The Failure of Risk Management (inbunden)
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Inbunden (Hardback)
Antal sidor
2 ed
John Wiley & Sons Inc
229 x 155 x 36 mm
590 g
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The Failure of Risk Management

Why It's Broken and How to Fix It

Inbunden,  Engelska, 2020-03-23
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A practical guide to adopting an accurate risk analysis methodology The Failure of Risk Management provides effective solutionstosignificantfaults in current risk analysis methods. Conventional approaches to managing risk lack accurate quantitative analysis methods, yielding strategies that can actually make things worse. Many widely used methods have no systems to measure performance, resulting in inaccurate selection and ineffective application of risk management strategies. These fundamental flaws propagate unrealistic perceptions of risk in business, government, and the general public. This book provides expert examination of essential areas of risk management, including risk assessment and evaluation methods, risk mitigation strategies, common errors in quantitative models, and more. Guidance on topics such as probability modelling and empirical inputs emphasizes the efficacy of appropriate risk methodology in practical applications. Recognized as a leader in the field of risk management, author Douglas W. Hubbard combines science-based analysis with real-world examples to present a detailed investigation of risk management practices. This revised and updated second edition includes updated data sets and checklists, expanded coverage of innovative statistical methods, and new cases of current risk management issues such as data breaches and natural disasters. Identify deficiencies in your current risk management strategy and take appropriate corrective measures Adopt a calibrated approach to risk analysis using up-to-date statistical tools Employ accurate quantitative risk analysis and modelling methods Keep pace with new developments in the rapidly expanding risk analysis industry Risk analysis is a vital component of government policy, public safety, banking and finance, and many other public and private institutions. The Failure of Risk Management: Why It's Broken and How to Fix It is a valuable resource for business leaders, policy makers, managers, consultants, and practitioners across industries.
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Fler böcker av Douglas W Hubbard

Övrig information

DOUGLAS W. HUBBARD is the inventor of Applied Information Economics (AIE). His methodology has earned him critical praise from Gartner and Forrester Research. He is also the author of How to Measure Anything: Finding the Value of Intangibles in Business and How to Measure Anything in Cybersecurity Risk. His articles appear in Nature, The American Statistician, The IBM Journal of R&D, InformationWeek and many more. He has over 30 years of experience in management consulting focusing on the application of quantitative methods in decision making


About the Author xi Preface xiii Acknowledgments xvii Part One An Introduction To The Crisis 1 Chapter 1 Healthy Skepticism for Risk Management 3 A Common Mode Failure 5 Key Definitions: Risk Management and Some Related Terms 8 What Failure Means 14 Scope and Objectives of This Book 17 Chapter 2 A Summary of the Current State of Risk Management 21 A Short and Entirely-Too-Superficial History of Risk 21 Current State of Risk Management in the Organization 25 Current Risks and How They are Assessed 26 Chapter 3 How Do We Know What Works? 35 Anecdote: The Risk of Outsourcing Drug Manufacturing 36 Why Its Hard to Know What Works 40 An Assessment of Self-Assessments 44 Potential Objective Evaluations of Risk Management 48 What We May Find 57 Chapter 4 Getting Started: A Simple Straw Man Quantitative Model 61 A Simple One-for-One Substitution 63 The Expert as the Instrument 64 A Quick Overview of Uncertainty Math 67 Establishing Risk Tolerance 72 Supporting the Decision: A Return on Mitigation 73 Making the Straw Man Better 75 Part Two Why Its Broken 79 Chapter 5 The Four Horsemen of Risk Management: Some (Mostly) Sincere Attempts to Prevent an Apocalypse 81 Actuaries 83 War Quants: How World War II Changed Risk Analysis Forever 86 Economists 90 Management Consulting: How a Power Tie and a Good Pitch Changed Risk Management 96 Comparing the Horsemen 103 Major Risk Management Problems to Be Addressed 105 Chapter 6 An Ivory Tower of Babel: Fixing the Confusion about Risk 109 The Frank Knight Definition 111 Knights Influence in Finance and Project Management 114 A Construction Engineering Definition 118 Risk as Expected Loss 119 Defining Risk Tolerance 121 Defining Probability 128 Enriching the Lexicon 131 Chapter 7 The Limits of Expert Knowledge: Why We Dont Know What We Think We Know about Uncertainty 135 The Right Stuff: How a Group of Psychologists Might Save Risk Analysis 137 Mental Math: Why We Shouldnt Trust the Numbers in Our Heads 139 Catastrophic Overconfidence 142 The Mind of Aces: Possible Causes and Consequences of Overconfidence 150 Inconsistencies and Artifacts: What Shouldnt Matter Does 155 Answers to Calibration Tests 160 Chapter 8 Worse Than Useless: The Most Popular Risk Assessment Method and Why It Doesnt Work 163 A Few Examples of Scores and Matrices 164 Does That Come in Medium?: Why Ambiguity Does Not Offset Uncertainty 170 Unintended Effects of Scales: What You Dont Know Can Hurt You 173 Different but Similar-Sounding Methods and Similar but Different-Sounding Methods 183 Chapter 9 Bears, Swans and Other Obstacles to Improved Risk Management 193 Algorithm Aversion and a Key Fallacy 194 Algorithms versus Experts: Generalizing the Findings 198 A Note about Black Swans 203 Major Mathematical Misconceptions 209 Were Special: The Belief That Risk Analysis Might Work, but Not Here 217 Chapter 10 Where Even the Quants Go Wrong: Common and Fundamental Errors in Quantitative Models 223 A Survey of Analysts Using Monte Carlos 224 The Risk Paradox 228 Financial Models and the Shape of Disaster: Why Normal Isnt So Normal 236 Following Your Inner Cow: The Problem with Correlations 243 The Measurement Inversion 248 Is Monte Carlo Too Complicated? 250 Part Three How to Fix It 255 Chapter 11 Starting with What Works 257 Speak the Language 259 Getting Your Probabilities Calibrated 266 Using Data for Initial Benchmarks 272 Checking the Substitution 280 Simple Risk Management 285 Chapter 12 Improving the Model 293 Empirical Inputs 294 Adding Detail to the Model 305 Advanced Methods for Improving Experts Subjective Estimates 312 Other Monte Carlo Tools 315 Self-Examinations for Modelers 317 Chapter 13 The Risk Community: Intra- and Extra-organizational Issues of Risk Management 323 Getting Organized 324