SIMULATING BUSINESS CASES
One of the more interesting extensions to a standard business case involves the use of simulation to conduct sensitivity analysis and financial stress-testing. And, given the focus on business analytics within this book, it is also a nice demonstration of the power of analytics in improving insight.
A key challenge with most financial modeling processes is they are by their very nature a static representation of potential outcomes. They take a series of fixed inputs, apply a variety of deterministic calculations to them, and provide a number of immutable outputs. This is a great abstraction of reality, but it is also a very blunt tool.
Reality is nowhere near as deterministic as a classic business allows. The assumptions used within most business cases are deliberately severely constrained, not because that is what reflects reality but because that is what a business case allows. Inputs such as the percentage reduction in churn expected to be achieved by the initiative, the degree of contagious churn quarantined through using social network analysis, or the expected aggregate rate of default are normally fixed to a single value and used to calculate a single set of outputs. At best, the business case may involve rerunning the calculations a few more times to accommodate low and high potential outcomes.
To give a better understanding of potential best-case, most-likely, and worst-case scenarios, the same business case is sometimes run three times, each ...