Build an auditing workbench that helps users inspect the assumptions underlying a financial forecast and understand how fragile its conclusions may be.
Allow users to import supported spreadsheets or enter structured assumptions for revenue, pricing, conversion, costs, hiring, churn, and cash timing.
Include:
An assumption registry with sources, owners, dates, and confidence levels.
A dependency graph linking assumptions to calculated outputs.
A detector for missing assumptions and inconsistent units.
A sensitivity analysis identifying which assumptions have the largest modeled impact.
A scenario comparison for optimistic, base, and downside cases.
A stale-assumption review queue.
A comparison between forecasts and actual outcomes when actual data exists.
An audit report explaining which conclusions depend on uncertain inputs.
Do not interpret a low-confidence assumption as a measured fact. Preserve original values, show formulas, and distinguish sensitivity analysis from probability forecasting. Never invent actual financial performance. Include a fictional business forecast with deliberately inconsistent assumptions and testable calculations.
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