How to measure anything workbook : finding the value of "intangibles" in business

**Now updated with new measurement methods and new examples, __How to Measure Anything__ shows managers how to inform themselves in order 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, government agency or other organization that, until now, you may have considered "immeasurable," including customer satisfaction, organizational flexibility, technology risk, and technology ROI. * Adds new measurement methods, showing how they can be applied to a variety of areas such as risk management and customer satisfaction * Simplifies overall content while still making the more technical applications available to those readers who want to dig deeper * Continues to boldly assert that any perception of "immeasurability" is based on certain popular misconceptions about measurement and measurement methods * Shows the common reasoning for calling something immeasurable, and sets out to correct those ideas * Offers practical methods for measuring a variety of "intangibles" * Provides an online database (www.howtomeasureanything.com) of downloadable, practical examples worked out in detailed spreadsheets Written by recognized expert Douglas Hubbard—creator of Applied Information Economics—__How to Measure Anything, Third 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. How to Measure Anything 3 Contents 9 Preface to the Third Edition 15 About the Companion Website 19 Acknowledgments 21 About the Author 23 Part I The Measurement Solution Exists 25 Chapter 1 The Challenge of Intangibles 27 The Alleged Intangibles 28 Yes, I Mean Anything 29 The Proposal: It’s about Decisions 31 A “Power Tools” Approach to Measurement 34 A Guide to the Rest of the Book 35 Chapter 2 An Intuitive Measurement Habit: Eratosthenes, Enrico, and Emily 39 How an Ancient Greek Measured the Size of Earth 40 Estimating: Be Like Fermi 41 Experiments: Not Just for AduLts 44 Notes on What to Learn from Eratosthenes, Enrico, and Emily 49 Notes 51 Chapter 3 The Illusion of Intangibles: Why Immeasurables Aren’t 53 The Concept of Measurement 54 A Definition of Measurement: An “Information Theory” Version 55 A Variety of Measurement Scales 56 Bayesian Measurement: A Pragmatic Concept for Decisions 58 The Object of Measurement 61 The Methods of Measurement 64 The Power of Small Samples: The Rule of Five 66 Even Smaller Samples: The Urn of Mystery 68 Our Small-Sample Intuition versus Math 70 Economic Objections to Measurement 72 The Broader Objection to the Usefulness of “Statistics” 76 Ethical Objections to Measurement 79 Reversing Old Assumptions 82 It’s Been Measured Before 83 You Have Far More Data than You Think 84 You Need Far Less Data than You Think 86 Useful, New Observations Are More Accessible than You Think 88 Notes 89 Part II Before You Measure 93 Chapter 4 Clarifying the Measurement Problem 95 Toward a Universal Approach to Measurement 97 The Unexpected Challenge of Defining a Decision 98 Decision-Oriented Measurements: For Scientists, Too 100 How to Get to a Real Decision 101 Requirements for a Decision 102 Potential Forms of a Decision 103 If You Understand it, You Can Model it 104 Getting the Language Right: What “Uncertainty” and “Risk” Really Mean 107 An Example of a Clarified Decision 108 Notes 114 Chapter 5 Calibrated Estimates: How Much Do You Know Now? 117 Calibration Exercise 119 Calibration Trick: Bet Money (or Even Just Pretend To) 125 Further Improvements on Calibration 128 Conceptual Obstacles to Calibration 130 The Effects of Calibration Training 135 Notes 142 Chapter 6 Quantifying Risk through Modeling 147 How Not to Quantify Risk 147 Real Risk Analysis: The Monte Carlo 149 An Example of the Monte Carlo Method and Risk 151 Tools and Other Resources for Monte Carlo Simulations 160 The Risk Paradox and the Need for Better Risk Analysis 164 Notes 167 Chapter 7 Quantifying the Value of Information 169 The Chance of Being Wrong and the Cost of Being Wrong: Expected Opportunity Loss 170 The Value of Information for Ranges 173 Beyond yes/no: Decisions on a Continuum 180 The Imperfect World: The Value of Partial Uncertainty Reduction 183 Perishable Information Values 187 Information Values for Multiple Variables 188 The Epiphany Equation: How the Value of Information Changes Everything 190 Summarizing Uncertainty, RisK, and Information Value: The pre-measurements 195 Notes 196 Part III Measurement Methods 197 Chapter 8 The Transition: From What to Measure to How to Measure 199 Tools of Observation: Introduction to the Instrument of Measurement 201 Decomposition 204 Secondary Research: Assuming You Weren’t the First to Measure It 208 The Basic Methods of Observation: If One Doesn’t Work, Try the Next 210 Measure Just Enough 212 Consider the Error 213 Choose and Design the Instrument 218 Note 220 Chapter 9 Sampling Reality: How Observing Some Things Tells Us about All Things 221 Building an Intuition for Random Sampling: The Jelly Bean Example 223 A Little About Little Samples: A Beer Brewer’s Approach 224 Are Small Samples Really “Statistically Significant”? 228 When Outliers Matter Most 232 The Easiest Sample Statistic Ever 234 A Biased Sample of Sampling Methods 238 Population Proportion Sampling 240 Spot Sampling 242 Serial Sampling 244 Measure to the Threshold 246 . . . And a Lot More 249 Experiment 250 An Example Experiment 252 Now, More about the Meaning of Significance 254 The Significance of Emily Rosa’s Experiment: A Counterfactual Outcome 256 Seeing Relationships in the Data: An Introduction to Regression modeling 259 A Regression Example: TV Ratings 260 Parting Thoughts About Regression 265 Notes 267 Chapter 10 Bayes: Adding to What You Know Now 271 The Basics and Bayes 272 Example: Applying Bayes to Market Tests of New Products 275 One More Time: A Bayesian Look at Emily’s Experiment 277 Demystifying the Urn of Mystery 280 Using Your Natural Bayesian Instinct 281 Instinctive Bayesian Approach 282 Heterogeneous Benchmarking: A “Brand Damage” Application 287 Bayesian Inversion for Ranges: An Overview 291 Example: Percentage of Customers Kept After a Change 291 Bayes for Estimates of Means 297 The Lessons of Bayes 300 Myth 1: Absence of Evidence 301 Myth 2: Correlation Is Not Evidence of Causation 303 Myth 3: Ambiguous Results Tell Us Nothing 304 Myth 4: “This Alone Tells Me Nothing” 305 Notes 306 Part IV Beyond the Basics 309 Chapter 11 Preference and Attitudes: The Softer Side of Measurement 311 Observing Opinions, Values, and the Pursuit of Happiness 311 A Willingness to Pay: Measuring Value via Trade-Offs 316 Putting It All on the Line: Quantifying Risk Tolerance 320 Quantifying Subjective Trade-Offs: Dealing with Multiple Conflicting Preferences 323 Keeping the Big Picture in Mind: Profit Maximization Versus Purely Subjective Trade-Offs 326 Notes 328 Chapter 12 The Ultimate Measurement Instrument: Human Judges 331 Homo Absurdus: The Weird Reasons behind Our Decisions 332 Getting Organized: A Performance Evaluation Example 337 Surprisingly Simple Linear Models 339 How to Standardize Any Evaluation: Rasch Models 340 Removing Human inconsistency: the Lens Model 344 Panacea or Placebo?: Questionable Methods of Measurement 349 Comparing the Methods 357 Example: A Scientist Measures the Performance of a Decision Model 359 Notes 360 Chapter 13 New Measurement Instruments for Management 363 The Twenty-First-Century Tracker: Keeping Tabs with Technology 363 Measuring the World: The Internet as an Instrument 366 Prediction Markets: A Dynamic Aggregation of Opinions 370 Notes 377 Chapter 14 A Universal Measurement Method: Applied Information Economics 381 Bringing the Pieces Together 382 Case: The Value of the System That Monitors Your Drinking Water 386 Phase 0 387 Phase 1 387 Phase 2 388 Phase 3 389 Epilogue 390 Case: Forecasting Fuel for the Marine Corps 391 Phase 0 392 Phase 1 393 Phase 2 394 Phase 3 396 Epilogue 396 Case: Measuring the Value of Acord Standards 397 Phase 0 398 Phase 1 398 Phase 2 400 Phase 3 401 Epilogue 402 Ideas for Getting Started: A Few Final Examples 402 Quality 403 Value of a Process, Department, or Function 403 Innovation 404 Information Availability 405 Flexibility 406 Flexibility with Options Theory 407 Summarizing the Philosophy 408 Notes 409 Appendix: Calibration Tests (and Their Answers) 411 Index 421 Now Updated With New Measurement Methods And New Examples, How To Measure Anything Shows Managers How To Inform Themselves In Order 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, Government Agency Or Other Organization That, Until Now, You May Have Considered Immeasurable, Including Customer Satisfaction, Organizational Flexibility, Technology Risk, And Technology Roi. Adds New Measurement Methods, Showing How They Can Be Applied To A Variety Of Areas Such As Risk Management And Custom. How To Measure Anything; Contents; Preface To The Third Edition; About The Companion Website; Acknowledgments; About The Author; Part I The Measurement Solution Exists; Chapter 1 The Challenge Of Intangibles; The Alleged Intangibles; Yes, I Mean Anything; The Proposal: It's About Decisions; A Power Tools Approach To Measurement; A Guide To The Rest Of The Book; Chapter 2 An Intuitive Measurement Habit: Eratosthenes, Enrico, And Emily; How An Ancient Greek Measured The Size Of Earth; Estimating: Be Like Fermi; Experiments: Not Just For Adults. Notes On What To Learn From Eratosthenes, Enrico, And Emilynotes; Chapter 3 The Illusion Of Intangibles: Why Immeasurables Aren't; The Concept Of Measurement; A Definition Of Measurement: An Information Theory Version; A Variety Of Measurement Scales; Bayesian Measurement: A Pragmatic Concept For Decisions; The Object Of Measurement; The Methods Of Measurement; The Power Of Small Samples: The Rule Of Five; Even Smaller Samples: The Urn Of Mystery; Our Small-sample Intuition Versus Math; Economic Objections To Measurement; The Broader Objection To The Usefulness Of Statistics. Ethical Objections To Measurementreversing Old Assumptions; It's Been Measured Before; You Have Far More Data Than You Think; You Need Far Less Data Than You Think; Useful, New Observations Are More Accessible Than You Think; Notes; Part Ii Before You Measure; Chapter 4 Clarifying The Measurement Problem; Toward A Universal Approach To Measurement; The Unexpected Challenge Of Defining A Decision; Decision-oriented Measurements: For Scientists, Too; How To Get To A Real Decision; Requirements For A Decision; Potential Forms Of A Decision; If You Understand It, You Can Model It. Getting The Language Right: What Uncertainty And Risk Really Meanan Example Of A Clarified Decision; Notes; Chapter 5 Calibrated Estimates: How Much Do You Know Now?; Calibration Exercise; Calibration Trick: Bet Money (or Even Just Pretend To); Further Improvements On Calibration; Conceptual Obstacles To Calibration; The Effects Of Calibration Training; Notes; Chapter 6 Quantifying Risk Through Modeling; How Not To Quantify Risk; Real Risk Analysis: The Monte Carlo; An Example Of The Monte Carlo Method And Risk; Tools And Other Resources For Monte Carlo Simulations. The Risk Paradox And The Need For Better Risk Analysisnotes; Chapter 7 Quantifying The Value Of Information; The Chance Of Being Wrong And The Cost Of Being Wrong: Expected Opportunity Loss; The Value Of Information For Ranges; Beyond Yes/no: Decisions On A Continuum; The Imperfect World: The Value Of Partial Uncertainty Reduction; Perishable Information Values; Information Values For Multiple Variables; The Epiphany Equation: How The Value Of Information Changes Everything; Summarizing Uncertainty, Risk, And Information Value: The Pre-measurements; Notes; Part Iii Measurement Methods. Chapter 8 The Transition: From What To Measure To How To Measure. Douglas W. Hubbard. Includes Bibliographical References And Index. Now updated with new measurement methods and new examples, How to Measure Anything shows managers how to inform themselves in order 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, government agency or other organization that, until now, you may have considered "immeasurable," including customer satisfaction, organizational flexibility, technology risk, and technology ROI. Adds new measurement methods, showing how they can be applied to a variety of areas such as risk management and customer satisfaction Simplifies overall content while still making the more technical applications available to those readers who want to dig deeper Continues to boldly assert that any perception of "immeasurability" is based on certain popular misconceptions about measurement and measurement methods Shows the common reasoning for calling something immeasurable, and sets out to correct those ideas Offers practical methods for measuring a variety of "intangibles" Provides an online database (www.howtomeasureanything.com) of downloadable, practical examples worked out in detailed spreadsheets Written by recognized expert Douglas Hubbard—creator of Applied Information Economics— How to Measure Anything, Third 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. "From market research to information technology to financial reporting, How to Measure Anything reveals the power of measurement to our understanding of business and the world at large. 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. With examples ranging from how a marine biologist measures the population of fish in a large lake to how the United States Marine Corps found out what really matters in forecasting fuel requirements for the battlefield, you will discover a 'universal approach' to measuring 'intangibles, ' along with some interesting methods for particular problems. Here, you will learn about: the Illusion of Intangibles: why immeasurables aren't; calibrated estimates: how much do you know now?; measuring risk: introduction to the Monte Carlo; sampling reality: how observing some things tells us about all; unconventional measurement instruments such as the internet, human judges, prediction markets, and more; measuring the value of information: what's it worth to measure?"--Publisher description