Occam's Razor (The Principle of Parsimony)

A principle favoring avoidance of unnecessary complexity among explanations that adequately account for relevant evidence. Simplicity must be defined and does not establish truth by itself.

Occam's razor favors avoiding unnecessary complexity when comparing explanations that account adequately for the evidence. Simplicity can concern assumptions, adjustable parameters, or description length, and those measures need not agree. The principle does not say that the shortest story or most familiar explanation is true.

Use parsimony with predictive and explanatory adequacy. A flexible model may fit past data by absorbing noise, while an overly simple one can miss a consequential pattern. Compare performance on relevant new cases and inspect assumptions. Formal Bayesian comparisons depend on specified models and priors; they do not reduce to counting assumptions in ordinary language.

When to use it

When choosing between competing explanations. When designing products, processes, or strategies. When someone proposes a complex solution—ask whether a simpler one would work just as well.

How it can help

Prompts a check that additional assumptions or flexibility improve explanation or prediction enough to justify their cost.