Scenario Planning
Builds scenarios around the two most uncertain high-impact drivers, rather than around good, base and bad.
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Running it, start to finish
- Separate what is predetermined from what is genuinely uncertain.
- Pick the two highest-impact uncertainties as your axes.
- Assign an owner to each early signal.
What you get back
The output this produces, every time.
- Builds on two genuine uncertainties rather than on optimism levels.
- Separates predetermined elements, which belong in every scenario rather than varying.
- Names an early signal per scenario, which is what converts the exercise into a plan.
Getting better results
Where this usually goes wrong, and how to avoid it.
- Do not rank scenarios by likelihood. It collapses the exercise back into a forecast and everyone plans for the one they were already planning for.
- The robust actions are the output. There are usually fewer than expected, and that scarcity is itself the finding about how contingent your plan is.
- Assign the signals to someone. A scenario nobody is watching for is a workshop. One with a named indicator and an owner is a plan.
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Written for The AI University. Every prompt in this library is original work — authored, tested and revised here, not collected from elsewhere. 365 of them, free with an account.