14 Monte Carlo Simulation


Change and uncertainty are ubiquitous features of the business world. The effective business analyst and model builder, whose work always involves planning for an uncertain future, must therefore have tools for dealing with these aspects of business life. In earlier chapters, we generally assumed that the parameters and relationships in our models were known with certainty. We did not entirely ignore uncertainty, but we dealt with it as a secondary feature of the situation, perhaps using what-if analysis or scenario analysis to explore how our model results would change if our assumptions changed. In Chapter 13, we began to look at decision problems in which uncertainty is a central, unavoidable feature of the problem, so that if we ignore it, our analysis is sure to be flawed. In this chapter, we present Monte Carlo simulation, an important and flexible technique for modeling situations in which uncertainty is a key factor.

Analytic Solver Platform provides the capability to implement Monte Carlo simulation in spreadsheet models. We assume in this chapter that the reader is familiar with the basic concepts of probability, because these are essential to analyzing situations involving uncertainty. The relevant concepts are reviewed in Appendix 3 (Basic Probability Concepts).

In a nutshell, simulation can describe not only what the outcomes of a given decision could be, but also the probabilities with which these outcomes will occur. In ...

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