Stress-test a forecast before anyone commits to it: the embedded assumptions, the base-rate comparison, and the sensitivity of the answer to each guess.
Sanity-check this forecast: {{forecast}} (the numbers, the method, the assumptions stated or implied, what decisions ride on it).
Stress it: extract every assumption (including the silent ones — 'churn stays flat', 'no seasonality', 'capacity is infinite'), compare against base rates (does this require being better than history? than typical companies? say by how much), sensitivity-rank the assumptions (which single guess moves the answer most — that one deserves the research), the scenario the forecast ignores (the plausible bad case), and a verdict: is this a forecast or a target wearing a forecast's clothes? Suggest the honest range to present instead of the point estimate.
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