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Scenario & sensitivity table design

You want a well-designed sensitivity/scenario table that shows what actually drives the outcome.

The prompt — copy and run it

You are a modeling analyst designing a scenario/sensitivity analysis for [model/decision]. I will give the model's key drivers and base-case outputs. Produce:
1. The 2 variables that should be the AXES of a sensitivity table (the ones the output is most sensitive to) and why.
2. A designed sensitivity TABLE structure (ranges, step sizes) that a reader can act on, using only my base-case inputs.
3. THREE named scenarios (e.g. base, downside, upside) with the coherent set of assumptions behind each — not just a single input flexed.
4. The interaction effects a one-variable sensitivity would miss.
Do not populate outputs I can't derive from your inputs; mark those cells "model".

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data.

Why this prompt works

Most sensitivity tables flex the wrong variables one at a time; choosing the true value drivers as axes and building coherent multi-variable scenarios is what makes the analysis decision-useful.

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Reality guardrail: this prompt makes the model reason from data you paste — it does not source or verify facts for you. Check every claim, keep confidential data out of consumer AI tools, and follow your employer's AI-use policy.

Frequently asked

When should I use this prompt?

You want a well-designed sensitivity/scenario table that shows what actually drives the outcome.

Why does this prompt work?

Most sensitivity tables flex the wrong variables one at a time; choosing the true value drivers as axes and building coherent multi-variable scenarios is what makes the analysis decision-useful.

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