Sensitivity Analysis Calculator
A one-at-a-time sensitivity analysis — swing each input across its range while holding the others at base, and rank them by how far the result moves.
The result is the product of the inputs.
How the sensitivity analysis calculator works
The result is the product of the inputs. Each input is set to its low and then its high value with the others at base, and the difference in the result is that input's swing. Ranked largest to smallest, that is a tornado chart.
The ranking is what matters, not the numbers. It tells you which two or three inputs deserve real research, and which can stay as guesses because getting them wrong barely moves the answer.
Formula: swing(i) = result(high_i) − result(low_i), others at base
Worked examples
| Inputs | Base result | Note |
|---|---|---|
| Four inputs | 36,000 | volume dominates |
| A wider price range | 36,000 | price takes the top spot |
| Two inputs only | 200 | A is far more sensitive |
FAQFrequently asked questions
What is a tornado chart?
The inputs ranked by how far the result moves when each one swings across its range, drawn as horizontal bars widest at the top. This page computes the ranking.
Why one at a time?
Because it is simple and answers the practical question — which input deserves research. It misses interactions, which the Monte Carlo page captures.
Why is the model a product?
Because most estimates are: price times volume times margin, or rate times hours times utilisation. Add a factor of 1 for anything that does not scale.
What do I do with the ranking?
Spend your effort on the top two or three. An input at the bottom of the tornado can be a guess without changing the decision.
Does a wide range always mean high sensitivity?
In a product model, sensitivity tracks the relative range — a 20% swing in any input moves the result by about 20%. So yes, and equally for every input.
Where these figures come from
- Hubbard (2014) — How to Measure Anything — the case for ranges over point estimates
- Vose (2008) — Risk Analysis: A Quantitative Guide — Monte Carlo and the triangular distribution
- Saltelli et al. (2008) — Global Sensitivity Analysis: The Primer — one-at-a-time sensitivity and its limits
- Standards Australia — AS ISO 31000 Risk management — the Australian standards body
Last checked: September 2026. The methods are textbook decision analysis: triangular distributions for three-point estimates, tornado ranking for sensitivity, and simple additive weighting for decision matrices.