Forecast Assumptions Audit: Which Numbers Drive the Result?
Find the assumptions that matter most and test them.
Added October 15, 2026. Written with AI assistance and checked for clarity and placeholders; not reviewed by a lawyer, accountant, clinician or other professional. How these prompts are made
The Open buttons send the prompt text as currently shown below to that site only when you click. Fill in the placeholders first.
Audit the assumptions in my forecast. The forecast and its assumptions: [FORECAST_AND_ASSUMPTIONS]. The decision it supports: [DECISION]. The evidence behind each assumption: [EVIDENCE]. List every assumption (growth rate, price, volume, costs, timing, churn, collection days) with value, source, and confidence (high, medium, low). Run a sensitivity table changing each key assumption by plus and minus 10 percent and show the effect on the result with the arithmetic for at least three. Rank assumptions by impact and by uncertainty. Identify the top three to research further and how. Build three scenarios (low, base, high) and describe the decision under each. Add warning signs to track monthly that would show which scenario is happening. This is analysis support, not advice. Do not invent evidence for assumptions. Add a worked sensitivity row: revenue assumption 100,000, cost ratio 70 percent, profit 30,000; if the cost ratio is 73 percent, profit is 27,000 (a 3,000 or 10 percent fall), while a 10 percent revenue drop alone gives 27,000 as well, so both assumptions need evidence.
Fill in before use
Optional: type your details and the prompt above updates. Nothing is saved or sent.
Replace each bracketed placeholder with your own details, then paste into Any AI or another assistant.