From operations research and financial modeling, with no single originator: the post-optimality analysis of Abraham Charnes and William W. Cooper (1961), the Monte Carlo method of Nicholas Metropolis and Stanislaw Ulam (1949), and the capital-budgeting simulation of David B. Hertz (1964).
Varies each input of a model across its plausible range to show which few assumptions move the answer, where the recommendation flips, and how wide the real range is.
When to reach for it
After building any NPV, forecast, pricing, or capacity model, and before showing the number to a decision maker.
How it runs
- Name the output that matters.
- Set a low, base, and high value for each input.
- Swing each input alone and rank inputs by their effect.
- Vary the top two or three together.
- Find the value at which the recommendation flips.
- Run a simulation if the inputs interact.
Where it sits in SOLVE eX
Go to the source
- Management Models and Industrial Applications of Linear Programming, Wiley, 1961
- The Monte Carlo Method, Journal of the American Statistical Association 44, 1949
- Risk Analysis in Capital Investment, Harvard Business Review 42, 1964
- Global Sensitivity Analysis: The Primer, Wiley (Andrea Saltelli and colleagues), 2008