fermi-estimation

To estimate market size when precise data is unavailable, decompose the problem into solvable factors, assign optimistic and pessimistic bounds to each, and calculate a most-likely value with traceable sanity checks.

Order-of-magnitude estimation is a technique for deriving approximate quantities when facing data scarcity. You should use it to structure assumptions for market scale, demand, or resource allocation when exact numbers are inaccessible.

Perform a sanity check on uncertain assumptions by validating the derived most-likely value against defined targets, units, geography, and time ranges, ensuring your upper and lower bounds remain logically consistent.

You cannot use Fermi estimation if you need exact solutions or official statistics. This approach explicitly refuses scenarios requiring precise numbers and is designed strictly for providing order-of-magnitude approximations under data scarcity.

The best way to structure assumptions for resource allocation estimates is to define the target, units, geography, and time range upfront, then break the problem into multiple estimable factors with distinct most-likely, optimistic, and pessimistic values.