ABSTRACT
This chapter presents the incorporation of uncertainty into spreadsheet models through the use of @RISK, an Excel add-in. Uncertainty is reflected through replacing parameters in the model that are uncertain with probability distributions, representing the uncertainty in their potential values. Monte Carlo simulation then simultaneously selects random values from these distributions and records how model outputs are affected. The result of such a Monte Carlo model is a distribution of possible model outputs, along with the probability (frequency) that these outputs occur, so that decision-makers understand the possible ranges of outcomes and their likelihood of happening.
These probabilistic assessments thus allow for explicit recognition of all uncertainties in a model. Further insights are obtained from tornado charts, which show which of the uncertainties are the key drivers of risk in the outcome. Another useful tool is demonstrated—simulation tables that permit a decision variable to be varied and its effect on uncertain results to be reviewed.
Two examples are explored in detail: the MoviePass and Retirement Model cases from the first chapter. We explore each, focusing on the potential profitability of MoviePass and on the timing of when a retirement fund may run out, as two cases.
