introduction to decision science

Spreadsheet Modeling & Decision Analysis

A Practical Introduction to Management Science

5th edition

Cliff T. Ragsdale

Introduction to Modeling & Problem Solving

Chapter 1

Introduction

We face numerous decisions in life & business.

We can use computers to analyze the potential outcomes of decision alternatives.

Spreadsheets are the tool of choice for today’s managers.

What is Management Science?

A field of study that uses computers, statistics, and mathematics to solve business problems.

Also known as:– Operations research– Decision science

Home Runs in Management Science

Motorola– Procurement of goods and services account

for 50% of its costs

– Developed an Internet-based auction system for negotiations with suppliers

– The system optimized multi-product, multi-vendor contract awards

– Benefits: $600 million in savings

Home Runs in Management Science

Waste Management– Leading waste collection company in North

America– 26,000 vehicles service 20 million residential &

2 million commercial customers– Developed vehicle routing optimization system– Benefits:

Eliminated 1,000 routes

Annual savings of $44 million

Home Runs in Management Science

Hong Kong International Terminals– Busiest container terminal in the world– 122 yard cranes serve 125 ships per week– Thousands of trucks move containers in & out of storage

yard– Used DSS to optimize operational decisions involving

trucks, cranes & storage locations– Benefits:

35% reduction in container handling costs50% increase in throughput30% improvement in vessel turnaround time

Home Runs in Management Science

John Deere Company– 2500 dealers sell lawn equipment & tractors with

support of 5 warehouses

– Each dealer stocks 100 products, creating 250,000 product-stocking locations

– Demand is highly seasonal and erratic

– Developed inventory system to optimize stocking levels over a 26-week horizon

– Benefits: $1 billion in reduced inventory Improved customer-service levels

What is a “Computer Model”?

A set of mathematical relationships and logical assumptions implemented in a computer as an abstract representation of a real-world object of phenomenon.

Spreadsheets provide the most convenient way for business people to build computer models.

The Modeling Approach to Decision Making

Everyone uses models to make decisions.

Types of models:– Mental (arranging furniture)– Visual (blueprints, road maps)– Physical/Scale (aerodynamics, buildings)– Mathematical (what we’ll be studying)

Characteristics of Models

Models are usually simplified versions of the things they represent

A valid model accurately represents the relevant characteristics of the object or decision being studied

Benefits of Modeling Economy - It is often less costly to

analyze decision problems using models.

Timeliness - Models often deliver needed information more quickly than their real-world counterparts.

Feasibility - Models can be used to do things that would be impossible.

Models give us insight & understanding that improves decision making.

Example of a Mathematical Model

Profit = Revenue - Expenses

or

Profit = f(Revenue, Expenses)

or

Y = f(X1, X2)

A Generic Mathematical Model

Y = f(X1, X2, …, Xn)

Y = dependent variable

(aka bottom-line performance measure)

Xi = independent variables (inputs having an impact on Y)

f(.) = function defining the relationship between the Xi & Y

Where:

Mathematical Models & Spreadsheets

Most spreadsheet models are very similar to our generic mathematical model:

Y = f(X1, X2, …, Xn)

Most spreadsheets have input cells (representing Xi) to which mathematical functions ( f(.)) are applied to compute a bottom-line performance measure (or Y).

Categories of Mathematical Models

Prescriptive known, known or under LP, Networks, IP,

well-defined decision maker’s CPM, EOQ, NLP,

control GP, MOLP

Predictive unknown, known or under Regression Analysis,

ill-defined decision maker’s Time Series Analysis,

control Discriminant Analysis

Descriptive known, unknown or Simulation, PERT,well-defined uncertain Queueing,

Inventory Models

Model Independent OR/MS

Category Form of f(.) Variables Techniques

The Problem Solving Process

Identify Problem

Formulate & Implement

ModelAnalyze Model

Test Results

Implement Solution

unsatisfactoryresults

The Psychology of Decision Making

Models can be used for structurable aspects of decision problems.

Other aspects cannot be structured easily, requiring intuition and judgment.

Caution: Human judgment and intuition is not always rational!

Anchoring Effects

Arise when trivial factors influence initial thinking about a problem.

Decision-makers usually under-adjust from their initial “anchor”.

Example:– What is 1x2x3x4x5x6x7x8 ?– What is 8x7x6x5x4x3x2x1 ?

Framing Effects

Refers to how decision-makers view a problem from a win-loss perspective.

The way a problem is framed often influences choices in irrational ways…

Suppose you’ve been given $1000 and must choose between:

– A. Receive $500 more immediately– B. Flip a coin and receive $1000 more if heads

occurs or $0 more if tails occurs

Framing Effects (Example)

Now suppose you’ve been given $2000 and must choose between:

– A. Give back $500 immediately– B. Flip a coin and give back $0 if heads occurs

or give back $1000 if tails occurs

A Decision Tree for Both Examples

Initial state

$1,500

Heads (50%)

Tails (50%)

$2,000

$1,000

Alternative A

Alternative B(Flip coin)

Payoffs

Good Decisions vs. Good Outcomes

Good decisions do not always lead to good outcomes...

A structured, modeling approach to decision making helps us make good decisions, but can’t guarantee good outcomes.

End of Chapter 1