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

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Bibliographic Details
Main Author: Hubbard, Douglas W., 1962- (Author)
Corporate Author: Ebooks Corporation
Format: Electronic eBook
Language:English
Published: Hoboken, New Jersey : Wiley, [2014]
Edition:Third edition.
Subjects:
Online Access:Connect to this title online (unlimited simultaneous users allowed; 325 uses per year)
Table of Contents:
  • Machine generated contents note: ch. 1 Challenge of Intangibles
  • Alleged Intangibles
  • Yes, I Mean Anything
  • Proposal: It's about Decisions
  • "Power Tools" Approach to Measurement
  • Guide to the Rest of the Book
  • ch. 2 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 Emily
  • Notes
  • ch. 3 Illusion of Intangibles: Why Immeasurables Aren't
  • Concept of Measurement
  • Object of Measurement
  • Methods of Measurement
  • Economic Objections to Measurement
  • Broader Objection to the Usefulness of "Statistics"
  • Ethical Objections to Measurement
  • Reversing Old Assumptions
  • Notes
  • ch. 4 Clarifying the Measurement Problem
  • Toward a Universal Approach to Measurement
  • Unexpected Challenge of Defining a Decision
  • If You Understand It, You Can Model It
  • Getting the Language Right: What "Uncertainty" and "Risk" Really Mean
  • Example of a Clarified Decision
  • Notes
  • ch. 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
  • Effects of Calibration Training
  • Notes
  • ch. 6 Quantifying Risk through Modeling
  • How Not to Quantify Risk
  • Real Risk Analysis: The Monte Carlo
  • Example of the Monte Carlo Method and Risk
  • Tools and Other Resources for Monte Carlo Simulations
  • Risk Paradox and the Need for Better Risk Analysis
  • Notes
  • ch. 7 Quantifying the Value of Information
  • Chance of Being Wrong and the Cost of Being Wrong: Expected Opportunity Loss
  • Value of Information for Ranges
  • Beyond Yes/No: Decisions on a Continuum
  • Imperfect World: The Value of Partial Uncertainty Reduction
  • Epiphany Equation: How the Value of Information Changes Everything
  • Summarizing Uncertainty, Risk, and Information Value: The Pre Measurements
  • Notes
  • ch. 8 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
  • Basic Methods of Observation: If One Doesn't Work, Try the Next
  • Measure Just Enough
  • Consider the Error
  • Choose and Design the Instrument
  • Notes
  • ch. 9 Sampling Reality: How Observing Some Things Tells Us about All Things
  • Building an Intuition for Random Sampling: The Jelly Bean Example
  • Little about Little Samples: A Beer Brewer's Approach
  • Are Small Samples Really "Statistically Significant"?
  • When Outliers Matter Most
  • Easiest Sample Statistics Ever
  • Biased Sample of Sampling Methods
  • Experiment
  • Seeing Relationships in the Data: An Introduction to Regression Modeling
  • Notes
  • ch. 10 Bayes: Adding to What You Know Now
  • Basics and Bayes
  • Using Your Natural Bayesian Instinct
  • Heterogeneous Benchmarking: A "Brand Damage" Application
  • Bayesian Inversion for Ranges: An Overview
  • Lessons of Bayes
  • Notes
  • ch. 11 Preference and Attitudes: The Softer Side of Measurement
  • Observing Opinions, Values, and the Pursuit of Happiness
  • 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 Purely Subjective Trade Offs
  • Notes
  • ch. 12 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
  • Example: A Scientist Measures the Performance of a Decision Model
  • Notes
  • ch. 13 New Measurement Instruments for Management
  • Twenty First Century Tracker: Keeping Tabs with Technology
  • Measuring the World: The Internet as an Instrument
  • Prediction Markets: A Dynamic Aggregation of Opinions
  • Notes
  • ch. 14 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
  • Case: Measuring the Value of ACORD Standards
  • Ideas for Getting Started: A Few Final Examples
  • Summarizing the Philosophy
  • Notes.