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

by Douglas W. Hubbard

• ISBN13: 9780470483435
• ISBN10: 0470483431
• Format: eBook
• Copyright: 2009-04-01
• Publisher: Wiley

Summary

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.

Table of Contents

Preface

Acknowledgments

An Introduction To The Crisis

Healthy Skepticism for Risk Management

Common Mode Failure

What Counts as Risk Management

Anecdote: The Risk of Outsourcing Drug Manufacturing

What Failure Means

Scope and Objectives of This Book

Risk Management: A Very Short Introduction to Where We've Been and Where (We Think) We Are

The Entire History of Risk Management (in 800 Words or Less)

Methods of Assessing Risks

Risk Mitigation

The State of Risk Management According to Surveys

How Do We Know What Works?

An Assessment of Self-Assessments

Potential Objective Evaluations of Risk Management

What We May Find

WHY IT'S BROKEN

The "Four Horsemen" of Risk Management: Some (Mostly) Sincere Attempts to Prevent an Apocalypse

Actuaries

War Quants: How World War II Changed Risk Analysis Forever

Economists

Management Consulting: How a Power Tie and a Good Pitch Changed Risk Management

Comparing the Horsemen

Major Risk Management Problems to Be Addressed

An Ivory Tower of Babel: Fixing the Confusion about Risk

The Frank Knight Definition

Risk as Volatility

A Construction Engineering Definition

Risk as Expected Loss

Risk as a Good Thing

Risk Analysis and Risk Management versus Decision Analysis

Enriching the Lexicon

The Limits of Expert Knowledge: Why We Don't Know What We Think We Know about Uncertainty

The Right Stuff: How a Group of Psychologists Saved Risk Analysis

Mental Math: Why We Shouldn't Trust the Numbers in Our Heads

"Catastrophic" Overconfidence

The Mind of "Aces": Possible Causes and Consequences of Overconfidence

Inconsistencies and Artifacts: What Shouldn't Matter Does

Answers to Calibration Tests

Worse Than Useless: The Most Popular Risk Assessment Method and Why It Doesn't Work

A Basic Course in Scoring Methods (Actually, It's the Advanced Course, Too-There's Not Much to Know)

Does That Come in ''Medium''?: Why Ambiguity Does Not Offset Uncertainty

Unintended Effects of Scales: What You Don't Know Can Hurt You

Clarification of Scores and Preferences: Different but Similar-Sounding Methods and Similar but Different-Sounding Methods

Black Swans, Red Herrings, and Invisible Dragons: Overcoming Conceptual Obstacles to Improved Risk Management

Risk and Righteous Indignation: The Belief that Quantitative Risk Analysis Is Impossible

A Note about Black Swans

Frequentist versus Subjectivist

We're Special: The Belief that Risk Analysis Might Work, But Not Here

Where Even the Quants Go Wrong: Common and Fundamental Errors in Quantitative Models

Introduction to Monte Carlo Concepts

Survey of Monte Carlo Users

The Risk Paradox

The Measurement Inversion

Where's the Science? The Lack of Empiricism in Risk Models

Financial Models and the Shape of Disaster: Why Normal Isn't so Normal

Following Your Inner Cow: The Problem with Correlations

"That's Too Uncertain": How Modelers Justify Excluding the Biggest Risks

Is Monte Carlo Too Complicated?

How To Fix It

The Language of Uncertain Systems: The First Step Toward Improved Risk Management

Getting Your Probabilities Calibrated

The Model of Uncertainty: Decomposing Risk with Monte Carlos

Decomposing Probabilities: Thinking about Chance the Way You Think about a Budget

A Few Modeling Principles

Modeling the Mechanism

The Outward-Looking Modeler: Adding Empirical Science to Risk

Why Your Model Won't Behave

Empirical Inputs

Introduction to Bayes: One Way to Get around that "Limited Data for Disasters" Problem

Self-Examinations for Modelers Who Care about Quality

The Risk Community: Intra- and Extraorganizational Issues of Risk Management

Getting Organized

Managing the Global Probability Model

Incentives for a Calibrated Culture

Extraorganizational Issues: Solutions beyond Your Office Building

Miscellaneous Topics

Final Thoughts on Quantitative Models and Better Decisions

Appendix Calibration Tests and Answers

Index

Table of Contents provided by Publisher. All Rights Reserved.