Modeling For Insight: A Master Class For Business Analysts

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 Turning Numbers into Knowledge: Mastering the Art of Problem Solving

PREFACE.
USING THIS BOOK.
ACKNOWLEDGMENTS.
ACKNOWLEDGMENTS FOR CASES.
ABOUT THE AUTHORS.
PART I.
1. Introduction.
1.0 Models and Modeling.
1.1 Well-Structured versus Ill-Structured Problems.
1.2 Modeling versus Problem Solving.
1.3 Modeling for Insight.
1.4 Novice Modelers and Expert Modelers.
1.5 Craft Skills in Modeling.
1.6 A Structured Modeling Process.
1.7 Modeling Tools.
1.8 Summary.
2. Foundations of Modeling for Insight.
2.0 Introduction.
2.1 The Modeling Process.
2.2 Tools for Modeling.
2.3 Presentation Skills.
2.4 Summary.
3. Spreadsheet Engineering.
3.0 Why Use Spreadsheets?
3.1 Spreadsheet Engineering.
3.2 Summary.
PART II.
4. A First Example—The Red Cross Problem.
4.0 Introduction.
4.1 The Red Cross Problem.
4.2 Bringing Blood Quality into the Analysis.
4.3 Improving and Iterating.
4.4 Summary.
5. Retirement Planning Problem.
5.0 Introduction.
5.1 Retirement Planning (A).
5.2 Retirement Planning (B).
5.3 Retirement Planning (C).
5.4 Presentation of Results.
5.5 Summary.
6. Technology Option.
6.0 Introduction.
6.1 Technology Option (A).
6.2 Technology Option (B).
6.2.1 Frame the Problem—M2.
6.3 Additional Refi nements.
6.4 Presentation of Results.
6.5 Summary.
PART III.
7. MediDevice.
7.0 Introduction.
7.1 MediDevice Case (A).
7.2 Revising the Model.
7.3 MediDevice Case (B).
7.4 Presentation of Results.
7.5 Summary.
8. Draft Commercials.
8.0 Introduction.
8.1 Draft Commercials Case.
8.2 Frame the Problem.
8.3 Diagram the Problem.
8.4 M1 Model and Analysis.
8.5 M2 Model and Analysis.
8.6 M3 Model and Analysis.
8.7 M4 Model and Analysis.
8.8 Presentation of Results.
8.9 Summary.
9. New England College Skiway.
9.0 Introduction.
9.1 New England College Skiway Case.
9.2 Frame the Problem.
9.3 Diagram the Problem.
9.4 M1 Model and Analysis.
9.5 Analyzing Mountain Capacity.
9.6 M2 Model and Analysis.
9.7 M3 Model and Analysis.
9.8 Considering Uncertainty.
9.9 Presentation of Results.
9.10 Summary.
10. National Leasing, Inc.
10.0 Introduction.
10.1 National Leasing Case.
10.2 Frame the Problem.
10.3 Diagram the Problem.
10.4 M1 Model and Analysis.
10.5 M2 Model and Analysis.
10.6 M3 Model and Analysis.
10.7 M4 Model and Analysis.
10.8 Presentation of Results.
10.9 Summary.
11. Pharma X and Pharma Y.
11.0 Introduction.
11.1 The Pharma X and Pharma Y Case.
11.2 Frame the Problem.
11.3 Diagram the Problem.
11.4 Expected Value or Simulation?
11.5 M1 Model and Analysis.
11.6 M2 Model and Analysis.
11.7 M3 Model and Analysis.
11.8 Presentation of Results.
11.9 Summary.
12. Invivo Diagnostics, Inc.
12.0 Introduction.
12.1 Invivo Diagnostics Case.
12.2 Frame and Diagram the Problem.
12.3 M1 Model and Analysis.
12.4 M2 Model and Analysis.
12.5 M3 Model and Analysis.
12.6 M4 Model and Analysis.
12.7 Presentation of Results.
12.8 Summary.
Appendix A: Guide to Solver.
Appendix B: Guide to Crystal Ball.
Appendix C: Guide to the Sensitivity Toolkit.
INDEX.