What it means
Every financial model rests on assumptions, such as prices, volumes, costs, interest rates or exchange rates. Sensitivity analysis changes one assumption at a time, holding the others fixed, and records how the output moves.
The assumptions that cause the biggest swings are the ones deserving the closest attention. The method is simple but powerful.
It reveals where a plan is fragile, for example if a 5% fall in price wipes out most of the profit, whereas a 5% rise in rent barely registers. Managers can then decide where to invest effort, buy insurance, negotiate contracts or build in a safety margin.
Results are usually shown as a table or a chart. A tornado chart ranks inputs by the size of their effect, and a two-way table shows how profit changes across a grid of price and volume combinations.
Finance teams use these in budgets, capital investment appraisals, loan applications and valuation work. Sensitivity is related to, but different from, scenario analysis.
A scenario changes several assumptions at once to describe a coherent story, such as a recession, whereas sensitivity changes one input at a time to isolate its effect. Many teams use both, starting with sensitivity to find what matters and then building scenarios around those drivers.
The limits are worth knowing. Real-world inputs often move together, so changing one in isolation can understate risk, and the analysis only tests the ranges you choose.
A flat table of numbers can also give false comfort if the range of assumptions is too narrow. A useful habit is to present the findings in terms the business can act on.
Instead of saying that profit has a sensitivity of five to price, say that every 1% price cut removes about 5% of profit, which makes the risk obvious to non-specialists. That framing helps sales, operations and finance agree on which levers to protect.
In practice
Real-world examples.
Example
A property developer tests a project against construction cost overruns of 5%, 10% and 15%. The model shows the project still earns its target return at 5% but not at 10%. The board agrees to fix the main building contract price before committing.
Example
A subscription business measures how monthly revenue changes if customer cancellations rise from 3% to 4%. The result shows a much bigger drop than expected, because the lost customers also reduce future referrals. The head of finance asks the customer team for a retention plan.
Example
A treasurer at an importing company tests how a 5% weaker home currency would affect the cost of goods bought in dollars. The result shows a $450,000 annual cost increase. She uses it to decide how much of the exposure to hedge.
Formula
Calculation
Sensitivity = percentage change in output / percentage change in input
Suppose a business sells 10,000 units at $50 each, with variable cost of $30 per unit and fixed costs of $100,000. Base profit = (50 - 30) x 10,000 - 100,000 = $100,000.
If the price falls 10% to $45, profit = (45 - 30) x 10,000 - 100,000 = $50,000, a fall of 50%, so sensitivity to price = -50% / -10% = 5.
If volume falls 10% to 9,000 units, profit = (50 - 30) x 9,000 - 100,000 = $80,000, a fall of 20%, so sensitivity to volume = -20% / -10% = 2.
Profit is two and a half times as sensitive to price as to volume, so protecting the price matters more.Case study
Seen in the real world.
Cobalt Coast Logistics is an illustrative, fictional freight company evaluating a new depot. The base case showed a respectable return, and the managing director was ready to sign.
The finance analyst ran a sensitivity table on fuel prices, utilisation and wage costs. Utilisation was the dominant driver: a fall from 85% to 80% cut the projected profit by nearly 40%, while a 10% rise in fuel cost reduced it by only 12%.
The company signed the lease but also negotiated anchor contracts guaranteeing a minimum volume. The illustrative lesson is that sensitivity points management towards the one assumption that can really hurt, rather than spreading attention evenly.
Watch out
Common mistakes.
- Changing several inputs at once and calling it sensitivity analysis, which makes it impossible to see which input caused the change.
- Testing only small, comfortable ranges, so the analysis never reveals how the plan behaves under a genuinely bad outcome.
- Treating the base case as certain once the table is built, instead of using the table to challenge the most influential assumptions.
Questions
People also ask.
How is sensitivity different from scenario analysis?
Sensitivity moves one input at a time to isolate its effect, whereas scenario analysis moves several together to describe a complete situation.
Which inputs should I test first?
Start with the assumptions that are both uncertain and large in value, such as selling price, volume, major costs and interest rates.
Can sensitivity be shown in a spreadsheet?
Yes, most spreadsheets offer data tables or simple formulas that recalculate results across a range of values for one or two inputs.
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