Praise for Modeling for Insight

"Most books on modeling are either too theoretical or too
focused on the mechanics of programming. Powell and Batt's emphasis
on using simple spreadsheet models to gain business insight (which
is, after all, the name of the game) is what makes this book stand
head and shoulders above the rest. This clear and practical book
deserves a place on the shelf of every business analyst."

--Jonathan Koomey, PhD, Lawrence Berkeley National Laboratory
and Stanford University, author of Turning Numbers into
Knowledge: Mastering the Art of Problem Solving

Most business analysts are familiar with using spreadsheets to
organize data and build routine models. However, analysts often
struggle when faced with examining new and ill-structured problems.
Modeling for Insight is a one-of-a-kind guide to building
effective spreadsheet models and using them to generate insights.
With its hands-on approach, this book provides readers with an
effective modeling process and specific modeling tools to become a
master modeler.

The authors provide a structured approach to problem-solving
using four main steps: frame the problem, diagram the problem,
build a model, and generate insights. Extensive examples, graduated
in difficulty, help readers to internalize this modeling process,
while also demonstrating the application of important modeling
tools, including:

* Influence diagrams

* Spreadsheet engineering

* Parameterization

* Sensitivity analysis

* Strategy analysis

* Iterative modeling

The real-world examples found in the book are drawn from a wide
range of fields such as financial planning, insurance,
pharmaceuticals, advertising, and manufacturing. Each chapter
concludes with a discussion on how to use the insights drawn from
these models to create an effective business presentation.
Microsoft Office Excel and PowerPoint are used throughout the book,
along with the add-ins Premium Solver, Crystal Ball, and
Sensitivity Toolkit. Detailed appendices guide readers through the
use of these software packages, and the spreadsheet models
discussed in the book are available to download via the book's
related Web site. Modeling for Insight is an ideal book for
courses in engineering, operations research, and management science
at the upper-undergraduate and graduate levels. It is also a
valuable resource for consultants and business analysts who often
use spreadsheets to better understand complex problems.

STEPHEN G. POWELL, PhD, is Professor at the Tuck School of
Business at Dartmouth College. The recipient of the 2001 INFORMS
Prize for the Teaching of Operations Research/Management Science
Practice, Dr. Powell teaches and conducts research on modeling for
business decision making. He is the coauthor of Management
Science: The Art of Modeling with Spreadsheets, Second Edition,
also published by Wiley.

ROBERT J. BATT, MEM, MBA, is Tuck Fellow and researcher
at the Tuck School of Business at Dartmouth College. With
experience in both academia and industry, his work focuses on
operations management and finance.

"Most books on modeling are either too theoretical or too focused on the mechanics of programming. Powell and Batt's emphasis on using simple spreadsheet models to gain business insight (which is, after all, the name of the game) is what makes this book stand head and shoulders above the rest. This clear and practical book deserves a place on the shelf of every business analyst."
Jonathan Koomey, PhD, Lawrence Berkeley National Laboratory and Stanford University, author of Turning Numbers into Knowledge: Mastering the Art of Problem Solving

Most business analysts are familiar with using spreadsheets to organize data and build routine models. However, analysts often struggle when faced with examining new and ill-structured problems. Modeling for Insight is a one-of-a-kind guide to building effective spreadsheet models and using them to generate insights. With its hands-on approach, this book provides readers with an effective modeling process and specific modeling tools to become a master modeler.

The authors provide a structured approach to problem-solving using four main steps: frame the problem, diagram the problem, build a model, and generate insights. Extensive examples, graduated in difficulty, help readers to internalize this modeling process, while also demonstrating the application of important modeling tools, including:

• Influence diagrams

• Spreadsheet engineering

• Parameterization

• Sensitivity analysis

• Strategy analysis

• Iterative modeling

The real-world examples found in the book are drawn from a wide range of fields such as financial planning, insurance, pharmaceuticals, advertising, and manufacturing. Each chapter concludes with a discussion on how to use the insights drawn from these models to create an effective business presentation. Microsoft Office Excel and PowerPoint are used throughout the book, along with the add-ins Premium Solver, Crystal Ball, and Sensitivity Toolkit. Detailed appendices guide readers through the use of these software packages, and the spreadsheet models discussed in the book are available to download via the book's related Web site. Modeling for Insight is an ideal book for courses in engineering, operations research, and management science at the upper-undergraduate and graduate levels. It is also a valuable resource for consultants and business analysts who often use spreadsheets to better understand complex problems.

PREFACE xiii

USING THIS BOOK xix

ACKNOWLEDGMENTS xxiii

ACKNOWLEDGMENTS FOR CASES xxv

ABOUT THE AUTHORS xxvii

PART I 1

1. Introduction 3
1.0 Models and Modeling 3
1.1 Well-Structured versus Ill-Structured Problems 4
1.2 Modeling versus Problem Solving 5
1.3 Modeling for Insight 6
1.4 Novice Modelers and Expert Modelers 7
1.5 Craft Skills in Modeling 8
1.6 A Structured Modeling Process 9
1.7 Modeling Tools 9
1.8 Summary 10

2. Foundations of Modeling for Insight 11
2.0 Introduction 11
2.1 The Modeling Process 11
2.2 Tools for Modeling 19
2.3 Presentation Skills 26
2.4 Summary 34

3. Spreadsheet Engineering 36
3.0 Why Use Spreadsheets? 36
3.1 Spreadsheet Engineering 37
3.2 Summary 49

PART II 51

4. A First ExampleThe Red Cross Problem 53
4.0 Introduction 53
4.1 The Red Cross Problem 53
4.2 Bringing Blood Quality into the Analysis 69
4.3 Improving and Iterating 78
4.4 Summary 79

5. Retirement Planning Problem 80
5.0 Introduction 80
5.1 Retirement Planning (A) 80
5.2 Retirement Planning (B) 99
5.3 Retirement Planning (C) 107
5.4 Presentation of Results 112
5.5 Summary 122

6. Technology Option 122
6.0 Introduction 122
6.1 Technology Option (A) 122
6.2 Technology Option (B) 131
6.3 Additional Refi nements 138
6.4 Presentation of Results 147
6.5 Summary 152

PART III 155

7. MediDevice 157
7.0 Introduction 157
7.1 MediDevice Case (A) 157
7.2 Revising the Model 172
7.3 MediDevice Case (B) 178
7.4 Presentation of Results 184
7.5 Summary 190

8. Draft Commercials 194
8.0 Introduction 194
8.1 Draft Commercials Case 194
8.2 Frame the Problem 196