Calculate sensitivity from a baseline and changed input and output: get the sensitivity coefficient (% output change ÷ % input change) plus scenarios.

Standard 10% step, changeable. Builds scenarios at −2, −1, 0, +1 and +2 steps.

Optional settings

Sensitivity Analysis Formula

The calculator uses two supplied input/output observations. Relative changes divide by the absolute baseline values, which must be nonzero. The observed coefficient K0 is their ratio; for negative baselines, this absolute-baseline convention is stated explicitly rather than presented as a universal percent-change definition.

K₀ = ((O₁ - O₀) / |O₀|) / ((I₁ - I₀) / |I₀|)
  • Where O1 is the changed observed output value.
  • O0 is the nonzero baseline output value.
  • I0 is the nonzero baseline input value.
  • I1 is the changed observed input value, which must differ from I0.

For scenario input change p%, projected output is Oproj = O0 + |O0| × Kp × p/100. Use Kp = K0 for the observed direction, |K0| for an assumed same direction, or −|K0| for an assumed opposite direction. The observed K0 never changes when an assumption is selected. Enter a positive step to generate −2, −1, 0, +1 and +2 step scenarios. These are baseline-linear assumptions, not validated predictions; zero observed output change gives K0 = 0 and flat scenarios. Retained Low, Moderate, High and Very high bands use |K0| thresholds 0.5, 1 and 2 only as illustrative page heuristics.

Sensitivity Analysis Definition

A sensitivity analysis is a method used in finance, engineering, and modeling to determine how changes in one or more input variables (assumptions) affect an output or result. It is not necessarily an “over time” calculation; it can be applied to any scenario where inputs may vary.

Sensitivity Analysis Example

How to perform a sensitivity analysis?

  1. First, determine the baseline output.

    Determine the baseline (starting) value of the output you care about.

  2. Next, determine the baseline input.

    Determine the baseline (starting) value of the input/assumption you plan to change.

  3. Next, choose the new input value.

    Enter both the changed input and the changed observed output, then supply a positive scenario step.

  4. Finally, compute the impact on the output.

    Calculate the signed observed change ratio, then inspect the five baseline-linear scenarios. Choose an explicit relationship assumption for scenarios; it does not change the observed coefficient.

FAQ

What is a sensitivity analysis?

A sensitivity analysis is a quantitative technique used to measure how a change in one or more inputs (assumptions) affects an output (result). For example, you can model how profit, demand, or break-even units change when you adjust selling price or costs. The result depends on the relationship or model you assume between the variables.

How is a sensitivity analysis calculated?

There is no single universal formula. This page divides observed changes by the absolute nonzero baselines and sets K0 = relative output change / relative input change. Its five scenarios assume Oproj = O0 + |O0| × Kp × p/100. The two-point ratio is not an exact derivative or a full domain model. Same/opposite direction selections are explicit scenario assumptions; the magnitude bands are illustrative page thresholds.