Sensitivity analysis definition
/What is Sensitivity Analysis?
Sensitivity analysis is the use of multiple what-if scenarios to model a range of possible outcomes. The technique is used to evaluate alternative business decisions, employing different assumptions about variables. A particularly useful aspect of sensitivity analysis is to locate those variables that can have an unusually large impact on the outcome of the analysis. The decision maker can then evaluate the probability of the variables experiencing significant changes. The outcome is a better understanding of the risks associated with an investment.
How to Create a Sensitivity Analysis
One way to create a sensitivity analysis is to aggregate variables into three scenarios, which are the worst case, most likely case, and best case. The probability of occurrence for the variables used in these three cases clusters the highest probability variables in the most likely case.
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Examples of Sensitivity Analysis
For example, a financial analyst could examine the potential profit levels that may be achieved as a result of an investment in machinery by altering the expected demand level, material costs, equipment downtime percentage, crewing costs, and the residual value of the equipment.
As another example, an analyst is modeling the range of profit outcomes for a prospective equipment purchase. A potential issue is that the equipment may be superseded by a new equipment model, which may reduce its resale value. Accordingly, the analyst conducts a sensitivity analysis that models the lifetime profitability of the investment, assuming a range of possible resale values at the end of the projected usage period for the equipment.
As a third example, an investor models the impact of various world events, such as a pandemic or a regional war, on the reported earnings of a public company in which he has invested, to see how these events will impact its stock price.
Disadvantages of Sensitivity Analysis
There are several disadvantages to using sensitivity analysis. These issues do not mean that you should not use this analysis technique, only that you should be aware of the potential problems associated with it. The issues are as follows:
Uses only historical data. Sensitivity analysis is derived from historical data, which may not apply to future predictions.
Does not incorporate probability of outcomes. Sensitivity analysis does a good job of modeling what-if scenarios, but has no way of stating the probability of occurrence of each one.
No recommended path. Sensitivity analysis shows a variety of possible outcomes, but does not make a recommendation regarding which path to pursue.
Terms Similar to Sensitivity Analysis
A sensitivity analysis is also known as a what-if analysis.