False Precision

You're seeing False Precision when a financial model projects revenue to the dollar five years out, or when a market sizing deck quotes a TAM to the tenth of a billion. The spreadsheet creates confidence the inputs don't warrant.

You're seeing False Precision when a team reports "customer satisfaction is 78.3%" from a survey of 40 people. The decimal place implies reliability that the sample size can't support.

Present your forecasts as ranges, not point estimates, especially to investors and your team. A range signals honesty and sophistication; false precision signals either naivety or manipulation. Save decimal-point precision for data you actually have.

Buffett famously said he'd rather be approximately right than precisely wrong — a direct rejection of false precision. He avoids complex financial models with spurious decimal places, preferring rough estimates of intrinsic value within a wide margin of safety. His approach: if you need three decimal places to justify a decision, the decision probably isn't clear enough. Founders can apply this by resisting the urge to dress up uncertain forecasts in precise numbers. When pitching investors or planning strategy, state your confidence level honestly. Use ranges and orders of magnitude for unknowns, and reserve precision for what you can actually measure. Buffett's success demonstrates that intellectual honesty about what you don't know is more valuable than fake exactness.