Finding the Value of Intangibles in Business - How to Measure Anything

As a professor of Risk Management and Insurance at the College of Charleston, I would like to heartily endorse Douglas Hubbard’s masterpiece, “How to Measure Anything.” Hubbard gave the old, consensus based world of risk consultants a good shake out with “The Failure of Risk Management.” I use that book in conjunction with How to Measure Anything to show business students how to come to terms with seeming intangibles. One of the hardest habits which we have drilled into our students from birth is to have an exact answer or remain silent. This absolutist mentality is broken when we demonstrate that measurement is really a reduction in uncertainty and that any such reduction can lead to huge cost savings. Add in that most businesses measure the least important things the most, and the most important things the least, and we come to understand why things went so wrong in 2008 despite the so-called “expert knowledge.” It is wonderful to watch the student’s lights come on as they realize and grasp the fact that nothing is intangible. I also use Hubbard’s work to show that persons who seem to magically tame randomness can become significant masters in their chosen business profession. It isn’t magic, it’s Hubbard!

Lord Kelvin penned those words generations ago, but the sentiment is as valid today as it was then.

Douglas Hubbard's Third Edition of "How to Measure Anything" helps you figure out what to measure and how to measure it.

This book is in its third printing for a reason. It is extremely useful and practical material for any decision-maker responsible for resource allocation.

Truth in lending. Yes, there is a trick to Hubbard's approach, but it is a good "trick." Hubbard defines measurement as a way of decreasing uncertainty through observation. That seems like a reasonable approach, and then, when you combine that definition with the goal of measurement ultimately to be an input to decision-making, you realize that, while you might not want to measure everything, given Hubbard's definitions, the one's that you don't want to measure are not very important to you.

Hubbard starts with what he calls "the clarification chain": if matters, it is detectable; if it is detectable then you can characterize the amount or relative amount of something; and, if can be detected then it can be measured.

The author covers some common objections or complications in measurement in some detail. For example, he describes how you can reduce a large amount of uncertainty through a small number of random samples. Hubbard describes how you can gain information on the observable variables even when unseen forces are at work, and he describes how to tease out subjective preferences and values.

One of the things that I appreciate about this book is that Hubbard also identifies legitimate objections to measurement. For example, there might be good moral or economic reasons for not measuring something.

Likewise, Hubbard cleverly points out that the following four statements are often true. The items has been measured before. You already have more data than you think. You don't need as much data as you imagine you do, and getting new observations is often easier than imagined.

The next section of the book describes setting up measurement for success. Since the ultimate objective of measuring a particular item is to reduce uncertainty to facilitate decision-making, you need to focus on what decisions are being made, and what the sources of uncertainty are. Once you have established what the major uncertainties are and how to decrease those uncertainties, you can make an informed decision on how much data you need to gather.

The remainder of the book (and the bulk of the new material from the first edition to the third edition) revolves around "soft information" gathering, e.g., preferences, ranges of values, etc.

The section on traditional, engineering measurement gathering is excellent.

Also, kudos to Hubbard for stating firmly on multiple occasions that correlation does not equal causality.

He spends a good amount of time on determining how and what to model to reduce uncertainty.

The book is worth its cover price for this section alone!

I highly recommend this book!

In service,

Rich

The book is about measuring factors that are important to making a decision, not just measurement for the sake of quantification. That may not be obvious, but it is a driving premise for the text. The book is well written, well organized, intelligent and deals with valuable concepts not addressed elsewhere in such an accessible manner.

If you’ve read the second edition, you don’t “need” to read the third; in a real sense it is more of the same. It’s “good” more of the same, you won’t waste your time, but there’s no new revelation. Even the chapters sync between the second and third edition. 42% more pages. I read and have occasionally referred to the second edition, no regrets about investing about 5 hours in the third edition, but I work in this field.

If you haven’t read a previous edition and you’re involved in making decisions involving many factors and with significant consequences, then this is a MUST read.

Understand, the title is NOT “How To [Easily] Measure Anything.” Hubbard’s “Defninition of Measurement” is “A quantitatively expressed reduction of uncertainty based upon one or more observations.” As Hubbard admits, it’s more of an “information theory” slant on measurement. That’s different than what most people think about measurement or quantification, but it is both interesting and useful, sometimes powerful.

At the risk of oversimplification, Hubbard’s premise is that there is always a way to economically improve the value of information by reducing the uncertainty associated with the information. His book focuses on things most people would, and have argued, can’t be measured, say the “value of IT” to an organization. You may not get to a hard metric, like a four decimal ROI, but you might get to a CI (confidence interval) of value.

Hubbard argues that his heavy use of statistical concepts is accessible because he largely eliminates the need for a reader to execute any heavy math, but if you haven’t had at least one course in statistics that you remember, the concepts are still valuable, but you’re not going to be able to execute much on your own.
Hubbard works with a process he invented, which he calls Applied Information Economics (AIE), which is adequately described in both the second and third edition, as follows:

1. Define the decision and the variables that matter.
2. Model the current state of uncertainty about the variables
3. Compute the value of additional measurements
4. Measure the high-value uncertainties
5. Make a risk/return decision after the economically justified amount of uncertainty is reduced.

Step 1, which is foundational to any decision, can be very difficult, and is often revisited and evolves over the course of a complex decision. The difficulty in identifying the variables that matter isn’t discussed much in the book.

AIE is an approach to “multi-criteria decision making,” there are many other approaches, but at some point they usually require “valuing” each of the criteria and that’s where “How to Measure Anything” is worth the read.

At the end of the read, will a reader be able to “measure anything?” For most, the answer is “no.” Hubbard spends about 12 pages on modeling and simulation and that’s fair, this isn’t an M&S book, but the skills and tools required are substantial and pivotal to much of what the book is about. Second, this is a book about measuring, or improving the value of information to be used in making a decision. It is not a book about the decision process as a whole.

I am an Earth scientist who often find myself doing all kinds of guesstimation and probabilistic analysis of real-world phenomena for which there is very little or no data at hand. It was very nice to find how the author explains many of the informal methods my colleagues and I use everyday in our work, although applied to different contexts, particularly in business and project management. This is a good thing, because it shows that many estimation problems are fundamentally the same independently on the field in which they appear. I found this book an interesting primer in how to develop measures for things that are usually considered outside quantification or even evaluation. The author explains useful approaches and gives many valuable examples. This is a book that deserves to be read twice, and the techniques explained in it deserve to be put in practice (yes, even in trivial matters, for the sake of practice). Very recommendable.

Having said that I also want to point out a few (forgivable) glitches. As is usual for the business or managerial literature there is ample use (and abuse!) of acronyms. Some acronyms are OK, but having a dozen or so of them in every chapter is annoying, breaks the flow of the reading experience and is also bad literary taste. Please Mr. Hubbard, think of this for a next edition!
There is also the question of Excel. I understand that in the world of managers and accountants this is the tool of choice, and that these people are possibly the main target readers. Note however that Excel is despised (on good grounds) by scores of scientists and engineers, who are likely also part of your audience. A few examples with other tools will do no harm.

I procrastinated about reading this book because it appeared to be only relevant to a narrow type of business problem. But it is much more ambitious, and aims to convince us that anything that matters can be measured. It should be a good antidote to people who give up on measuring important values on grounds such as it's too hard or too subjective (i.e. it teaches people to do Fermi estimates).

A key part of this is to use a sensible definition of the word measurement: "A quantitatively expressed reduction of uncertainty based on one or more observations".

He urges us to focus on figuring out what observations are most valuable, because there are large variations in the value of different pieces of information. If we focus on valuable observations, the first few observations are much more valuable than subsequent ones.

He emphasizes the importance of calibration training which, in addition to combating overconfidence, makes it hard for people to claim they don't know how to assign numbers to possible observations.

He succeeds in convincing me that anything that matters to a business can be measured. There are a few goals for which his approach doesn't seem useful (e.g. going to heaven), but they're rarer than our intuition tells us. Even vague-sounding concepts such as customer satisfaction can either be observed (possible with large errors) via customer behavior or surveys, or they don't matter.

It will help me avoid the temptation of making Quantified-Self types measurements to show off how good I am at quantifying things, and focus instead on being proud to get valuable information out of a minimal number of observations.

This was a fascinating read that I personally found somewhat inspirational. Packed with clear examples and written in an infectiously enthusiastic style, the book is extremely convincing in persuading the reader that truly anything can be measured. The author doesn't attempt to produce a template for approaching these difficult problems - instead, you're left with the sense that you will need a unique and ingenious solution once you commit to what it is that needs measuring.

Anyone with average math will understand the examples and there's nothing overly statistical in the text, apart from a couple of short sections. I haven't read the previous editions but would highly recommend this for students and business managers interested in applying measurement and data-driven models to difficult real world problems where most people throw up their hands.

Hubbard explains how to "find the value of intangibles in business." An excellent book and one which should be on every manager's book shelf.

Hubbard has made what can be a deadly dull subject interesting and accessible. I found several examples for measuring exactly what I needed and always felt I could not measure. This book is a must read for leaders including the Master Six Sigma Blackbelt on your staff. Finding the value of intangibles in business has always been a challenge. How to Measure Anything is full of practical ideas for getting to a measurement.

Measurement: reducing the uncertainty. As long as we are not willing to accept a best guess, or educated estimate, or range of possibilities for a difficult to measure item we will not move forward. Our decisions will be flawed. Hubbard put forth these four assumptions which I found to be most useful when thinking about measuring:

1. Your problem is not as unique as you think
2. You have more data than you think
3. You need less data than you think
4. There is a useful measurement that is much simpler than you think.

Numbers can be used to confuse people; especially the gullible ones lacking basic skills with numbers. Therefore we, as leaders, must be committed to making sure the whole organization is data driven and understands the way we can reduce uncertainty through the straight forward techniques Hubbard explains. As he states, "The fact is that the preference for ignorance over even marginal reductions in ignorance is never the moral high ground."

Hubbard gives us a very useful check list for a Universal Approach to Measurement:
1. What are you trying to measure? What is the real meaning of the alleged "intangible?"
2. Why do you care -- what's the decision and where is the "threshold?"
3. How much do you know now -- what ranges or probabilities represent your uncertainty about this?
4. What is the value of the information? What are the consequences of being wrong and the chance of being wrong, and what, if any, measurement effort would be justified?
5. Within a cost justified by the information value, which observations would confirm or eliminate different possibilities? For each possible scenario, what is the simplest thing we should see if that scenario were true?
6. How do you conduct the measurement that accounts for various types of avoidable errors (again, where the cost is less than the value of the information)?

I especially enjoy the approach Hubbard takes to quantify the cost of making measurement based on the value of the information obtained. Too often, I have seen projects founder on either inaction to get data which would be of great value and little cost or, perhaps, the exact opposite -- spending great amounts of time and money to obtain relatively useless information.

To emphasize: After reading Hubbard's excellent book on `How to Measure Anything,' I was able to immediately solve several measurement challenges for my CEO and Business Owner colleagues. This book makes accessible measurement techniques that have eluded many of my colleagues. It should be on every manager's desk. - Dave Kinnear, CEO dbkAssociates, Inc. and Vistage Chair.

Strengths:
1) Sort of unique book on a very interesting subject. Usually the quantitative risk theme refers to finance/derivatives, but this one is broad and business oriented.
2) Gives you perspective. I certainly know more things after reading it.

Weaknesses:
1) Very wordy, tends to be almost philosophical occasionally.
2) Trying to be intuitive, it leaves out maths but occasionally assumes that the reader is aware of several specialist concepts. This is a structural contradiction (I come from a science and business background and still didn't know a number of things that were left unexplained).
3) In contrast, it overanalyses easy and intuitive concepts, accessible even by the layman in the first place.
4) Includes excel sheets and uses them heavily. The whole flow depends on them. Very excel oriented (for my taste, other people may like it).
5) Numerous references to the author's seminars. Measure how many such references before start feeling like you are reading a teaser for the seminars/certification.
6) Tables and figures in the Kindle book are not readable if you do not change your setup (orientation etc.).

In the auction market, finding the value of anything is easy. A trade name or a customer list, for example can be auctioned off to the highest bidder and "value" can be found in the form of cash. What if the need for "value" of an intangible is needed for strategic decisionmaking? That is far more elusive. You have no "competitive market" to arrive at valuation. How to Measure Anything, helps you with the objective tools for arriving at value in absence of a market. The text is accessible to the non-mathematician. A valuable aid to any executive involved in strategic decision making.

This is my second copy of this book. I purchased the previous one, but after moving, had lost it. When I saw it on Vine I ordered it. It's like revisiting an old friend. The key point in the book I feel is to use experience to measure the "unmeasurable". Many of us double check data against related information we already have stored in our brain, to see it the new data makes sense and appears legitimate. Most of us do this somewhat unconsciously. The author takes such thinking from the subconscious, and "formalizes" it. A very useful tool, and helpful in getting me to increase my "thinking outside the box". I recommend it to any who analyze data, have to quantify the "unquantifiable", and similar, in work or in life.

If you think all business books are all banal fluff designed to promote the careers of their authors, this one book disproves your theory. This almost makes this book a black swan (highly improbable that it exists at all, given the crushing weight of evidence that nearly all business books are, in fact, banal fluff) but the fact that it is widely used, widely quoted, and now on its third edition should dispel any disbelievers.

Yes, this book is the real deal. It is the book that makes people who struggle with algebra able to quantify schedule risk, information value, and calculate probability using simple formulas and tools. Jack Stack makes it a widely known fact that he expects all employees, even those on the factory assembly line, to be able to read a balance sheet. This isn't just some fad he obsesses over - the impact is real and is very positive. The same can be said for anyone, anywhere, about knowing how to use basic knowledge to quantify every day things, even things that are "intangible." This book gets you there faster than anything else I've seen.

This book does appear daunting, and requires both very intensive reading and exercises for you to do on your own. You're simply not going to get it all unless you put the book down and try it out. This can be very uncomfortable for people who consider themselves quantitatively illiterate, but the assurance is there are no prerequisites other than a first grasp of the English language (or whatever language this book is translated into). And once you're using what you learned the book in your daily life, you'll have a better sense of what quantitative skills you need to improve, so you don't end up taking a dozen math courses to learn the one missing element that actually matters.

Douglas made this book to be used, to bring us out of the shadows of quantitative ignorance and give us all the power to challenge BS statistics, measure the risks and values in our lives and in our businesses, and as a result, live better and more enlightened lives. This is important stuff, so don't sleep on it. Definitely recommended.

As a Manager in a medium-sized financial investments firm in Dallas, measurement is an on-going aspect of the job. But the big problem with managing investments, potential investments, and portfolio combinations (in other words, how much of each security from a specific industry should we add to our holdings to raise or lower our risk and therefore possible income) is knowing WHAT to measure and HOW to go about trying to turn a "squishy" or as the author more accurately puts it, intangible aspect of an investment into an aspect we can quantify, measure, and follow.

The CEO of GoDaddy once said that everything gets better when you measure it. After all of our staff read this book, that has become one of our company's de facto standards. We find that if we closely follow data related to our progress as a company AND as individuals that all our stats improve and over time our company's wealth as well as our own incomes rise accordingly. That is the key to why How to Measure Anything: Finding the Value of Intangibles in Business has become part of my desk reference in many ways. It taught me to focus on measurements that I was not doing and it allows our other Managers to do the same much more effectively. You can't just buy a statistics package for a PC and think you're measuring anything helpful! That kind of Black Box approach doesn't cut it because you don't know the WHY behind what is being tracked and often you don't know the underlying algorithm that produced those measurements.

I really want to stress that the major benefit How to Measure Anything had on my company and why the impact was so important is due to us learning that many of the factors before that we assumed could not be measured were just wrong. Not that the factors were wrong, WE WERE for thinking there were pieces of important data that we simply couldn't measure well or accurately. If it's important, it CAN be measured and we are fully versed now in separating out what we need to measure and then systematically going about doing so. Thinking something was immeasurable was our biggest mistake and correcting that mistake has turned our company into a measuring machine. There is just NO WAY that our competition is following the same data and therefore getting the same results we have been since we changed the way we approach our key data. And even though I'm in the investment field this book would be invaluable in so many other places, more so than I could ever think of but of course engineering, banking, brokerages, education, and financial-related policy jobs certainly NEED the info here. This should be required reading of every pre-MBA student as well as every employee at any firm that needs to track data closely to improve bottom-line results.

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.

Hubbard has done it again. Even if you own previous iterations of this book, it's worth getting this edition for the updates.

Hubbard makes sense out of measuring things that normally aren't measured. Accurate, meaningful measurements are at the heart of good business decisions.

The author has provided lots and lots of examples - which help to drive the information home so that a manager can implement. However, the book is written in a very accessible manner, so I actually enjoy reading it (compare that to almost any other business book).

As operation consultants, the measurement of intangibles is an important part of the work we do for clients every day. In this context; the development of measurement systems is always a challenging task. As a solution, this book provides a concise reference of several integrated measurement strategies which are particularly useful. This information reminded me that significant process improvements are often possible when using even the most basic measurement systems if none existed before. As a result, I have always thought about how measurements can be most effectively created and applied in practice. The author has provided a holistic viewpoint of measurement topics, which is why I wish I had written this book several years ago. I could have used the practical information that it contains.

This is an excellent business decision making and consulting guide, which relies on a combination of statistical and behavioral measures. It is particularly applicable to decisions involving risk, valuation, and the value of information. It is not as is stated in the first half of the title a guide to "Measuring Anything"; for example little insight is provided that would be applicable to measurement of physical quantities, or rates and bottlenecks in a factory. Some methods discussed while insightful involve non-standard definitions of quantities. For example a behavioral measure of correctness based on knowledge sufficiency tests is given as an example of Confidence Intervals, rather than the conventional definition of Interval Estimates in a Normal Probability Distribution.

I highly recommend this text as an addition to the Internal or External Consultant's library. It is a valuable set of insights into business decision making.

This book is a 'must read' for researchers, especially those interested in achieving impacts in the real world. Hubbard pulls together the best elements from a number of fields related to decision sciences and combines them in a way that can be practically applied to real world problems.

Applied Information Economics will challenge researchers - they will find out that they are probably not researching the right things to improve real world decision making, and that they are collecting far more data than needed.

I used to feel very uncomfortable when asked to quantify research impact pathways; but being able to put uncertainties on variables in a model changed all that - you just express your degree of uncertainty, and then see if you really need to put more research into narrowing it. This greatly increases the efficiency of research. In addition, expressing uncertainties also frees you to include in a model anything you think is important - this encourages holistic thinking and ensures you do not miss important costs or benefits in your analysis.

This book should be compulsory reading for all applied researchers.

Keith Shepherd, Agricultural Research Scientist

I teach Risk Management and Insurance at the College of Charleston. As an Executive-in-Residence Professor at the School of Business, I must praise Douglas Hubbard's masterpiece "How To Measure Anything." I am very impressed with the Grounding in fact, hard scientific fact that this book deploys. But amazingly once this is accepted, the intangibility of the unknown or unmeasured ceases or falls away! Some people get frightened by what they misunderstand. In addition many persons, even at the commanding heights of business, treat statistics and mathematics as some sort of magic. Perci Diaconis, Stanford's Chairman of Statistics and Mathematics often talks about how scoundrels, card sharks, hustlers, hucksters and thieves play with deception and seemingly complicated processes to trick us (usually out of our money!). Even expert management consultants prey on such vulnerability. I think that naysayers to this book fear having clear statistical light shine upon their less scientifically rigorous efforts.
What is doubly remarkable though is how enjoyable this book is to read. Good math and science is great philosophy. Remember that instruments such as a compass, square, level, and scale were once referred to as philosophical instruments. ; Science itself used to be called natural philosophy. I know that my students will learn a great deal from this book along with Hubbard's other great work "The Failure of Risk Management." Together we will be removing uncertainty and replacing it with a clearer light!

Successful business is based on experiment and measurement. You can't manage what you can't measure. Turns out you can measure everything and so you can manage everything. Douglas Hubbard wrote an awesome book to help us build a habit to reduce decision-making uncertainty by attempting to measure the decision factors. Read this book to build such a habit and succeed.

A colleague of mine from work had the 2nd edition of this book sitting on his shelf. After thumbing through it for a bit I borrowed it and am so happy I did! There are so many “Aha” moments in the book that directly relate to my own work, that I waited for the 3rd edition to come out, purchased it, and read it cover to cover.

Hubbard starts with shattering the myth that some things just can’t be measured (if it can be observed, it can be measured), then goes on to give methodology with understandable and relatable real-world examples from his own work. I highly recommend this book to anyone in management or consulting.

In my opinion, "Anything Can Be Subjectively Estimated" is a more accurate title, i.e. I am replacing "measure" with "estimate" and taking out "how to". This book contains much useful information, but the content is still insufficient for the bold title. I find it a bit boring to read. It is a rather lengthy book, and I had a hard time getting through the later chapters. It is a business book and reads like one.

Doug continues to impress with his latest (third edition) book How To Measure Anything. His ability to convey the material in a way "non math majors" can consume it makes it a fascinating read. The third edition brings a lot of new material over the second edition which I already own. Doug just has an ability to make measuring things seem easy and puts to rest so many common myths. His insights, humor, and examples in so many areas just help you to understand the concepts presented. The added materials provided make this book a must have and worth every penny!

Doug Hubbard’s How to Measure Anything is an immensely useful tool for anyone looking to improve their business decision-making. For several decades, it has been a well-understood social science principle that quantitative models have several advantages over expert intuition (a topic that’s covered extensively in the book). The potential applications within the business world are vast, yet seriously underappreciated, and this book does as good a job as any for guiding a reader to their utilization.

The book advocates a method called Applied Information Economics, which is thoroughly explicated with example calculations and practical applications, such that a reader can practically become a practitioner on their own.

The third edition of How to Measure Anything is updated with considerably more example calculations, further improving the accessibility of the material. The section on Bayesian methods, for example, is as thorough as some introductory statistics textbooks on the calculations, but infinitely more accessible with real-world case examples and applications to commonly perpetrated myths (e.g., “Correlation is not evidence of causation”, Bayes’ Theorem tells us that it is!).

Doug Hubbard’s How to Measure Anything is an immensely useful tool for anyone looking to improve their business decision-making. For several decades, it has been a well-understood social science principle that quantitative models have several advantages over expert intuition (a topic that’s covered extensively in the book). The potential applications within the business world are vast, yet seriously underappreciated, and this book does as good a job as any for guiding a reader to their utilization.

The book advocates a method called Applied Information Economics, which is thoroughly explicated with example calculations and practical applications, such that a reader can practically become a practitioner on their own.

The third edition of How to Measure Anything is updated with considerably more example calculations, further improving the accessibility of the material. The section on Bayesian methods, for example, is as thorough as some introductory statistics textbooks on the calculations, but infinitely more accessible with real-world case examples and applications to commonly perpetrated myths (e.g., “Correlation is not evidence of causation”, Bayes’ Theorem tells us that it is!).

This text was assigned for my masters program. I Liked the overall message: that everything can be measured. I found his methods very logical and helps you break down the "impossible." I liked the self evaluation and the use of confidence intervals.

Being a network and telecom consulting company, we have read many math books, but "How to Measure Anything" is one of the few math books that gave us clearer vision on how to quantify value in your network/telecom including the intangibles and also how to quantify your network/telecom risk. The chapters are strategically aligned and easy to follow and you don't have to be a statistician/mathematician to execute on the logic. We found it as an enjoyable book to read

Ray Mota, PhD
Managing Partner
ACG Research

Doug brings a no nonsense, pragmatic approach to measuring value. His economic methods and practical examples make it easy to understand and discuss. This is a critical reveleation needed for both private and public sector organizations. No more excuses! Put a measurement system in place! All organizations have patterns, and Doug's methods prove that by uncovering the relationships with the data. Don't let the squeaky wheel guide your organization, use a solid measurement appraoch as explained in this book.

Hubbard displays an intuitive writing style. The book illustrates his clear understanding of an otherwise enigmatic subject. His ability to present and convey information that affords the reader true clarity is marvelous. With this book, executives can measure and assign value as a machinist measures part specifications using a vernier micrometer!
An Absolute Must-Have for the Executive Toolbox!!

I'm not a data scientist or a forensic accountant, so I was a little intimidated, even reluctant to buy this book. I'm so glad I got over myself! Mr. Hubbard is able to present some of the most seemingly complicated subject matter in a way that just about anyone can understand and, best of all, APPLY IMMEDIATELY!!

After reading the beautifull book by Mr. Hubbard I finally understood that obstacles wich appear in a business are not unpassable and if you follow his advice about the surpassing the misconceptions then you will be on your way. I particularly loved the section of the book about customer satisfaction because a satisfied customer will allways come back. A must have if you plan to develop or make a better business

Doug Hubbard’s How to Measure anything teaches us how to quantify things that are generally assumed to be totally immeasurable, such as security and flexibility. There are plenty of example calculations, allowing the reader to implement such measurements in their own business operations. This book is a powerful tool.

I was really excited and hopeful to gain some insights on many of the age-old problems when I stared reading. I moved this book to the top of my reading list, and was disappointed by the time I get to chapter 3. The author really doesn't know anything that I didn't know and my most challenging measurement problems remain just as challenging as before. It's not a total waste of time, but definitely not the experience that I had hoped for.

I am reminded of Margaret Thatcher's quip that being powerful is like being a lady...if you have to tell people that you are? You aren't. If you have to constantly tell people how important your ideas are? They probably aren't. Real-world risk management is inexact and highly qualitative. It cannot be made as quantitative as Hubbard suggests without losing its connection to what you are really measuring. Hubbard's entire approach seems to be that the only valid approaches to risk management are quantitative. As a real world risk manager? That isn't true...it feels good to those uncomfortable with the complexities and the nebulous nature of true risk, but real world risk management is much closer to Frank Knight's definition of "uncertainty", which by definition lacks sufficient historical context to manage quantitatively. Hubbard wrote an interesting book, with some good insights, but I don't see any of the really effective risk management professionals (all with graduate degrees and experience at least as extensive as Hubbards) using the ideas he promotes. I have been a risk professional for a decade, and have worked with some very experienced and educated risk professionals with backgrounds with some of the most prestigious companies in the country. Real-world risk managers do not only (or even largely) do the stuff Hubbard talks about. Because it doesn't work the way he suggests it does. His ideas are interesting, once you get past the self-serving arrogance, but they need to be taken in context; this isn't how the real world works; quantitative techniques are great, but in many cases qualitative "soft" approaches work much better. This book is definitely worth reading, but keep in mind that the approaches discussed only comprise a fraction of the techniques necessary t be a good risk manager, and the underlying theme that these techniques are superior are disputed by many in the field.

There is a world of difference between knowing you CAN measure anything and knowing HOW to measure anything. The author demonstrates convincingly that anything can be measured, but was not a bit of help in teaching me HOW to measure any of the intangables I work with.

In one section he explained how seperating the cause and result where a result has many variables is difficult. What he did not do is give any concrete information on how to do so.

I'm surprised at the number of positive reviews so maybe I missed something. But I found it to be an easy reading primer for someone who hasn't done much work in measurement, but little more.

- Jeremy

Horrible book, unless you have an advanced understanding of math and statistics, you'll be lost most of the time after the second chapter. The author is self referencing quite often and is superfluous throughout the whole book. I could sum up what the book says in one line: If you think about something long enough, you can guesstimate it's value.