| |
| |
| Preface | |
| |
| |
| Acknowledgments | |
| |
| |
| Measurement: The Solution Exists | |
| |
| |
| The Intangibles and the Challenge | |
| |
| |
| An Intuitive Measurement Habit: Eratosthenes, Enrico, & 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 Emily | |
| |
| |
| The Illusion of Intangibles: Why Immeasurables Aren't | |
| |
| |
| The Concept of Measurement | |
| |
| |
| The Object of Measurement | |
| |
| |
| The Methods of Measurement | |
| |
| |
| Economic Objections to Measurement | |
| |
| |
| The Broader Objection to the Usefulness of "Statistics" | |
| |
| |
| Ethical Objections to Measurement | |
| |
| |
| Toward a Universal Approach to Measurement | |
| |
| |
| Before You Measure | |
| |
| |
| Clarifying the Measurement Problem | |
| |
| |
| Getting the Language Right: What "Uncertainty" and "Risk" Really Mean | |
| |
| |
| Examples of Clarification: Lessons for Business from, of All Places, Government | |
| |
| |
| Calibrated Estimates: How Much Do You Know Now? | |
| |
| |
| Testing Your Ability to Assess Odds | |
| |
| |
| Calibration Exercise | |
| |
| |
| Further Improvements on Calibration | |
| |
| |
| Conceptual Obstacles to Calibration | |
| |
| |
| The Effects of Calibration | |
| |
| |
| Measuring Risk: Introduction to the Monte Carlo Simulation | |
| |
| |
| An Example of the Monte Carlo Method and Risk | |
| |
| |
| Tools and Other Resources for Monte Carlo Simulations | |
| |
| |
| The Risk Paradox | |
| |
| |
| Measuring the Value of Information | |
| |
| |
| The Chance of Being Wrong and the Cost of Being Wrong: Expected Opportunity Loss | |
| |
| |
| The Value of Information for Ranges | |
| |
| |
| The Imperfect World: The Value of Partial Uncertainty Reduction | |
| |
| |
| The Epiphany Equation: The Value of a Measurement Changes Everything | |
| |
| |
| Summarizing Uncertainty, Risk, and Information Value: The First Measurements | |
| |
| |
| Measurement Methods | |
| |
| |
| The Transition: From What to Measure to How to Measure | |
| |
| |
| Tools of Observation: Introduction to the Instrument of Measurement | |
| |
| |
| Decomposition | |
| |
| |
| Secondary Research: Assuming You Weren't the First to Measure It | |
| |
| |
| The Basic Methods of Observation: If One Doesn't Work, Try the Next | |
| |
| |
| Measure Just Enough | |
| |
| |
| Consider the Error | |
| |
| |
| Choose and Design the Instrument | |
| |
| |
| Sampling Reality: How Observing Some Things Tells Us about All Things | |
| |
| |
| Building an Intuition for Random Sampling: The Jelly Bean Example | |
| |
| |
| A Little About Little Samples: A Beer Brewer's Approach | |
| |
| |
| The Easiest Sample Statistics Ever | |
| |
| |
| A Biased Sample of Sampling Methods | |
| |
| |
| Measure to the Threshold | |
| |
| |
| Experiment | |
| |
| |
| Seeing Relationships in the Data: An Introduction to Regression Modeling | |
| |
| |
| Bayes: Adding to What You Know Now | |
| |
| |
| Simple Bayesian Statistics | |
| |
| |
| Using Your Natural Bayesian Instinct | |
| |
| |
| Heterogeneous Benchmarking: A "Brand Damage" Application | |
| |
| |
| Getting a Bit More Technical: Bayesian Inversion for Ranges | |
| |
| |
| Beyond the Basics | |
| |
| |
| Preference and Attitudes: The Softer Side of Measurement | |
| |
| |
| Observing Opinions, Values, and the Pursuit of Happiness | |
| |
| |
| A Willingness to Pay: Measuring Value via Trade-offs | |
| |
| |
| Putting It All on the Line: Quantifying Risk Tolerance | |
| |
| |
| Quantifying Subjective Trade-offs: Dealing with Multiple Conflicting Preferences | |
| |
| |
| Keeping the Big Picture in Mind: Profit Maximization versus Subjective Trade-offs | |
| |
| |
| The Ultimate Measurement Instrument: Human Judges | |
| |
| |
| Homo absurdus: The Weird Reasons behind Our Decisions | |
| |
| |
| Getting Organized: A Performance Evaluation Example | |
| |
| |
| Surprisingly Simple Linear Models | |
| |
| |
| How to Standardize Any Evaluation: Rasch Models | |
| |
| |
| Removing Human Inconsistency: The Lens Model | |
| |
| |
| Panacea or Placebo?: Questionable Methods of Measurement | |
| |
| |
| Comparing the Methods | |
| |
| |
| New Measurement Instruments for Management | |
| |
| |
| The Twenty-First-Century Tracker: Keeping Tabs with Technology | |
| |
| |
| Measuring the World: The Internet as an Instrument | |
| |
| |
| Prediction Markets: Wall Street Efficiency Applied to Measurements | |
| |
| |
| A Universal Measurement Method: Applied Information Economics | |
| |
| |
| Bringing the Pieces Together | |
| |
| |
| Case: The Value of the System That Monitors Your Drinking Water | |
| |
| |
| Case: Forecasting Fuel for the Marine Corps | |
| |
| |
| Ideas for Getting Started: A Few Final Examples | |
| |
| |
| Summarizing the Philosophy | |
| |
| |
| Calibration Tests | |
| |
| |
| Index | |