Change one input at a time

Choose a small set of important variables such as acquisition cost, conversion, retained contribution or partner productivity. Hold the other assumptions stable while changing one variable across a plausible range. This reveals the source of movement rather than hiding it inside a fully rewritten scenario.

Show the decision threshold

Identify where the result would change management’s action. Perhaps a campaign stops producing enough contribution, or a launch requires more cash than available. The useful output is the threshold and its implications, not simply a colourful table of larger and smaller totals.

Prioritise evidence collection

Invest the next research or pilot effort in the assumptions that materially affect the decision. If changing a minor cost barely affects the outcome, extensive diligence on that cost may be less valuable than validating conversion. Sensitivity analysis should focus learning, not manufacture certainty. Keep the base assumptions written beside the sensitivity table. Without that context, readers may interpret the upper end as a forecast rather than a conditional calculation, or compare two scenarios that quietly use different customer volumes and cost definitions.

Imagine this

Illustrative operating example

At a hypothetical $100 contribution per sale, 1,000 sales provide $100,000 before fixed costs. If contribution falls to $60, the same volume provides $60,000. That $40,000 difference may matter more than a small increase in website traffic.

Make it practical.

Use this checklist as you read. Checks are not stored.

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