How to Measure Anything: Finding the Value of 'Intangibles in Business'

What it’s about

Douglas Hubbard dismantles the costly myth that important business quantities like quality, risk, security, employee morale, or public image are immeasurable. Drawing on his Applied Information Economics (AIE) method and inspired by 'measurement mentors' Eratosthenes, Enrico Fermi, and nine-year-old Emily Rosa, he shows that measurement means reducing uncertainty—not achieving exact certainty—and that even a few clever observations can dramatically improve big, risky decisions. The book equips readers with calibrated estimation, Monte Carlo risk modeling, value-of-information calculations, sampling shortcuts (the Rule of Five, the Urn of Mystery), Bayesian updating, and methods to turn human experts into reliable instruments (Lens models, Rasch models). The central revelation—the 'Measurement Inversion'—is that organizations routinely measure what is easy and ignore what truly matters, and that computing the economic value of information tells you exactly what to measure, how much, and when to stop. Through real cases (Veterans Affairs IT security, EPA drinking water, Marine Corps fuel forecasting, ACORD standards), the book proves that resourceful, decision-focused measurement pays for itself many times over.

The through-line

Who it’s for

A manager, analyst, or decision maker who must make big, risky decisions and wants better information about things others have dismissed as immeasurable.

The problem

Critical 'intangibles'—quality, risk, security, customer satisfaction, productivity, brand value—appear impossible to measure, so decisions are made under unnecessary uncertainty. They feel stuck, intimidated by statistics, and anxious that any measurement will be too imperfect, too expensive, or simply impossible.

The plan

1. Define the decision the measurement supports and clarify exactly what the intangible means in observable terms.
2. Quantify your current uncertainty with calibrated 90% confidence intervals and probabilities.
3. Model the decision and its risk (e.g., with a Monte Carlo simulation).
4. Compute the value of additional information to decide what and how much to measure.
5. Apply economical measurement methods—sampling, experiments, Bayesian updating, expert calibration.

The payoff

Better-informed decisions with quantified risk and return. · Resources allocated to what truly matters, saving money and avoiding costly errors. · Confidence that even 'intangible' factors can be measured economically and iteratively.

See our guide

• Practice Business Intelligence & Data Science →
• The Four-S Discipline — One System, Four Capabilities →
• Measure What Matters →
• Study People And Organizations With Scientific Rigor →
• The Behavioral Science Underneath It All →
• Build A People Analytics Function →
• Design The Organization And Change It →
• Do Research That Holds Up →
• Design Surveys People Answer Honestly →
• Understand What Drives Individual Performance →
• Choose And Apply The Right Analytical Method →

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• A Practical Guide To Conjoint Analysis →
• Analytics at Work: Smarter Decisions, Better Results →
• Big Data: A Revolution That Will Transform How We Live, Work, and Think →
• Big Data_ A Very Short Introduction (Very Short Introductions) →
• Business Adventures →
• Business Intelligence Guidebook: From Data Integration to Analytics →
• Data Mining for Business Analytics: Concepts, Techniques, and Applications →
• Data Warehouse and Data Mining →

Additional reading

• The Failure of Risk Management: Why It’s Broken and How to Fix It · Douglas W. Hubbard

  This book is referenced multiple times as a deeper dive into the book's treatment of risk, providing a more thorough critique of popular but flawed risk matrices and scoring methods.

• Pulse: The New Science of Harnessing Internet Buzz to Track Threats and Opportunities · Douglas W. Hubbard

  This book is presented as an extension of Chapter 13, focusing entirely on the Internet as a powerful new measurement instrument and detailing how to use web data to measure economic and social trends.

• Expert Political Judgment: How Good Is It? How Can We Know? · Philip E. Tetlock

  Cited as providing one of the largest and most definitive studies showing that simple quantitative algorithms outperform human experts in forecasting, confirming a central thesis of 'How to Measure Anything'.

• Clinical versus Statistical Prediction · Paul E. Meehl

  The book refers to this as the 'monumental, classic book' that originally established the superiority of statistical models over expert clinical judgment, a finding the author applies broadly to management.

• The Wisdom of Crowds · James Surowiecki

  Mentioned as the book that popularized the idea of prediction markets, which 'How to Measure Anything' presents as a powerful new tool for forecasting and measurement.

Featured in these guides

• The Behavioral Science Underneath It All →Cited source
• Build A People Analytics Function →Cited source
• Practice Business Intelligence & Data Science →Cited source
• Measure What Matters →Named in 2 disagreements
• Design The Organization And Change It →Cited source
• Study People And Organizations With Scientific Rigor →Cited source
• Do Research That Holds Up →Cited source
• Choose And Apply The Right Analytical Method →Cited source
• Design Surveys People Answer Honestly →Cited source
• Understand What Drives Individual Performance →Cited source

Where other books disagree

• Do Attributes Exist Before Measurement? →
• Reliability First Or Decision Value First? →