Quick Answer
Sensitivity analysis is a technique that tests how changes in individual input variables affect your financial model's output. By varying one assumption at a time — such as revenue growth rate, churn, or headcount — while holding others constant, you identify which variables have the largest impact on outcomes like profit, cash flow, or valuation. This reveals where to focus your planning effort.
Sensitivity analysis answers the question: "If this assumption is wrong, how much does it matter?" By systematically varying each key input and measuring the impact on outputs, you learn which assumptions are critical and which are less important. (For a concise definition, see our glossary entry on sensitivity analysis.)
1. Identify key variables. Select the 5-10 assumptions with the highest uncertainty or largest potential impact: revenue growth, churn rate, sales conversion, headcount, key cost items.
2. Define the range. For each variable, set a reasonable range. Revenue growth might vary from -10% to +30%. Churn might range from 5% to 20%. Base these ranges on historical variation and market conditions.
3. Test one at a time. Change each variable independently while holding all others at their base case values. Record the impact on your key output metrics (EBITDA, cash flow, runway).
4. Rank by impact. Sort variables by their impact on the output metric. The variables with the largest impact deserve the most planning attention.
5. Visualise results. Present findings in a tornado chart (horizontal bars showing the range of impact for each variable) or a data table showing outputs at different input levels.
One-way: Varies one input at a time. Simple and clear, good for identifying individual variable importance.
Two-way: Varies two inputs simultaneously to see how they interact. Useful for understanding correlated risks (e.g., how do revenue and churn together affect runway?). Often presented as a matrix or heat map.
Don't test too many variables — focus on the material ones. Don't use unrealistically wide ranges that produce unhelpful results. And remember that sensitivity analysis tests variables independently; in reality, variables are often correlated (recession affects both revenue and churn simultaneously). Use scenario analysis for correlated changes.
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FAQ
A tornado chart is a horizontal bar chart showing how each variable affects a key output. The widest bars (at the top) represent the most impactful variables. It is called a tornado chart because the shape — wide at the top, narrow at the bottom — resembles a tornado.
Sensitivity analysis changes one variable at a time to isolate its impact. Scenario planning changes multiple variables together to model a coherent story (e.g., a recession scenario). Use sensitivity to identify key variables; use scenarios to model plausible futures.
Focus on 5-10 key variables. These should be the assumptions with the highest uncertainty and the largest potential financial impact. Testing too many variables dilutes the insight.
Yes. FP&A software like Grove FP can run sensitivity analysis automatically by varying each key assumption across a defined range and presenting the results in tornado charts and data tables.
Include sensitivity analysis in board presentations, investor decks, and annual budget reviews. It demonstrates rigorous thinking and helps stakeholders understand the risk profile of your plan.
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