The practice of varying a model's key assumptions to see how much the answer moves. The difference between a forecast that informs a decision and a single number that merely decorates one.
Any business case can be made to clear a hurdle. Sensitivity analysis reveals how hard the authors had to try, which is often the most decision-relevant fact in the whole pack.
Last reviewed 3 July 2026 · Free and ungated
Which of your break-even assumptions have failed elsewhere? The Global Board can tell you, confidentially, before sign-off.
Challenge the assumptions before committingSensitivity analysis takes a financial or operational model and systematically varies its inputs, adoption rates, prices, volumes, timelines, discount rates, to show how the output responds. Its products are simple: which assumptions the result is most sensitive to, and how far each can move before the recommendation changes.
A case presented as one scenario is an argument; sensitivity turns it back into a forecast by exposing its load-bearing walls. For the person who must approve the commitment, two outputs matter most. The first is the break-even point of each major assumption, the adoption rate or price at which the case stops working, because that can be compared against lived experience. The second is which variables the outcome barely responds to, since arguments in the room have a habit of concentrating on visible assumptions rather than consequential ones. Knowing the difference redirects scarce challenge to where it changes the decision.