Data, Models, and Decisions
Data, Models, and Decisions
The Fundamentals of Management Science, 2nd Edition
by Dimitris Bertsimas and Robert Freund
This book represents a departure from existing textbooks. Rather than covering methodology, the book introduces decision support systems through real world applications, and uses spreadsheets to model and solve problems. It uses management science techniques (statistics, simulation, probabilistic modeling and optimization), but only as tools to facilitate problem solving.
The book is used in the core MBA program at MIT's Sloan School of Management for the class titled Data, Models, and Decisions.
We believe that the use of management science tools and models represents the future of best-practices for tomorrow's successful companies. It is therefore imperative that tomorrow's business leaders be well-versed in the underlying concepts and modeling tools of management science, broadly defined. George Dantzig, a founding father of modern management science, wrote, ``The final test of any theory is its capacity to solve the problems which originated it. It is our mission in this book to contribute to preparing today's management students to become tomorrow's business leaders, and therefore demonstrate that the tools and models of management science pass Dantzig's test.
This book is designed with the following three principles in mind:
- Rigor: In order to become tomorrow's business leaders, today's managers need to know the fundamental quantitative concepts, tools, and modeling methods. The focus here is on fundamental and concepts. While management students should not be expected to remember specific formulas, spreadsheet commands, or technical details after they graduate, it is important for them to retain fundamental concepts necessary for managing in an increasingly technically-oriented business environment. Simply teaching students to plug numbers into black-box models is not relevant to a student's education. This book emphasizes how, what, and why certain tools and models are useful, and what their ramifications would be when used in practice.
- Relevance: All of the material presented in the book is immediately applied to realistic and representative business scenarios. Because students recognize a spreadsheet as a standard business environment, the spreadsheet is the basic template for almost every model that is presented in the book. Furthermore, the book features over thirty business cases that are drawn from our own consulting experience or the experience of our students and cover a wide spectrum of industries, management functions, and modeling tools.
- Readability: We have deliberately written the book in a style that is engaging, informative, informal, conversational in tone, and imbued with a touch of humor from time to time. Many students and colleagues have praised the book's engaging writing style. Most of the chapters and cases have been pre-tested in classrooms at MIT Sloan, Harvard Business School, Wharton, Columbia University, University of British Columbia, Ohio State University, Northwestern University, and McGill University, plus several universities overseas.
- Unified Treatment of Quantitative Methods: The book combines topics from two traditionally distinct quantitative subjects: probability/statistics, and management science optimization models, into one unified treatment of quantitative methods and models for management and business. The book stresses those fundamental concepts that we believe are most important for the practical analysis of management decisions. Consequently, it focuses on modeling and evaluating uncertainty explicitly, understanding the dynamic nature of decision-making, using historical data and limited information effectively, simulating complex systems, and allocating scarce resources optimally.
- Concise Writing: Despite its wide coverage, the book is designed to be more concise than most existing textbooks. That is, the relevant points are made in the book once or twice, with appropriate examples, and then reinforced in the exercises and in the case modules. There is no excess repetition of material.
- Appropriate Use of Spreadsheets: Because students recognize a spreadsheet as a standard business environment, the spreadsheet is the basic template for almost every model presented in the book. In addition, for simulation modeling, linear regression, and linear, nonlinear and discrete optimization, we present command instructions on how to construct and run these models in a spreadsheet environment. However, the book presumes that students already have a basic familiarity with spreadsheets, and so the book is not a spreadsheet user's manual. Unlike many existing textbooks, the use of spreadsheets in our book is designed not to interfere with the development of key concepts. For example, in Chapters 7-9, which cover optimization models, we introduce and develop the concept of an optimization model by defining decision variables and by explicitly constructing the relevant constraints and objective function. Only then do we translate the problem into a spreadsheet for solution by appropriate software. In context, spreadsheets are a vehicle for working with models, but are not a substitute for thinking through the construction of models and analyzing modeling-related issues.
- Case Material for Tomorrow's Managers: The book features over thirty business cases that are rich in context, realistic, and are often designed with the protagonist being a relatively young MBA graduate facing a difficult management decision. They cover a wide spectrum of industries, functional areas of management, and modeling tools.
- A Capstone Chapter on Integration in the Art of Decision Modeling: Chapter 10, which is the last chapter in the book, illustrates the integrated use of decision modeling in three sectors: the airlines industry, the financial investment management industry, and the manufacturing sector. This chapter contains much material to motivate students about the power of using management science tools and models in their careers.
The following materials are available here for purchasers of the book.
- Spreadsheets: Spreadsheet data and partially-and/or fully-constructed spreadsheet models for many of the cases in the book. Click here to initiate file download.
- Crystal Ball Software: Crystal Ball® Simulation Software. The simulation case models in Chapter 5 are designed to work with Crystal Ball® simulation software, which is a Microsoft Excel® add-on. Instructions to obtain Crystal Ball® software can be found under Resources for Students.
The following resources are available to qualified instructors upon request:
- Microsoft PowerPoint® Presentation slides for lecture material.
- Test Bank of examination questions.
- Solution Manual for all exercises.
- Case Instructor Notes for cases in the book.
A solution manual is available to qualified instructors upon request. An instructor resource form with solutions to the exercises will be provided upon request. Please fill out the form in the "For Instructors" section under Resources.
A review of the book can be found at GraduateTutor.com.