This title is now updated with new research and even more intuitive explanations, a demystifying explanation of how managers can inform themselves to make less risky, more profitable business decisions. This insightful and eloquent book will show you how to measure those things in your own business that, until now, you may have considered 'immeasurable', including customer satisfaction, organizational flexibility, technology risk, and technology ROI. It adds even more intuitive explanations of powerful measurement methods and shows how they can be applied to areas such as risk management and customer satisfaction. It continues to boldly assert that any perception of 'immeasurability' is based on certain popular misconceptions about measurement and measurement methods. This title shows the common reasoning for calling something immeasurable, and sets out to correct those ideas. It offers practical methods for measuring a variety of 'intangibles'. It also adds recent research, especially in regards to methods that seem like measurement, but are in fact a kind of 'placebo effect' for management - and explains how to tell effective methods from management mythology. Written by recognized expert Douglas Hubbard - creator of "Applied Information Economics" - "How to Measure Anything, Second Edition" illustrates how the author has used his approach across various industries and how any problem, no matter how difficult, ill defined, or uncertain can lend itself to measurement using proven methods.

Table of Contents

Preface xi Acknowledgments xv SECTION I MEASUREMENT: THE SOLUTION EXISTS 1 CHAPTER 1 Intangibles and the Challenge 3 Yes, I Mean Anything 5 The Proposal 6 CHAPTER 2 An Intuitive Measurement Habit: Eratosthenes, Enrico, and Emily 9 How an Ancient Greek Measured the Size of Earth 10 Estimating: Be Like Fermi 11 Experiments: Not Just for Adults 13 Notes on What to Learn from Eratosthenes, Enrico, and Emily 18 CHAPTER 3 The Illusion of Intangibles: Why Immeasurables Aren't 21 The Concept of Measurement 22 The Object of Measurement 26 The Methods of Measurement 28 Economic Objections to Measurement 35 The Broader Objection to the Usefulness of "Statistics" 37 Ethical Objections to Measurement 39 Toward a Universal Approach to Measurement 41 SECTION II BEFORE YOU MEASURE 45 CHAPTER 4 Clarifying the Measurement Problem 47 Getting the Language Right: What "Uncertainty" and "Risk" Really Mean 49 Examples of Clarification: Lessons for Business from, of All Places, Government 51 CHAPTER 5 Calibrated Estimates: How Much Do You Know Now? 57 Calibration Exercise 59 Further Improvements on Calibration 64 Conceptual Obstacles to Calibration 65 The Effects of Calibration 71 CHAPTER 6 Measuring Risk through Modeling 79 How Not to Measure Risk 79 Real Risk Analysis: The Monte Carlo 81 An Example of the Monte Carlo Method and Risk 82 Tools and Other Resources for Monte Carlo Simulations 91 The Risk Paradox and the Need for Better Risk Analysis 93 CHAPTER 7 Measuring the Value of Information 99 The Chance of Being Wrong and the Cost of Being Wrong: Expected Opportunity Loss 100 The Value of Information for Ranges 103 The Imperfect World: The Value of Partial Uncertainty Reduction 107 The Epiphany Equation: How the Value of Information Changes Everything 110 Summarizing Uncertainty, Risk, and Information Value: The First Measurements 114 SECTION III MEASUREMENT METHODS 117 CHAPTER 8 The Transition: From What to Measure to How to Measure 119 Tools of Observation: Introduction to the Instrument of Measurement 120 Decomposition 124 Secondary Research: Assuming You Weren't the First to Measure It 127 The Basic Methods of Observation: If One Doesn't Work, Try the Next 128 Measure Just Enough 131 Consider the Error 132 Choose and Design the Instrument 136 CHAPTER 9 Sampling Reality: How Observing Some Things Tells Us about All Things 139 Building an Intuition for Random Sampling: The Jelly Bean Example 141 A Little about Little Samples: A Beer Brewer's Approach 142 Statistical Significance: A Matter of Degree 145 When Outliers Matter Most 148 The Easiest Sample Statistics Ever 150 A Biased Sample of Sampling Methods 153 Measure to the Threshold 162 Experiment 165 Seeing Relationships in the Data: An Introduction to Regression Modeling 169 One Thing We Haven't Discussed-and Why 174 CHAPTER 10 Bayes: Adding to What You Know Now 177 Simple Bayesian Statistics 178 Using Your Natural Bayesian Instinct 181 Heterogeneous Benchmarking: A "Brand Damage" Application 187 Bayesian Inversion for Ranges: An Overview 190 Bayesian Inversion for Ranges: The Details 193 The Lessons of Bayes 196 SECTION IV BEYOND THE BASICS 201 CHAPTER 11 Preference and Attitudes: The Softer Side of Measurement 203 Observing Opinions, Values, and the Pursuit of Happiness 203 A Willingness to Pay: Measuring Value via Trade-offs 207 Putting It All on the Line: Quantifying Risk Tolerance 211 Quantifying Subjective Trade-offs: Dealing with Multiple Conflicting Preferences 214 Keeping the Big Picture in Mind: Profit Maximization versus Purely Subjective Trade-offs 218 CHAPTER 12 The Ultimate Measurement Instrument: Human Judges 221 Homo absurdus: The Weird Reasons behind Our Decisions 222 Getting Organized: A Performance Evaluation Example 227 Surprisingly Simple Linear Models 228 How to Standardize Any Evaluation: Rasch Models 230 Removing Human Inconsistency: The Lens Model 234 Panacea or Placebo?: Questionable Methods of Measurement 238 Comparing the Methods 246 CHAPTER 13 New Measurement Instruments for Management 251 The Twenty-First-Century Tracker: Keeping Tabs with Technology 251 Measuring the World: The Internet as an Instrument 254 Prediction Markets: A Dynamic Aggregation of Opinions 257 CHAPTER 14 A Universal Measurement Method: Applied Information Economics 265 Bringing the Pieces Together 266 Case: The Value of the System that Monitors Your Drinking Water 270 Case: Forecasting Fuel for the Marine Corps 275 Ideas for Getting Started: A Few Final Examples 281 Summarizing the Philosophy 287 APPENDIX Calibration Tests (and Their Answers) 289 Index 299

About the Author

DOUGLAS W. HUBBARD is the inventor of Applied Information Economics (AIE), a measurement methodology that has been used in IT portfolios, entertainment media, military logistics, R&D portfolios, and many more areas where big decisions are based on factors that seem difficult or impossible to measure. He is an internationally recognized expert in metrics, decision analysis, and risk management, and is a popular speaker at numerous conferences. He has written articles for InformationWeek, CIO Enterprise, Architecture Boston, Analytics and OR/MS Today and is also the author of The Failure of Risk Management: Why It's Broken and How to Fix It.