- Hardcover: 320 pages
- Publisher: Wiley; 2 edition (April 12, 2010)
- Language: English
- ISBN-10: 0470539399
- ISBN-13: 978-0470539392
- Product Dimensions: 6.3 x 1.1 x 9.3 inches
- Shipping Weight: 1.2 pounds
- Average Customer Review: 155 customer reviews
- Amazon Best Sellers Rank: #617,533 in Books (See Top 100 in Books)
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How to Measure Anything: Finding the Value of Intangibles in Business Hardcover – April 12, 2010
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Now updated with new research and even more intuitive explanations, a demystifying explanation of how managers can inform themselves to make less risky, more profitable business decisions
This insightful and eloquent book will show you how to measure those things in your own business that, until now, you may have considered "immeasurable," including customer satisfaction, organizational flexibility, technology risk, and technology ROI.
- Adds even more intuitive explanations of powerful measurement methods and shows how they can be applied to areas such as risk management and customer satisfaction
- Continues to boldly assert that any perception of "immeasurability" is based on certain popular misconceptions about measurement and measurement methods
- Shows the common reasoning for calling something immeasurable, and sets out to correct those ideas
- Offers practical methods for measuring a variety of "intangibles"
- Adds recent research, especially in regards to methods that seem like measurement, but are in fact a kind of "placebo effect" for management – and explains how to tell effective methods from management mythology
Written by recognized expert Douglas Hubbard-creator of Applied Information Economics-How to Measure Anything, Second Edition illustrates how the author has used his approach across various industries and how any problem, no matter how difficult, ill defined, or uncertain can lend itself to measurement using proven methods.
How Everything Can Be Measured
Amazon-exclusive content from author Douglas Hubbard
"How to Measure Anything was already my favorite book (just ahead of Hubbard's second book, The Failure of Risk Management) and one I actively promote to my students and colleagues. But the Second Edition, improving on the already exquisite first edition, is and achievement of its own. As a physicist and economist, I applied these techniques in several fields for several years. For the first time, somebody wrote together all these concerns on one canvas that is at the same time accessible to a broad audience and applicable by specialists. This book is a must for students and experts in the field of analysis (in general) and decision-making."
—Dr. Johan Braet, University of Antwerp. Faculty of Applied Economics, Risk Management and Innovation
"Now, performance measures can be defined for even the most difficult problems. Doug Hubbard's book is a marvelous tutorial on how to define sound metrics to justify and manage complex programs. It is a must read for anyone concerned about mitigating the risks involved with Capital Planning, Investment Decisions and Program Management."
—Jim Flyzik, former Government CIO, White House Technology Advisor and CIO Magazine Hall of Fame Inductee
Praise from How to Measure Anything, First Edition
"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,' to put something into context, to find insight to help us get our jobs done, to be more successful, to discover things, or to build things. 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, Ph.D., M.D., Chief Technology Officer at CyberTrust and inventor of the first antivirus software
"Interestingly written and full of case studies and rich examples, Hubbard's book is a valuable resource for those who routinely make decisions involving uncertainty. This book is readable and quite entertaining, and even those who consider themselves averse to statistics may find it highly approachable."
"Hubbard has made a career of finding ways to measure things that other folks thought were immeasurable. Quality? The value of telecommuting? The risk of IT project failure? the benefits of greater IT security? Public image? He says it can be done—and without breaking the bank.... If you'd like to fare better in the project-approval wars, take a look at this book."
—ComputerWorld, August 2007
"I use this book as a primary reference for my measurement class at MIT. The students love it because it provides practical advice that can be applied to a variety of scenarios; from aerospace & defense, healthcare, politics, etc."
—Ricardo Valerdi, PhD, Lecturer, MIT
"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 MetaMetrics, Inc.
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One simple idea is that, as long as the experiment reduces the costly uncertainty by the amount that is larger than the cost of research, it is worth performing. For instance, many experiments that may appear meaningless to a "classical" statistician because of their small sample size can be well justified once the benefit of uncertainty reduction is taken into account. The flipside is that if a study is well funded, well designed and replicated from the statistical viewpoint, it can still be useless. If our goal is to reduce the uncertainty to below a pre-specified threshold, then the "statistically" large sample size may still be unable to do the job. If the study is too expensive compared to the value of reduced uncertainty, it is not worth doing either. Another negative scenario is when we invest resources into measuring a variable that would make a small contribution to the uncertainty of the final outcome even if we knew the exact distribution of the variable.
The book provides numerous examples that would be hard to crack for a "classical" statistician, and yet they are very amenable to the Applied Information Economics method developed by Mr. Hubbard. I can highly recommend it to all who "do not believe in statistics", as well as to the young quantitative analysts who want to expand the set of applications they can handle successfully.
Most capital investments are poorly analyzed. Doug Hubbard provides remedies for the common shortcomings:
o Typical cost-benefit analyses use single-value best estimates for inputs; these ignore or inadequately address risk and uncertainty. Also, often, important benefits are omitted because they are "intangibles" such as "improved customer service." Remedies in the book: Capture expert judgments as probability distributions; then solve the forecast model with Monte Carlo simulation. Decompose and explicitly represent former-intangibles in measurable units.
o Multi-criteria scoring approaches often feel good yet have little theoretical foundation. They are entirely subjective and have not been shown to improve decision-making. Remedy: clarify the business (or other) objective and craft a quantified decision policy accordingly. Judge and/or model inputs in meaningful, quantitative terms.
Everything important to a decision should be in a forecasting model. And everything in those models is either structural or quantified.
For me, three primary themes emerge in the book:
1. Calibration. Hubbard asserts that everything can be quantified--and he enjoys challenging individuals and groups to find any exception. Most people, even if expert in their field, are biased when making judgments. Hubbard shows ways to "calibrate" these experts (including the reader) with perhaps a half-day of practice. Most readers (as did I) will find that they initially fare poorly on the engaging calibration exercises in the book. We suffer from overconfidence and other cognitive biases. With feedback and practice, most people can quickly improve at assessing probabilities and probability distributions, and confidence ranges.
2. What needs to be measured further? The most interesting calculation in the book is a form of sensitivity analysis. Which variables are most important to measure further? Hubbard calculates the value of perfect information for each variable with a straightforward expected opportunity loss calculation. Though an analysis may have dozens of identified variables with uncertainty, in his experience typically only 1 to 3 variables are worthy of further measurement.
3. Deliberately seek information about the most-important risks and uncertainties where the additional time and cost are justified. This usually means obtaining more data with targeted investigation. Hubbard offers these encouraging maxims:
o It has been done before
o You have more data than you think
o You need less data than you think
o It is more economical than you think
Additional highlights of the book include:
o Abundant war story examples. Much of Hubbard's work has been in the information technology (IT) sector. I especially enjoyed the case about forecasting fuel consumption for the U.S. Marine Corps.
o Demystifying parameters that the reader might initially think as "intangibles." For example, "Improved Customer Service" might be measured in terms of percent of customers re-ordering; percent of returns; average delivery time, etc.
o Example calculations, all done with Microsoft® Excel. He hosts a website, [...], where the reader can download example calculation worksheets, additional calibration quizzes, papers, articles, and reader comments.
The first edition is excellent. Upon learning of a second edition, I immediately bought the updated book for a fresh re-read. This was again a good investment of time and money. The new edition is updated, expanded (about 15%), and more crisp. The editing and layout are again excellent. Several references are now embedded to his other best-selling and companion book, The Failure of Risk Management.