Suppose you expect a new product line to start generating a certain amount of annual profit a year from now. What if some variable in the scenario changed? How would that affect your overall evaluation of the investment opportunity?
Sensitivity analysis enables you to ask just this kind of question. It also helps you see the ramifications of incremental changes in the assumptions that underlie a particular projection. A sensitivity analysis shall determines how different values of an independent variable affect a particular dependent variable under a given set of assumptions. This technique is used within specific boundaries that depend on one or more input variables, such as the effect that changes in interest rates (independent variable) has on bond prices (dependent variable).
Kedai Jam Terlajak Laris (KJTL) is considering investing in a new line of serving carts. Key stakeholders have different assumptions about this investment:
The three different assumptions are
- Aarif, the vice president of the company’s hanging-racks division, would exercise day-to-day oversight of the new product line. He projects that the new line will generate MYR 60,000 in annual profit for five years.
- Adi, the company’s CFO, is a bit wary about the investment. That’s because he thinks that Aarif has drastically underestimated the marketing costs necessary to support the new line. He predicts an annual profit stream of MYR 45,000.
- Luqman, KJTL’s senior vice president for new business development, is optimistic by nature. He’s convinced that the serving carts will practically sell themselves, producing an annual profit stream of MYR 75,000 a year.
KJTL conducts a sensitivity analysis by calculating NPV for the three different profit scenarios:
Yield three different results:
- NPV for Aarif’s scenario is MYR 2,742.
- NPV for Adi’s scenario is MYR – 60,443 (a negative NVP).
- NPV for Luqman’s scenario is MYR 65,927.
If Adi is right, the serving carts won’t be worth the investment, since the NPV for this scenario is significantly negative. But if Aarif or Luqman is right, the investment will be worthwhile marginally so according to Aarif’s profit projections, and very much so according to Luqman’s.
This is where judgment comes into play. If Adi is the best estimator of the three, KJTL’s board of directors might prefer to accept her estimate of the new line’s profit potential. Better still, the company should analyze its marketing costs in greater detail.
Whichever route KJTL takes, the sensitivity analysis will give the board of directors a more nuanced view of the investment and how it would be affected by different assumptions.