How to Measure Anything: Finding the Value of Intangibles in Business 3rd Edition

Book Preface

I can’t speak for all authors, but I feel that a book—especially one based largely on ongoing research—is never really finished. This is precisely what editions are for. In the time since the publication of the second edition of this book, I continue to come across fascinating published research about the power and oddities of human decision making. And as my small firm continues to apply the methods in this book to real-world problems, I have even more examples I can use to illustrate the concepts. Feedback from readers and my experience explaining these concepts to many audiences have also helped me refine the message.

Of course, if the demand for the book wasn’t still strong six years after the first edition was published, Wiley and I wouldn’t be quite as incentivized to publish another edition. We also found this book, written explicitly for business managers, was catching on in universities. Professors from all over the world were contacting me to say they were using this book in a course they were teaching. In some cases it was the primary text—even though How to Measure Anything (HTMA) was never written as a textbook. Now that we see this growing area of interest, Wiley and I decided we should also create an accompanyingworkbook and instructor materials with this edition. Instructor materials are available at www.wiley.com.

In the time since I wrote the first edition of HTMA, I’ve written a second edition (2010) and two other titles—The Failure of Risk Management: Why It’s Broken and How to Fix It and Pulse: The New Science of Harnessing Internet Buzz to Track Threats and Opportunities. I wrote these books to expand on ideas I mention in earlier editions of How to Measure Anything and I also combine some of the key points I make in these books into this new edition.

For example, I started writing The Failure of Risk Management because I felt that the topic of risk, on which I could spend only one chapter and a few other references in this book, merited much more space. I argued that a lot of the most popular methods used in risk assessments and risk management don’t stand up to the bright light of 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 and the welfare of the population. All important decision makers could benefit from learning that anything they really need to know is measurable. However, in a democracy and a free-enterprise economy, voters and consumers count among these “important decision makers.” Chances are that your decisions in some part of your life or your professional responsibilities would be improved by better measurement. And it’s virtually certain that your life has already been affected—negatively—by the lack of measurement in someone else’s decisions in business or government.

I’ve made a career out of measuring the sorts of things many thought were immeasurable. I first started to notice the need for better measurement in 1988, shortly after I started working for Coopers & Lybrand as a brand-new MBA in the management consulting practice. I was surprised at how often clients dismissed a critical quantity—something that would affect a major new investment or policy decision—as completely beyond measurement. Statistics and quantitative methods courses were still fresh in my mind. In some cases, when someone called something “immeasurable,” I would remember a specific example where it was actually measured. I began to suspect any claim of immeasurability as possibly premature, and I would do research to confirm or refute the claim. Time after time, I kept finding that the allegedly immeasurable thing was already measured by an academic or perhaps professionals in another industry.

At the same time, I was noticing that books about quantitative methods didn’t focus on making the case that everything is measurable. They also did not focus on making the material accessible to the people who really needed it. They start with the assumption that the reader already believes something to be measurable, and it is just a matter of executing the appropriate algorithm. And these books tended to assume that the reader’s objective was a level of rigor that would suffice for publication in a scientific journal—not merely a decrease in uncertainty about some critical decision with a method a non-statistician could understand.