The Failure of Risk Management Why It's Broken and How to Fix It

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  • Edition: 1st
  • Format: Hardcover
  • Copyright: 2009-04-27
  • Publisher: Wiley

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An essential guide to the calibrated risk analysis approachThe Failure of Risk Management takes a close look at misused and misapplied basic analysis methods and shows how some of the most popular "risk management" methods are no better than astrology! Using examples from the 2008 credit crisis, natural disasters, outsourcing to China, engineering disasters, and more, Hubbard reveals critical flaws in risk management methodsand shows how all of these problems can be fixed. The solutions involve combinations of scientifically proven and frequently used methods from nuclear power, exploratory oil, and other areas of business and government. Finally, Hubbard explains how new forms of collaboration across all industries and government can improve risk management in every field.Douglas W. Hubbard (Glen Ellyn, IL) is the inventor of Applied Information Economics (AIE) and the author of Wiley's How to Measure Anything: Finding the Value of Intangibles in Business (978-0-470-11012-6), the #1 bestseller in business math on Amazon. He has applied innovative risk assessment and risk management methods in government and corporations since 1994.

Author Biography

Douglas W. Hubbard is the inventor of Applied Information Economics (AIE). He is an internationally recognized expert in the field of measuring intangibles, risks, and value, especially in IT value, and is a popular speaker at numerous conferences. He has written articles for InformationWeek, CIO Enterprise, and DBMS magazine. His AIE method has been applied to dozens of large Fortune 500 IT investments, military logistics, venture capital, aerospace, and environmental issues. Doug is the author of How to Measure Anything: Finding the Value of Intangibles in Business (Wiley).

Table of Contents

Prefacep. xi
Acknowledgmentsp. xv
An Introduction to the Crisisp. 1
Healthy Skepticism for Risk Managementp. 3
Common Mode Failurep. 4
What Counts as Risk Managementp. 8
Anecdote: The Risk of Outsourcing Drug Manufacturingp. 11
What Failure Meansp. 16
Scope and Objectives of This Bookp. 18
Risk Management: A Very Short Introduction to Where We've Been and Where (We Think) We Arep. 21
The Entire History of Risk Management (in 800 Words or Less)p. 22
Methods of Assessing Risksp. 24
Risk Mitigationp. 26
The State of Risk Management According to Surveysp. 31
How Do We Know What Works?p. 37
An Assessment of Self-Assessmentsp. 37
Potential Objective Evaluations of Risk Managementp. 42
What We May Findp. 49
Why It's Brokenp. 53
The "Four Horsemen" of Risk Management: Some (Mostly) Sincere Attempts to Prevent an Apocalypsep. 55
Actuariesp. 57
War Quants: How World War II Changed Risk Analysis Foreverp. 59
Economistsp. 63
Management Consulting: How a Power Tie and a Good Pitch Changed Risk Managementp. 68
Comparing the Horsemenp. 74
Major Risk Management Problems to Be Addressedp. 76
An Ivory Tower of Babel: Fixing the Confusion about Riskp. 79
The Frank Knight Definitionp. 81
Risk as Volatilityp. 84
A Construction Engineering Definitionp. 86
Risk as Expected Lossp. 86
Risk as a Good Thingp. 88
Risk Analysis and Risk Management versus Decision Analysisp. 90
Enriching the Lexiconp. 91
The Limits of Expert Knowledge: Why We Don't Know What We Think We Know about Uncertaintyp. 95
The Right Stuff: How a Group of Psychologists Saved Risk Analysisp. 97
Mental Math: Why We Shouldn't Trust the Numbers in Our Headsp. 99
"Catastrophic" Overconfidencep. 102
The Mind of "Aces": Possible Causes and Consequences of Overconfidencep. 107
Inconsistencies and Artifacts: What Shouldn't Matter Doesp. 111
Answers to Calibration Testsp. 115
Worse Than Useless: The Most Popular Risk Assessment Method and Why It Doesn't Workp. 117
A Basic Course in Scoring Methods (Actually, It's the Advanced Course, Too-There's Not Much to Know)p. 118
Does That Come in "Medium"?: Why Ambiguity Does Not Offset Uncertaintyp. 123
Unintended Effects of Scales: What You Don't Know Can Hurt Youp. 130
Clarification of Scores and Preferences: Different but Similar-Sounding Methods and Similar but Different-Sounding Methodsp. 135
Black Swans, Red Herrings, and Invisible Dragons: Overcoming Conceptual Obstacles to Improved Risk Managementp. 145
Risk and Righteous Indignation: The Belief that Quantitative Risk Analysis Is Impossiblep. 146
A Note about Black Swansp. 151
Frequentist versus Subjectivistp. 158
We're Special: The Belief that Risk Analysis Might Work, But Not Herep. 161
Where Even the Quants Go Wrong: Common and Fundamental Errors in Quantitative Modelsp. 167
Introduction to Monte Carlo Conceptsp. 168
Survey of Monte Carlo Usersp. 172
The Risk Paradoxp. 174
The Measurement Inversionp. 176
Where's the Science? The Lack of Empiricism in Risk Modelsp. 178
Financial Models and the Shape of Disaster: Why Normal Isn't so Normalp. 181
Following Your Inner Cow: The Problem with Correlationsp. 187
"That's Too Uncertain": How Modelers Justify Excluding the Biggest Risksp. 191
Is Monte Carlo Too Complicated?p. 195
How to Fix Itp. 199
The Language of Uncertain Systems: The First Step Toward Improved Risk Managementp. 201
Getting Your Probabilities Calibratedp. 203
The Model of Uncertainty: Decomposing Risk with Monte Carlosp. 208
Decomposing Probabilities: Thinking about Chance the Way You Think about a Budgetp. 212
A Few Modeling Principlesp. 213
Modeling the Mechanismp. 215
The Outward-Looking Modeler: Adding Empirical Science to Riskp. 221
Why Your Model Won't Behavep. 223
Empirical Inputsp. 224
Introduction to Bayes: One Way to Get around that "Limited Data for Disasters" Problemp. 227
Self-Examinations for Modelers Who Care about Qualityp. 233
The Risk Community: Intra-and Extraorganizational Issues of Risk Managementp. 241
Getting Organizedp. 242
Managing the Global Probability Modelp. 244
Incentives for a Calibrated Culturep. 250
Extraorganizational Issues: Solutions beyond Your Office Buildingp. 254
Miscellaneous Topicsp. 256
Final Thoughts on Quantitative Models and Better Decisionsp. 258
Appendix Calibration Tests and Answersp. 261
Indexp. 273
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