No. 8 · Decisions · Mathematics
Sensitivity Analysis
Not all assumptions are equal: find the few that swing the whole result.
In the Almanac
“The Limits to Growth”, 1972 · “Hinkley Point C”, 2016–2024
Both stories in full, three ways to use it and where it misleads.
Get the AlmanacQuestions
What is Sensitivity Analysis?
Sensitivity Analysis is the study of how changes in a model's inputs affect its outputs. By adjusting one assumption at a time, such as costs, growth or interest rates, you discover which ones barely matter and which can swing the whole result, as rising costs and delays did at Hinkley Point C.
How do you use Sensitivity Analysis?
To use it, stress test big financial decisions at higher interest rates, identify the assumptions your projects depend on most, and build plans that still work when one thing goes wrong.
When does Sensitivity Analysis matter?
Sensitivity Analysis is one of the 35 mental models for decisions, the situations where you ask: Which way should I go? Within that, it belongs to “Weighing the options”, alongside A/B Testing, Back-of-the-Envelope Calculation and Cost-Benefit Analysis.
What is an example of Sensitivity Analysis?
Two stories show it at work: The Limits to Growth (1972) and Hinkley Point C (2016–2024). Both are told in full in The Mental Models Daily Almanac, which has two stories for each of its 365 models.
Which mental models are related to Sensitivity Analysis?
Scenario Analysis, Monte Carlo Simulation and Margin of Safety. Sensitivity Analysis itself comes from mathematics.