Management Science: The Art of Modeling with Spreadsheets, 4 edition

Book Preface

This is a book for business analysts about modeling. A model is a simplified representation of a situation or problem, and modeling is the process of building, refining, and analyzing that representation for greater insight and improved decision making. Some models are so common that they are thought of as routine instruments rather than models. A budget, a cash flow projection, or a business plan may have many uses, but each one is a model. In addition, many sophisticated models are embedded in software. Option pricing models, credit scoring models, or inventory models are key components of important decisionsupport systems. Beyond these types, we encounter many customized models, built by the millions of people who routinely use spreadsheet software to analyze business situations. This group includes consultants, venture capitalists, marketing analysts, and operations specialists. Almost anyone who uses spreadsheets in business has been involved with models and can benefit from formal training in the use of models.

Models also play a central role in management education. A short list of models that nearly every business student encounters would include cash flow models, stock price models, option pricing models, product life cycle models, market diffusion models, order quantity models, and project scheduling models. For the management student, a basic ability to model in spreadsheets can be a powerful tool for acquiring a deeper understanding of the various functional areas of business. But to fully understand the implications of these models, a student needs to appreciate what a model is and how to learn from it. Our book provides that knowledge.

For many years, modeling was performed primarily by highly trained specialists using mainframe computers. Consequently, even a simple model was costly and frequently required a long development time. The assumptions and results often seemed impenetrable to business managers because they were removed from the modeling process. This situation has changed radically with the advent of personal computers and electronic spreadsheets. Now, managers and analysts can build their own models and produce their own analyses. This new kind of modeling is known as end-user modeling. Now that virtually every analyst has access to a powerful computer, the out-of-pocket costs of modeling have become negligible. The major cost now is the analyst’s time: time to define the problem, gather the data, build and debug a model, and use the model to support the decision process. For this time to be well spent, the analyst must be efficient and effective in the modeling process. This book is designed to improve modeling efficiency by focusing on the most important tasks and tools and by suggesting how to avoid unproductive steps in the modeling effort. This book is also designed to improve modeling effectiveness by introducing the most relevant analytic methods and emphasizing procedures that lead to the deepest business insights.