Spreadsheet Modeling & Decision Analysis

A Practical Introduction to Management Science

4th edition

Cliff T. Ragsdale

1-2

Introduction to Modeling & Problem Solving

Chapter 1

1-3

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.

1-4

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

1-5

Home Runs in Management Science

• Merril Lynch– 5 million customers– 16,000 financial advisors– Developed a model to design product

features and pricing options to better reflect customer value

– Benefits: • $80 million increase in annual revenue• $22 billion increase in net assiets

1-6

Home Runs in Management Science

• Jan de Wit Co.– Brazil’s largest lily farmer– Annually plants 3.5 million bulbs and

produces 420,000 pots & 220,000 bundles of lilies in 50 varieties.

– Developed model to determine what to plant, when to plant it, and how to sell it.

– Benefits:• 26% increase in revenue• 32% increase in contribution margin

1-7

Home Runs in Management Science

• NBC– Must determine program schedules– Schedules must meet advertisers

demographic and cost requirements– Developed optimization model to

determine optimal timing and pricing of commercials

– Benefits:• $50 million increase in annual revenue

1-8

Home Runs in Management Science

• Samsung Electronics– Leading DRAM manufacturer– Semiconductor facilities cost $2-$3 billion– High equipment utilization is key– Developed comprehensive planning and

scheduling system to control WIP– Benefits:

• Cut cycle times in half• $1 billion increase in annual revenue

1-9

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.

1-10

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)

1-11

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

1-12

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.

1-13

Example of a Mathematical Model

Profit = Revenue - Expensesor

Profit = f(Revenue, Expenses)or

Y = f(X1, X2)

1-14

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:

1-15

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).

1-16

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

1-17

The Problem Solving Process

Identify Problem

Formulate & Implement

ModelAnalyze Model

Test Results

Implement Solution

unsatisfactoryresults

1-18

The Psychology of Decision Making

• Models can be used for structurable aspects of decision problems.

• Other aspects cannot be structured easily and require intuition and judgment.

• Caution: Human judgment and intuition is not always rational!

1-19

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 ?

1-20

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

1-21

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

1-22

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

1-23

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.

1-24

End of Chapter 1