Fermi Estimation

Overview

Fermi estimation, named after physicist Enrico Fermi, is the art of making reasonable estimates for quantities that seem impossible to know without direct measurement. By decomposing a question into factors you can estimate, then multiplying, you often get surprisingly accurate order-of-magnitude results.

Core Principle: Break the unknown into known (or estimable) pieces. Even rough estimates combine to reasonable accuracy due to errors canceling out.

Trigger Card

When you need a number you can't measure or look up, and order-of-magnitude is enough:

1. Decompose: Quantity = Factor₁ × Factor₂ × ... × Factorₙ (by component, by rate×time, or by population×fraction).
2. Estimate each factor with a range, not a point; use geometric mean for order-of-magnitude; round to one significant figure.
3. Multiply and sanity-check: Does the order of magnitude make sense? Would a 10× error change the decision?
4. Report: "~X, within 3-5×" — never false precision.

If the number is lookup-able (COUNT(*), pricing page, profile it), do that instead — a made-up estimate where a real value exists is strictly worse.