Product Description
Praise for How to Measure Anything: Finding the Value of Intangibles in Business

"I love this book. Douglas Hubbard helps us create a path to know the answer to almost any question in business, in science, or in life . . . Hubbard helps us by showing us that when we seek metrics to solve problems, we are really trying to know something better than we know it now. How to Measure Anything provides just the tools most of us need to measure anything better, to gain that insight, to make progress, and to succeed."
-Peter Tippett, PhD, M.D.
Chief Technology Officer at CyberTrust
and inventor of the first antivirus software

"Doug Hubbard has provided an easy-to-read, demystifying explanation of how managers can inform themselves to make less risky, more profitable business decisions. We encourage our clients to try his powerful, practical techniques."
-Peter Schay
EVP and COO of
The Advisory Council

"As a reader you soon realize that actually everything can be measured while learning how to measure only what matters. This book cuts through conventional clichés and business rhetoric and offers practical steps to using measurements as a tool for better decision making. Hubbard bridges the gaps to make college statistics relevant and valuable for business decisions."
-Ray Gilbert
EVP Lucent

"This book is remarkable in its range of measurement applications and its clarity of style. A must-read for every professional who has ever exclaimed, 'Sure, that concept is important, but can we measure it?'"
-Dr. Jack Stenner
Cofounder and CEO of MetraMetrics, Inc.

CUSTOMER REVIEWS (Average Customer Rating: 5.0 based on 26 reviews)

Eye opening

Nutshell review - What a fantastic and eye-opening book - it is very well written and gives us some wonderful insights into the world of measuring. The book explains the mathematical concepts clearly (without becoming a book on math or statistics), provides excellent examples to help understand the material and shows how to apply these concepts in the real world.

Hubbard defines a measurement as creating a set of observations that reduce uncertainty and expressing that result as a quantity. This idea of reducing uncertainty in that which we want to measure (as opposed to trying to calculate some exact and objective number) provides an excellent aha! start to the material. Each chapter draws the reader in with more insights and greater understanding, building upon previous material and culminating with a very well presented case for being able to measure (i.e. reduce the uncertainty in) apparently anything.

Hubbard includes several quotes throughout the text and I think this one should help convince anyone interested in reducing uncertainty in their field of work to read this book; "Anything you need to quantify can be measured in some way that is superior to not measuring it at all" - Gilb's Law.
December 25, 2008

Easy to read, practical

This book is a real gem.
While the layout and graphical design are a little on the "homely" side, Hubbard's text and examples are very easy to read and understand. Plenty of key points emphasized in sidebars and very practical, authentic examples that really make the subject live and breath.
Highly recommended.
December 23, 2008

Very interesting read

As a person who has to measure a lot of data, I often feel overwhelmed. Douglas Hubbard puts measurement into perspective, and breaks it down into sane manageable chunks. I enjoyed this book and recommend it highly.
December 16, 2008

Required reading for business decision makers

I made this book a required read for my MBA Business Research Method class. It addresses some of the key falacies in thinking about the research for decision making. I have a more detailed review on [...].
November 16, 2008

How to use measurements as a tool for better decision making

Measuring seeming intangibles can be a very tricky task, and Hubbard does a masterful job walking the reader through the process of moving from a position of limiting their applicability of measurement to a position where they can essentially quantify anything. This text is very well written and only basic math skills are needed to apply the content. In a few isolated instances, the author walks the reader through some calculations that require knowledge of statistics beyond basic math, and even limits his discussion to Microsoft Excel functions in at least one case where he feels the math might be a little too inaccessible to the reader, although even in this scenario the math is by no means very advanced. In this reviewer's opinion, this feat is rather incredible, because the resources typically available on this subject matter are typically saturated with statistics, and the method of problem solving the author presents should make most readers very comfortable regardless of background. While this book can help measure tangibles, the intent here is to guide the reader to a point where they can measure what are typically viewed as intangibles, such as risk, quality, performance, value, demand, etc. While the background of the author is technology, and much of the discussion can be applied to nonfunctional architectural qualities, the book demonstrates that there really is no limit to measuring traditional intangibles. As Hubbard indicates in his first chapter, "anything can be measured. If a thing can be observed in any way at all, it lends itself to some type of measurement method. No matter how 'fuzzy' the measurement is, it's still a measurement if it told you more than you knew before. And those very things most likely to be seen as immeasurable are, virtually always, solved by relatively simple measurement methods". The author is careful to point out that this work is not intended to cover every single subject matter, but "focus on measurements that are relevant - even critical - to major organizational decisions and yet don't seem to lend themselves to an obvious and practical measurement solution. The book addresses some common misconceptions about intangibles, describes a 'universal approach' to show how to go about measuring an 'intangible', and backs it up with some interesting methods for particular problems". The author explains that the key obstacle to overcome in this space is the very definition of measurement itself: "a set of observations that reduce uncertainty where the result is expressed as a quantity". Measurement does not need to be exact. In fact, it is often the case in many fields of work that exact measurement is not even possible, and in other cases the cost is too high or time is too short to arrive at exact measurements. Probability calibration is one of the tools presented in the early chapters of this book to prepare the reader for what follows. Essentially, the goal of this tool is to help the reader assign levels of confidence to numeric estimates of quantifiable items in order to help move to estimates of the seemingly immeasurable. Many practical examples are discussed throughout the book. Diagrams and sidebars are extremely well placed. Very well recommended.
October 20, 2008

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