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 decision-support 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.Ashort 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-usermodeling.Nowthat virtually every analyst has access to a powerfulcomputer,
the out-of-pocket costs ofmodeling have become negligible. The major cost now is the
analyst’s time: time to define the problem, gather data, build and debug a model, and
use themodel to support the decision process.For this timeto bewell 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.