Definition · scenario analysis
Sensitivity analysis
Sensitivity analysis is the practice of measuring how changes in one input affect an output, holding others constant. For sensitivity analysis, the useful boundary is the driver, assumption, source data, owner, time period, scenario logic, and decision the model is meant to support.
Also known as what-if sensitivity, sensitivity testing
Why it matters
Understanding sensitivity analysis matters because planning only improves decisions when assumptions, drivers, owners, and time periods are explicit enough to revisit when actuals arrive. Pluvo computes sensitivities directly on the underlying model, so changing an assumption updates every dependent figure with a clear, auditable trail.
In practice
Planning example
Teams use sensitivity analysis when a forecast, budget, or scenario needs an assumption that can be revisited. The finance team should know the driver, source data, owner, and period before using it in a model.
Pluvo example
Pluvo computes sensitivities directly on the underlying model, so changing an assumption updates every dependent figure with a clear, auditable trail.
In practice, teams should define sensitivity analysis with a clear source, owner, time period, and decision before they use it in reporting, planning, or operating reviews.
Understanding sensitivity analysis matters because planning only improves decisions when assumptions, drivers, owners, and time periods are explicit enough to revisit when actuals arrive. Pluvo computes sensitivities directly on the underlying model, so changing an assumption updates every dependent figure with a clear, auditable trail.
A strong workflow for sensitivity analysis separates the definition from the action: first agree what the term means, then decide how it is measured, when it changes, and who is accountable for the next step.
Pluvo computes sensitivities directly on the underlying model, so changing an assumption updates every dependent figure with a clear, auditable trail.
FAQ
What is sensitivity analysis?
Sensitivity analysis is the practice of measuring how changes in one input affect an output, holding others constant. For sensitivity analysis, the useful boundary is the driver, assumption, source data, owner, time period, scenario logic, and decision the model is meant to support.
How is it different from scenario analysis?
The boundary for sensitivity analysis differs from related terms by scope, source data, time period, and decision use. In this glossary, it covers measuring how changes in one input affect an output, holding others constant, so teams should compare those boundaries before using it in reporting or planning.