Modeling for Insight: A Master Class for Business Analysts / Edition 1

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Overview

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.

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What People Are Saying

From the Publisher
"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
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Product Details

  • ISBN-13: 9780470175552
  • Publisher: Wiley
  • Publication date: 11/3/2008
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 496
  • Product dimensions: 6.10 (w) x 9.20 (h) x 1.00 (d)

Meet the Author

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.

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Table of Contents

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 Example—The 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
8.3 Diagram the Problem 198
8.4 M1 Model and Analysis 200
8.5 M2 Model and Analysis 205
8.6 M3 Model and Analysis 207
8.7 M4 Model and Analysis 216
8.8 Presentation of Results 222
8.9 Summary 232

9. New England College Skiway 233
9.0 Introduction 233
9.1 New England College Skiway Case 233
9.2 Frame the Problem 234
9.3 Diagram the Problem 237
9.4 M1 Model and Analysis 239
9.5 Analyzing Mountain Capacity 246
9.6 M2 Model and Analysis 250
9.7 M3 Model and Analysis 256
9.8 Considering Uncertainty 273
9.9 Presentation of Results 274
9.10 Summary 283

10. National Leasing, Inc. 285
10.0 Introduction 285
10.1 National Leasing Case 286
10.2 Frame the Problem 289
10.3 Diagram the Problem 291
10.4 M1 Model and Analysis 293
10.5 M2 Model and Analysis 304
10.6 M3 Model and Analysis 313
10.7 M4 Model and Analysis 319
10.8 Presentation of Results 324
10.9 Summary 333

11. Pharma X and Pharma Y 334
11.0 Introduction 334
11.1 The Pharma X and Pharma Y Case 334
11.2 Frame the Problem 338
11.3 Diagram the Problem 339
11.4 Expected Value or Simulation? 340
11.5 M1 Model and Analysis 341
11.6 M2 Model and Analysis 354
11.7 M3 Model and Analysis 366
11.8 Presentation of Results 372
11.9 Summary 380

12. Invivo Diagnostics, Inc. 381
12.0 Introduction 381
12.1 Invivo Diagnostics Case 381
12.2 Frame and Diagram the Problem 384
12.3 M1 Model and Analysis 388
12.4 M2 Model and Analysis 394
12.5 M3 Model and Analysis 406
12.6 M4 Model and Analysis 426
12.7 Presentation of Results 434
12.8 Summary 443

Appendix A: Guide to Solver 445

Appendix B: Guide to Crystal Ball 451

Appendix C: Guide to the Sensitivity Toolkit 456

INDEX 464

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