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Occam's Razor

mental-model

Source: Tool Use

Categories: philosophycognitive-science

From: Poor Charlie's Almanack

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A cutting tool mapped onto explanation selection. Among competing hypotheses that equally account for the evidence, prefer the one with the fewest assumptions. The razor metaphor is precise: it does not build or create; it removes. The instrument’s job is to shave away unnecessary complexity, leaving only what is required to explain the observed facts.

The mapping structures how we evaluate explanations:

Munger used Occam’s razor as a guard against over-engineered explanations in investing. When a company’s results can be explained by simple economics (good product, growing market), do not reach for elaborate narratives about visionary management or paradigm shifts. The simplest sufficient explanation is usually the most reliable.

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Origin Story

The principle is attributed to William of Ockham (c. 1287-1347), an English Franciscan friar and scholastic philosopher, though he never stated it in the exact form usually quoted. His actual writings contain formulations like “Plurality must never be posited without necessity” (Pluralitas non est ponenda sine necessitate). The name “Occam’s razor” was applied retroactively, the “razor” metaphor appearing in the seventeenth century to describe principles that “shave away” unnecessary hypotheses.

The principle predates Ockham. Aristotle wrote that “the more limited, if adequate, is always preferable.” Ptolemy stated “we consider it a good principle to explain the phenomena by the simplest hypothesis possible.” But Ockham applied it with particular force to metaphysical debates about universals, cutting away Platonic entities he considered unnecessary.

In the twentieth century, the razor acquired formal grounding through information theory (Kolmogorov complexity), Bayesian model selection (Bayes factors penalize model complexity), and machine learning (regularization as a computational implementation of parsimony). What began as a medieval philosophical intuition turned out to have deep mathematical structure.

Munger included it in his mental models toolkit as a general-purpose filter for evaluating business narratives, investment theses, and causal explanations. His practical deployment: when a company’s stock price requires an elaborate story to justify, the story is probably wrong.

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