STRATEGYWeeks to result

The Bad Decision Taxonomy

Twelve systematic failure modes that produce catastrophic choices

Problem it solves

bad decision taxonomy

Best for

Leaders, investors, and decision-makers who want a comprehensive checklist of systematic failure modes to audit their decision process against before committing to major choices.

Not ideal for

Routine daily decisions that do not warrant systematic bias checking, or situations where speed is more important than decision quality.

Overview

Why this framework exists

Morgan Housel's Bad Decision Taxonomy catalogs twelve systematic causes of terrible decisions, building on Massimo Piattelli-Palmarini's research on repeated human mistakes. The taxonomy is not about occasional errors but about structural failure modes that produce reliably bad outcomes across individuals, organizations, and civilizations. The twelve causes include: incentive-driven boundary stretching (financial rewards that gradually expand moral limits), tribal loyalty blindness (group membership that discourages challenging flawed ideas), tail risk underestimation (focusing on comfortable consequence ranges while ignoring catastrophic possibilities), compounding error blindness (small mistakes accumulating invisibly into major problems), self-justification asymmetry (excusing your own flaws while spotting others'), overconfidence in certainty (preferring assumed 100% success odds over realistic 60%), insufficient margins of safety, misreading adaptation (assuming permanent conditions), playing different games (following advice from people with different goals), stress response miscalculation (overestimating risk tolerance during calm periods), past success bias (previous wins creating overconfidence), and incomplete information (focusing only on measurable data while missing crucial unmeasurable factors). Each cause operates independently but they frequently compound, producing decisions that are catastrophically wrong despite feeling thoroughly analyzed.

Core principles

4 total
  1. Most bad decisions are produced by systematic failure modes, not random error.
  2. Financial incentives stretch moral boundaries further than people anticipate.
  3. Small mistakes compound invisibly into catastrophic problems.
  4. Imagined risk tolerance during calm periods differs dramatically from actual tolerance under stress.

Steps

3 steps
  1. Audit your decision against the twelve failure modes
    Before committing to any major decision—investment, hire, partnership, strategy change—systematically check it against each of the twelve failure modes. Ask: Are financial incentives causing me to stretch boundaries? Am I suppressing concerns to maintain tribal loyalty? Am I ignoring tail-end consequences? Could small errors be compounding into larger ones? Am I excusing my own reasoning while criticizing others'? Am I assuming certainty where probability exists? Do I have adequate margins of safety? Am I assuming current conditions are permanent? Am I following advice from someone playing a different game? Am I overestimating my stress tolerance? Is past success making me overconfident? Am I missing crucial unmeasurable factors? This systematic audit takes 15-20 minutes but prevents the most common categories of catastrophic error.
    Pro tipCreate a physical checklist card with all twelve failure modes and review it before every major decision. The systematic process catches errors that intuitive decision-making misses.
    WarningDo not use this as an excuse for analysis paralysis. The audit should take 15-20 minutes, not weeks. Its purpose is to catch obvious structural errors, not to achieve certainty.
  2. Identify which failure modes you are most susceptible to
    Review your past bad decisions and categorize them according to the twelve failure modes. Most people have two or three dominant failure patterns that produce the majority of their errors. A competitive person might be consistently susceptible to past success bias and overconfidence in certainty. A people-pleaser might be vulnerable to tribal loyalty blindness and self-justification asymmetry. A quantitative person might fall prey to incomplete information bias (over-relying on measurable data). Identifying your personal top three failure modes allows you to build targeted countermeasures for the specific biases that most frequently trip you up.
    Pro tipAsk three trusted colleagues to independently identify your most common decision-making failure modes. Their observations will differ from your self-assessment in revealing ways.
  3. Build structural countermeasures for your top failure modes
    For each of your top two or three failure modes, create a structural countermeasure that does not depend on willpower or self-awareness in the moment. If tribal loyalty blindness is your weakness, designate a trusted outsider who is explicitly empowered to challenge group consensus. If stress response miscalculation is your pattern, pre-commit to rules that constrain your behavior during high-stress periods (investment stop-losses, mandatory cooling-off periods before major decisions). If incentive-driven boundary stretching is your risk, define ethical boundaries in writing during calm periods and make them visible to others who will hold you accountable. Structural countermeasures are more reliable than self-awareness because they operate even when the bias is actively distorting your judgment.
    Pro tipWrite your countermeasures as 'when-then' rules: 'When I feel certain about an investment, then I will assume I am overconfident and reduce position size by 30%.'
    WarningCountermeasures that require you to notice your own bias in real-time will fail most of the time. Design countermeasures that activate automatically through external triggers, accountability partners, or pre-committed rules.

Checklist

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Examples

2 cases
The Great Depression as compounding error

Housel uses the Great Depression as a prime example of compounding error blindness. No single event caused the Depression—it resulted from multiple individually manageable problems occurring simultaneously: a stock market crash, banking panics, poor agricultural harvests, protectionist trade policies, and monetary policy mistakes. Each problem alone would have been recoverable. But when they compounded simultaneously, they produced a catastrophe that no individual risk assessment had anticipated. This demonstrates how small, seemingly unrelated errors can combine into outcomes that exceed any single failure mode.

OutcomeA decade-long economic catastrophe produced by the compounding of individually manageable problems, demonstrating that the interaction of small errors can produce outcomes catastrophically worse than any single error
Morgan Housel, Common Causes of Very Bad Decisions, Collaborative Fund
Robert McNamara's Vietnam statistical failures

Housel references Robert McNamara's approach to the Vietnam War as an example of incomplete information bias. McNamara, a former Ford Motor Company president, applied rigorous quantitative analysis to the war effort—tracking body counts, territory controlled, and material destroyed. But as Housel notes, the statistics 'could not quantify the feelings of the Vietnamese people.' The unmeasurable factors—national identity, determination, cultural resistance—proved far more decisive than any measurable metric. The most sophisticated quantitative analysis produced catastrophically wrong conclusions because it systematically excluded the most important variables.

OutcomeA war strategy built on measurable metrics failed catastrophically because the decisive factors were unmeasurable, demonstrating that focusing only on quantifiable data creates dangerous blind spots
Morgan Housel, Common Causes of Very Bad Decisions

Common mistakes

3 traps
Believing awareness of biases prevents them
Knowing about cognitive biases does not make you immune to them. Housel's failure modes operate at a structural level that awareness alone cannot overcome. A person who knows about overconfidence can still be overconfident. Structural countermeasures—rules, accountability systems, and external checks—are required because self-awareness is insufficient.
Applying the checklist only to others' decisions
One of the twelve failure modes is self-justification asymmetry: people easily spot others' biases while remaining blind to their own. The most common misuse of the taxonomy is using it to critique others' decisions while exempting your own from the same scrutiny.
Treating the taxonomy as exhaustive
Twelve failure modes cover the most common structural causes of bad decisions but are not comprehensive. Novel failure modes emerge from new technologies, unprecedented situations, and unique personal circumstances. The taxonomy is a starting point for decision auditing, not a complete list of everything that can go wrong.

Origin story

How this framework came to be

Housel published this essay on the Collaborative Fund blog in 2019, building on Italian psychologist Massimo Piattelli-Palmarini's work cataloging factors behind repeated human mistakes. Housel expanded Piattelli-Palmarini's list with additional causes drawn from his own research on financial history, behavioral economics, and organizational failure. The essay was particularly influenced by Housel's study of the Great Depression—which he uses as an example of compounding errors where multiple manageable problems (stock crashes, banking panics, poor harvests) combined destructively when occurring simultaneously. He also drew on Ben Graham's margin of safety concept, Robert McNamara's Vietnam War statistical failures, and the persistent pattern of investors who overestimate their risk tolerance during calm periods only to panic-sell during actual downturns. The taxonomy emerged as Housel's attempt to create a pre-flight checklist for decision-making—a systematic way to audit important decisions against the most common structural failure modes before committing resources.

Source

Traced to primary
Source · ESSAY
Common Causes of Very Bad Decisions
Morgan Housel · 2019
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