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The Failure of Risk Management
The Failure of Risk Management (Why It's Broken and How to Fix It) by Douglas W. Hubbard
Key Takeaways
Qualitative Metrics Must Be Avoided
Qualitative risk analysis (i.e. risk matrices, scoring charts) departs from legitimate statistical methodology and has no robust evidence to suggest its efficacy. There is good reason to believe that such methods are deleterious to their intended purpose in contradiction to the common response that they are "better than nothing".
Utility as a Measure of Value
Expected Value (Probability × Magnitude) alone can not predict or inform risky decisions, except for risk-neutral parties. People and organizations are risk-averse ...
- Finish this paragraph. (see chapter 6) ➕ 2025-07-04
Expert Opinion Must Be Adjusted
Expert opinion is valuable despite its flaws. ...
The book details the statistically observable tendency for people to underestimate risk and to be overconfident in their beliefs. It describes the process of "calibration" by which people can be trained to compensate for this bias and make predictions far more accurately.
Experts tend to be good at creating heuristics, but do not apply them consistently in practice.
[!example] Chapter 7 describes a study where experts were shown to estimate risk differently for identical cases.
Luck Looks Like Skill
Chapter 7 p.154
Hubbard describes a study which concluded that, given the number of German pilots and their overall victory/defeat figures, there was a ~30% chance an individual would achieve The Red Baron's record by luck alone.
He later refers to the tendency to overvalue competence in the role of achieving improbable accomplishments as the "Red Baron effect".
There's Always Enough Data
Hubbard challenges the popular rebuttal that X industry lacks the data to use quantitative models.
[!quote] Fallacy of Close Analogy - p.236 ...the belief that unless two things are identical in every way, nothing learned from one can be applied to the other.
Mentioned Topics and Abbreviations
- Analytic Hierarchy Process (AHP)
- Multi-Attribute Utility Theory (MAUT)
- Actuarial Science
- Options Theory (OT)
- Modern Portfolio Theory (MPT)
- Probabalistic Risk Analysis (PRA)
- Value at Risk (VaR)
- Loss-Exceedance Curve (LEC)
- Risk Tolerance
Critiques
Exsupero Ursus
Chapter 9 p.195
Hubbard uses exsupero ursus to describe the tendency of his detractors to dismiss quantitative methods as inappropriate to their industry-specific risks. He provides another analogy in which one car is picked of two (ordinary) cars because the other car can't fly. Based on this strawman it is clear Hubbard believes his detractors are correct that qualitative methods can not capture the entire nuance of risk probability, but that they are failing to acknowledge that their preferred alternatives are not demonstrably more effective at doing so. The nuance Hubbard dismisses without addressing is the possibility of model improvement. A most competant detractor would be aware of the apparent contradiction but argue that their methods will eventually surpass quantitative methods if they are further developed. Such a position would additionally contextualize Hubbard's observations that detractors become emotional in their defense. To them, Hubbards methods represent an attractive short-term gain excluding a long-term payoff.
Hubbard's dismissal rubs me wrong because it reads exactly as he describes the "at least we're doing something" argument throughout the book and just pages earlier.