Coming soon · Step-by-step Guide
How to Measure Anything: Finding the Value of 'Intangibles in Business'
A practical guide arguing that anything a manager cares about—however 'intangible'—can be measured by reframing measurement as the economically justified reduction of uncertainty to inform decisions.
This is a step-by-step procedural book — we're building it into Stepcode, with a profile to follow.
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
- Define the decision the measurement supports and clarify exactly what the intangible means in observable terms.
- Quantify your current uncertainty with calibrated 90% confidence intervals and probabilities.
- Model the decision and its risk (e.g., with a Monte Carlo simulation).
- Compute the value of additional information to decide what and how much to measure.
- 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
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Additional reading
- Competing on Analytics: The New Science of Winning · Thomas H. Davenport and Jeanne G. Harris
The authors' previous book, which provides the strategic context by describing the earliest and most aggressive adopters of analytics. This book builds on it by providing a 'how-to' guide for all organizations.
- Sources of Power: How People Make Decisions · Gary Klein
Discusses decision-making in high-pressure situations where there is no time for systematic data gathering, providing a contrast to the analytical approach and showing when intuition is necessary.
- The Black Swan: The Impact of the Highly Improbable · Nassim Nicholas Taleb
Argues that statistical analysis is limited because it cannot predict rare, high-impact 'black swan' events, serving as a cautionary note on the limits of analytics.
- Moneyball: The Art of Winning an Unfair Game · Michael Lewis
A popular case study of how the Oakland A's baseball team used an analytical approach to player selection to compete with richer teams, illustrating the power of competing on analytics.
- Why Great Leaders Don't Take Yes for an Answer · Michael Roberto
Describes how to foster a culture of constructive conflict and debate in decision-making processes, which is essential for an analytical culture where assumptions are tested and merit triumphs over politics.
- The Visual Display of Quantitative Information · Edward Tufte
A foundational work on how to create clear visual representations of data, a key skill for communicating analytical findings effectively.
- Super Crunchers: Why Thinking-By-Numbers Is the New Way to Be Smart · Ian Ayres
The book discusses how statistical analyses are replacing human intuition and expert judgment in decision-making, a core theme related to the discussion of 'Moneyball' and the demise of the expert.
- Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed · James Scott
Documents how governments' fetish for quantification and data can lead to misguided and harmful policies, providing a deep historical context for the book's warnings about the 'dictatorship of data'.
- The War Managers · Douglas Kinnard
A survey of U.S. generals' views on the Vietnam War, revealing that the 'body count' metric was seen as a worthless and inflated measure of progress, illustrating the dangers of relying on flawed data.
- Thinking, Fast and Slow · Daniel Kahneman
Explains the cognitive biases that lead humans to see illusory causal links, which the author's argue big data correlations can challenge and disprove.