management in the organization Strong cooperation
or collaboration between business and IT Decision-making top
beneficiary of Big Data 15 Question 16: What impact, if any, has
your organizations Big Data initiative(s) had on improving decision
making? Please select the ONE best response below. Commentary: EMEA
reports significantly more respondents saying decision making not
improved Business and IT report similar levels of satisfaction (67%
IT and 63% business) with 78% C-level saying decision-making
improved Energy and Manufacturing report greatest improvements;
Financial Services, Government and Health Care report the least 65%
29% 6% My organizations Big Data initiative(s) has improved
decision-making in the business. My organization hasnt had time to
evaluate the results from its Big Data initiative(s).My
organizations Big Data initiative(s) hasnt yet improved
decision-making in the business Other data sets Big Data
driverswhich business problems triggered investments Storage
demands now and in the future Data types involvedstructured vs.
unstructured Internal vs. external data explored, too Why Big data
projects fail Which departments control Big Data projects Big Data
funding growing Most important Big Data technologies 16 For More
Information Larry Marion, Editorial Director
[email protected] 17