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How to Measure Anything: Finding the Value of Intangibles in Business, by Douglas W. Hubbard
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Anything can be measured. This bold assertion is the key to solving many problems in business and life in general. The myth that certain things can't be measured is a significant drain on our nation's economy, public welfare, the environment, and even national security. In fact, the chances are good that some part of your life or your professional responsibilities is greatly harmed by a lack of measurement-by you, your firm, or even your government. Building up from simple concepts to illustrate the hands-on yet intuitively easy application of advanced statistical techniques, How to Measure Anything reveals the power of measurement in our understanding of business and the world at large. This insightful and engaging book shows you how to measure those things in your business that until now you may have considered "immeasurable," including technology ROI, organizational flexibility, customer satisfaction, and technology risk. Offering examples that will get you to attempt measurements-even when it seems impossible-this book provides you with the substantive steps for measuring anything, especially uncertainty and risk. Don't wait-listen to this book and find out: -The three reasons why things may seem immeasurable but are not -Inspirational examples of where seemingly impossible measurements were resolved with surprisingly simple methods -How computing the value of information will show that you probably have been measuring all the wrong things -How not to measure risk -Methods for measuring "soft" things like happiness, satisfaction, quality, and more -How to fine-tune human judges to be powerful, calibrated measurement instruments -How you can use the Internet as an instrument of measurement A complete resource with case studies, How to Measure Anything illustrates how author Douglas Hubbard-creator of Applied Information Economics-has used his approach across various industries. You'll learn how any problem, no matter how difficult, ill-defined, or uncertain, can lend itself to measurement using proven methods. Straightforward and easy-to-follow, this is the resource you'll refer to again and again-beyond measure.
- Sales Rank: #386081 in Books
- Published on: 2010-04-12
- Ingredients: Example Ingredients
- Original language: English
- Number of items: 1
- Dimensions: 9.30" h x 1.10" w x 6.30" l, 1.09 pounds
- Binding: Hardcover
- 320 pages
Amazon.com Review
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 can we measure the population of fish in a lake? And how is that like measuring unsatisfied customers who didn’t complain or measuring security breaches that were not detected? How can we isolate the effect advertising has on sales when a vast amount of unknowns also affect sales? How did an 11-year old girl use a simple measurement to debunk a popular practice in medicine? How did intelligence analysts in WWII estimate the monthly German tank production by an analysis of serial numbers of captured tanks? How do we measure quality, risk or innovation? How do we know what to measure in the first place? The answers are easier than you might think. The idea that some things are utterly immeasurable is based on just three common misconceptions. As I explained in How to Measure Anything, the three misconceptions can be overcome and powerful measurement methods can be applied to resolve just about any problem. The misconceptions are Concept, Object and Method (you can remember them as .com). The concept of measurement refers to the meaning the word “measurement” is assumed to have. Some things are thought to be immeasurable only because it is believed that measurement must be some exact value. But the more pragmatic scientific approach to the term measurement is to treat it as quantified uncertainty reduction based on observation. If you have a wide range of possible values for the percentage of customers who would prefer a new product, all you really need is a reduction in that uncertainty to make a better bet about a new product. The second misconception about measurement is the objective of measurement itself. If “strategic alignment”, or “employee empowerment” seem immeasurable, it is only because they are – initially – ambiguous. But if they are important to a business, then they must have observable consequences. They must have some impact on some decision (otherwise they wouldn’t need to be measured at all). And so they must be detectable in some manner, directly or indirectly. The third misconception is about methods. Obscure but well-developed methods already exist for more types of measurement problems than most managers realize. Controlled experiments, variations on random sampling methods, and some very simple but non-obvious methods can be used in many practical business situations. While many measurements feel daunting at first, the fact is that we often have more data than we think, we need less data than we think, and getting more data through observation is simpler than we think. And, above all else, no matter how challenging a measurement problem appears, we should assume that we are not the first to measure something like it. Any measurement problem you encounter will very likely already have a practical solution. You only need to know about it. Once these imaginary obstacles have been overcome, there are practical measurement solutions that can be applied to any uncertain decision. We can quantify any uncertainty and then compute the value of reducing that uncertainty by measurement. Where the value of information about a measurement is very high, my book explains how to employ sampling, controlled experiments, and even more methods in a way that makes it approachable for any manager.
Review
"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 and defense, healthcare, politics, etc." ---Ricardo Valerdi, Ph.D., Lecturer, MIT
Review
"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."
—Strategic Finance
"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.
Most helpful customer reviews
20 of 20 people found the following review helpful.
Extremely Practical for any Risk Manager
By ccooper
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.
7 of 8 people found the following review helpful.
Pretty good introduction to measurement for business problems
By Bas Vodde
"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.
4 of 4 people found the following review helpful.
Highly recommended for all who do or do not believe in quantification
By N. Tuzov
My Ph.D. coursework revolved around advanced quantitative methods, and therefore I did consider many real-world things to be immeasurable. Indeed, lots of practical cases involve small sample sizes, a large number of factors that can influence the outcome, and many other sources of uncertainty. Such problems are not very amenable to advanced quantitative methods. They may appear absolutely hopeless, but not if you switch to the decision making framework described in this book.
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.
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