{"product_id":"how-to-measure-anything-9781118539279","title":"How to Measure Anything","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eShows managers how to inform themselves in order to make less risky, profitable business decisions. This book shows 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, and technology risk.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface to the Third Edition xiii\u003c\/p\u003e \u003cp\u003eAcknowledgments xix\u003c\/p\u003e \u003cp\u003eAbout the Author xxi\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I The Measurement Solution Exists 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 The Challenge of Intangibles 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Alleged Intangibles 4\u003c\/p\u003e \u003cp\u003eYes, I Mean Anything 5\u003c\/p\u003e \u003cp\u003eThe Proposal: It’s about Decisions 7\u003c\/p\u003e \u003cp\u003eA “Power Tools” Approach to Measurement 10\u003c\/p\u003e \u003cp\u003eA Guide to the Rest of the Book 11\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 An Intuitive Measurement Habit: Eratosthenes, Enrico, and Emily 15\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eHow an Ancient Greek Measured the Size of Earth 16\u003c\/p\u003e \u003cp\u003eEstimating: Be Like Fermi 17\u003c\/p\u003e \u003cp\u003eExperiments: Not Just for Adults 20\u003c\/p\u003e \u003cp\u003eNotes on What to Learn from Eratosthenes, Enrico, and Emily 25\u003c\/p\u003e \u003cp\u003eNotes 27\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 The Illusion of Intangibles: Why Immeasurables Aren’t 29\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Concept of Measurement 30\u003c\/p\u003e \u003cp\u003eThe Object of Measurement 37\u003c\/p\u003e \u003cp\u003eThe Methods of Measurement 40\u003c\/p\u003e \u003cp\u003eEconomic Objections to Measurement 48\u003c\/p\u003e \u003cp\u003eThe Broader Objection to the Usefulness of “Statistics” 52\u003c\/p\u003e \u003cp\u003eEthical Objections to Measurement 55\u003c\/p\u003e \u003cp\u003eReversing Old Assumptions 58\u003c\/p\u003e \u003cp\u003eNotes 65\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Before You Measure 69\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 Clarifying the Measurement Problem 71\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eToward a Universal Approach to Measurement 73\u003c\/p\u003e \u003cp\u003eThe Unexpected Challenge of Defining a Decision 74\u003c\/p\u003e \u003cp\u003eIf You Understand It, You Can Model It 80\u003c\/p\u003e \u003cp\u003eGetting the Language Right: What “Uncertainty” and “Risk” Really Mean 83\u003c\/p\u003e \u003cp\u003eAn Example of a Clarified Decision 84\u003c\/p\u003e \u003cp\u003eNotes 90\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Calibrated Estimates: How Much Do You Know Now? 93\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCalibration Exercise 95\u003c\/p\u003e \u003cp\u003eCalibration Trick: Bet Money (or Even Just Pretend To) 101\u003c\/p\u003e \u003cp\u003eFurther Improvements on Calibration 104\u003c\/p\u003e \u003cp\u003eConceptual Obstacles to Calibration 106\u003c\/p\u003e \u003cp\u003eThe Effects of Calibration Training 111\u003c\/p\u003e \u003cp\u003eNotes 118\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Quantifying Risk through Modeling 123\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eHow Not to Quantify Risk 123\u003c\/p\u003e \u003cp\u003eReal Risk Analysis: The Monte Carlo 125\u003c\/p\u003e \u003cp\u003eAn Example of the Monte Carlo Method and Risk 127\u003c\/p\u003e \u003cp\u003eTools and Other Resources for Monte Carlo Simulations 136\u003c\/p\u003e \u003cp\u003eThe Risk Paradox and the Need for Better Risk Analysis 140\u003c\/p\u003e \u003cp\u003eNotes 143\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Quantifying the Value of Information 145\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Chance of Being Wrong and the Cost of Being Wrong: Expected Opportunity Loss 146\u003c\/p\u003e \u003cp\u003eThe Value of Information for Ranges 149\u003c\/p\u003e \u003cp\u003eBeyond Yes\/No: Decisions on a Continuum 156\u003c\/p\u003e \u003cp\u003eThe Imperfect World: The Value of Partial Uncertainty Reduction 159\u003c\/p\u003e \u003cp\u003eThe Epiphany Equation: How the Value of Information Changes Everything 166\u003c\/p\u003e \u003cp\u003eSummarizing Uncertainty, Risk, and Information Value: The Pre-Measurements 171\u003c\/p\u003e \u003cp\u003eNotes 172\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III Measurement Methods 173\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 The Transition: From What to Measure to How to Measure 175\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTools of Observation: Introduction to the Instrument of Measurement 177\u003c\/p\u003e \u003cp\u003eDecomposition 180\u003c\/p\u003e \u003cp\u003eSecondary Research: Assuming You Weren’t the First to Measure It 184\u003c\/p\u003e \u003cp\u003eThe Basic Methods of Observation: If One Doesn’t Work, Try the Next 186\u003c\/p\u003e \u003cp\u003eMeasure Just Enough 188\u003c\/p\u003e \u003cp\u003eConsider the Error 189\u003c\/p\u003e \u003cp\u003eChoose and Design the Instrument 194\u003c\/p\u003e \u003cp\u003eNotes 196\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Sampling Reality: How Observing Some Things Tells Us about All Things 197\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBuilding an Intuition for Random Sampling: The Jelly Bean Example 199\u003c\/p\u003e \u003cp\u003eA Little about Little Samples: A Beer Brewer’s Approach 200\u003c\/p\u003e \u003cp\u003eAre Small Samples Really “Statistically Significant”? 204\u003c\/p\u003e \u003cp\u003eWhen Outliers Matter Most 208\u003c\/p\u003e \u003cp\u003eThe Easiest Sample Statistics Ever 210\u003c\/p\u003e \u003cp\u003eA Biased Sample of Sampling Methods 214\u003c\/p\u003e \u003cp\u003eExperiment 226\u003c\/p\u003e \u003cp\u003eSeeing Relationships in the Data: An Introduction to Regression Modeling 235\u003c\/p\u003e \u003cp\u003eNotes 243\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Bayes: Adding to What You Know Now 247\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Basics and Bayes 248\u003c\/p\u003e \u003cp\u003eUsing Your Natural Bayesian Instinct 257\u003c\/p\u003e \u003cp\u003eHeterogeneous Benchmarking: A “Brand Damage” Application 263\u003c\/p\u003e \u003cp\u003eBayesian Inversion for Ranges: An Overview 267\u003c\/p\u003e \u003cp\u003eThe Lessons of Bayes 276\u003c\/p\u003e \u003cp\u003eNotes 282\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart IV Beyond the Basics 285\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 Preference and Attitudes: The Softer Side of Measurement 287\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eObserving Opinions, Values, and the Pursuit of Happiness 287\u003c\/p\u003e \u003cp\u003eA Willingness to Pay: Measuring Value via Trade-Offs 292\u003c\/p\u003e \u003cp\u003ePutting It All on the Line: Quantifying Risk Tolerance 296\u003c\/p\u003e \u003cp\u003eQuantifying Subjective Trade-Offs: Dealing with Multiple Conflicting Preferences 299\u003c\/p\u003e \u003cp\u003eKeeping the Big Picture in Mind: Profit Maximization versus Purely Subjective Trade-Offs 302\u003c\/p\u003e \u003cp\u003eNotes 304\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 The Ultimate Measurement Instrument: Human Judges 307\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eHomo Absurdus: The Weird Reasons behind Our Decisions 308\u003c\/p\u003e \u003cp\u003eGetting Organized: A Performance Evaluation Example 313\u003c\/p\u003e \u003cp\u003eSurprisingly Simple Linear Models 315\u003c\/p\u003e \u003cp\u003eHow to Standardize Any Evaluation: Rasch Models 316\u003c\/p\u003e \u003cp\u003eRemoving Human Inconsistency: The Lens Model 320\u003c\/p\u003e \u003cp\u003ePanacea or Placebo?: Questionable Methods of Measurement 325\u003c\/p\u003e \u003cp\u003eComparing the Methods 333\u003c\/p\u003e \u003cp\u003eExample: A Scientist Measures the Performance of a Decision Model 335\u003c\/p\u003e \u003cp\u003eNotes 336\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13 New Measurement Instruments for Management 339\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Twenty-First-Century Tracker: Keeping Tabs with Technology 339\u003c\/p\u003e \u003cp\u003eMeasuring the World: The Internet as an Instrument 342\u003c\/p\u003e \u003cp\u003ePrediction Markets: A Dynamic Aggregation of Opinions 346\u003c\/p\u003e \u003cp\u003eNotes 353\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14 A Universal Measurement Method: Applied Information Economics 357\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBringing the Pieces Together 358\u003c\/p\u003e \u003cp\u003eCase: The Value of the System That Monitors Your Drinking Water 362\u003c\/p\u003e \u003cp\u003eCase: Forecasting Fuel for the Marine Corps 367\u003c\/p\u003e \u003cp\u003eCase: Measuring the Value of ACORD Standards 373\u003c\/p\u003e \u003cp\u003eIdeas for Getting Started: A Few Final Examples 378\u003c\/p\u003e \u003cp\u003eSummarizing the Philosophy 384\u003c\/p\u003e \u003cp\u003eNotes 385\u003c\/p\u003e \u003cp\u003eAppendix Calibration Tests (and Their Answers) 387\u003c\/p\u003e \u003cp\u003eIndex 397\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":48866373402967,"sku":"9781118539279","price":32.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118539279.jpg?v=1722278340","url":"https:\/\/bookcurl.com\/products\/how-to-measure-anything-9781118539279","provider":"Book Curl","version":"1.0","type":"link"}