How to Measure Anything: Finding the Value of Intangibles in Business Hardcover – April 12, 2010

Some things are easy to measure. Time, money, exercise, calories, location - all of these are relatively straightforward to repeatably determine or calculate.

But how does one go about measuring happiness? What about compassion, or public influence, or creativity? These are more intangible, harder to pin down to a number that means anything.

Douglas Hubbard has written an impressive work called "How To Measure Anything: Finding the Value of Intangibles in Business."

While it's written primarily for business people, the lessons transfer smoothly to self-experimenters. Hubbard begins with a compelling case for why to measure intangibles:

"Often, an important decision requires better knowledge of the alleged intangible, but when a [person] believes something to be immeasurable, attempts to measure it will not even be considered.

As a result, decisions are less informed than they could be. The chance of error increases. Resources are misallocated, good ideas are rejected, and bad ideas are accepted. Money is wasted. In some cases life and health are put in jeopardy. The belief that some things--even very important things--might be impossible to measure is sand in the gears of the entire economy.

Any important decision maker could benefit from learning that anything they really need to know is measurable."

He goes on to explain in detail how to measure intangibles, including sections on how to clarify problems, calibrate estimates, measure risk, sample reality, and use Bayesian statistics to add to available knowledge. He also describes his Applied Information Economics (AIE) Approach that ties together several threads of his ideas:

"The AIE approach addresses four things:
1. How to model a current state of uncertainty
2. How to compute what else should be measured
3. How to measure those things in a way that is economically justified
4. How to make a decision"

I'm working my way through the book, and am incredibly grateful to Douglas Hubbard for writing it.

Mr. Hubbard provides a very well written analysis on how the things most people think can't be measured really can be measured. The book provides very thought provoking insights on how many of today's most popular "risk assessment" frameworks fall short and often introduce more error. It also provides proven and very practical and useful ways (with examples) to think about risk that helps management better communicate the uncertainty they have in their assessments and defining a proven method for setting up measurements that can produce a more consistent result that provide a lot of power in decision making. The book also outlines the need for risk analysts to get "calibrated" which is something that was very eye opening and game changing and crucial to improving our risk and decision making. All in all one of the best books I have ever read related to risk management that goes way beyond theory, and uses proven techniques deployed in the insurance and science areas.

This book provides the link between the college statistical classes and the "real" world that is full of uncertainty, incomplete information and things that seemingly are impossible to measure. The most important aspects of the book are not the mathmatical techniques but the conceptual groundwork that help break down previously held paradigms about measurement. Once these barriers have been removed then possibilities open up. Highly recommended.

"How to measure anything" is an interesting book exploring how to measure 'things' that are usually claimed to be unmeasurable. The things is mostly interpreted as something related to business measurements such as quality, customer satisfaction, or business case. The book does a pretty good job at describing measurement in general and how to apply that to difficult to measure things. It does what is promised in its title.

The book contains 4 different parts: 1) Measurement: The Solution Exists, 2) Before You Measure, 3) Measurement Methods, and 4) Beyond The Basics. Each of these parts contain 3-4 chapters. In total, the book is about 300 pages and reasonably easy to read despite the math that is included at times.

The first part is an introduction to the whole book and covers the general picture. It starts with the goal of the book and then introduces three people who measures something difficult in different ways. The three people will be used repeatedly throughout the book. Then it explains what a measurement is and why you would measure. Within the book, measurements are tight very much towards making a decision.

The second part starts the measurement journey by discussing things that you ought to do before you measure, such as.. deciding what and why you want to measure... what is your measurement problem. From there is discusses calibration, but it adds an interesting angle that it calibrates people estimating things also. It introduces risk modeling and running Monte Carlo simulations and ends the preparation part by deciding when a measurement is worth it... which is when there is enough value to the information it provides.

The third part covers actual measuring of things. It starts of by showing that decomposing the measurement problem is half-way solving the problem of measuring intangibles. After that it talks about sampling or how much you should measure before having valuable information. It then finalizes the measurement part with Bayesian statistics.

The last part covers additional measurement topics such as the attitude towards measurement and human bias and how that influences estimations and measurements. It also has a chapter on 'new' ways of measuring things mostly using new technology. The last chapter introduces the measurement methodology created by the author called "Applied Information Economics" which is roughly described in this book.

As mentioned above, the book is pretty good.It covers a lot about measurement. There were a few things that made me uncomfortable in the book. One was the assumption that we must make big decisions and therefore we need to have that big decision be informed by measurement. It never went on to question whether the big decision could be split in many small decisions (more small investments over one big one). Especially considering the IT background of the author, I felt that was missing. Also, the book doesn't talk much about the situation where easy measurements of intangibles lead to dysfunctional behavior/decisions (covered in e.g. Managing Performance in Organizations by Rob Austin). It suggests that some measurement it always better than no measurement, whereas in reality I do not necessarily agree.

Other than that, the book was ok on language. It was probably easier to read than most statistics book, yet I did find the writing at times repetitive and a bit boring. Still all over all, it was a pretty good book and would give it 4 stars if not for the 2 objections above, thus decided to go with 3 stars.