The variables used to develop the table, including sales price, variable costs, unit sales, and the unit growth rate, are all most likely, or base-case, values, and the resulting $25,517 NPV shown in Part 5 is called the base-case NPV. Now we ask a series of "what if" questions: "What if unit sales falls 30 percent below the most likely level?" In our sensitivity analysis we hold the other variables at their base case levels and then examine the situation when the key variables change. Each new calculated NPV is plotted on the graph in Part 6 to show how sensitive NPV is to changes in each variable. The table below outlines the NPV figures that we used to construct the graph. The slopes of the lines in the graph show how sensitive NPV is to changes in each of the inputs: the steeper the slope, the more sensitive the NPV is to a change in the variable. From the figure and the table, we see the project's NPV is very sensitive to changes in the sales price, variable cost, and growth rate.
Although sensitivity analysis is probably the most widely used risk analysis technique, it does have limitations. In addition, it would be useful to vary more than one variable at a time so we could see the combined effects of changes in the variables. We saw from the sensitivity analysis that the key variables are sales price, variable costs, unit sales, and the unit growth rate. Therefore, in our sensitivity analysis we hold the other variables at their base case levels and then examine the situation when the key variables change. We assume that the company regards the worst case as one where each of the three variables is 30% worse than the base level, and the best case has each variable 30% better than base. We also assume that there is a 25% chance of the best and worst cases, and a 50% chance of base case levels. The best-case, base-case, and worst-case values are shown in Part 7, along with the plot of the data. If...
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