Glossary›Sensitivity Analysis
FP&A & Planning

Sensitivity Analysis

Updated September 2026Finance Software Glossary

Sensitivity analysis is a technique that measures how much a financial outcome changes when one input assumption changes, holding everything else constant. It answers questions like how much profit falls if churn rises one point. Finance teams use it to find which assumptions matter most before building full scenarios.

The classic form flexes one variable through a range, such as price from minus 5% to plus 5%, and records the effect on an output like EBITDA or cash. Ranking the results shows where the model is fragile: if a one-point change in gross margin moves profit more than a ten-point change in marketing spend, margin assumptions deserve the scrutiny.

Sensitivity analysis differs from scenario planning in scope. Sensitivity moves one input at a time to test the model's mechanics. A scenario changes many inputs together to describe a plausible future. Most teams run sensitivities first, then build scenarios around the variables that proved most powerful.

In software: platforms with live driver models, such as Pigment and Anaplan, recalculate outputs instantly when an input changes, which makes one-variable flexing a routine exercise. Aleph keeps models in the spreadsheet layer while syncing actuals, so analysts run sensitivities with familiar formulas on governed data.

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