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113 of 116 people found the following review helpful:
5.0 out of 5 stars
Reducing the Uncertainty in Intangible Business Value . . ., October 31, 2007
This review is from: How to Measure Anything: Finding the Value of "Intangibles" in Business (Hardcover)
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.
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53 of 54 people found the following review helpful:
5.0 out of 5 stars
Clear explanation making the complex simple., September 10, 2007
This review is from: How to Measure Anything: Finding the Value of "Intangibles" in Business (Hardcover)
Douglas Hubbard covers a broad landscape but does exactly what the title claims; it provides a guide to measuring anything. Hubbard builds from simple concepts to show the practical yet intuitively simple application of some rather advanced statistical techniques. The author's skill is in communicating complex ideas in an easy to follow and motivational flow that builds in a series of seemingly obvious steps.
The book is both philosophical and practical. If one read no more than the first three chapters one's view of the world would be changed forever. Yet the later chapters cover many extremely simple illustrations of some complex statistical concepts. I particularly enjoyed his discussion of the value of information (chapter 7), Bayesian Statistics (chapter 10), and some advanced concepts such as measuring value via observable trade-offs and using prediction markets. No one reading just a portion of this book would walk away without a new insight.
This book would be extremely useful to students in an MBA program or to those pursuing an advanced degree in one of the social sciences. It would provide a valued motivational reference to anyone studying Computer Science, Economics, or Applied Statistics. Anyone teaching or mentoring students in these disciplines might want to review this book for inclusion in their curriculum.
The book also has considerable potential at helping someone working the area of Data Warehousing and Business Intelligence. For example, Steve and Nancy Williams have written a great book titled "The Profit Impact of Business Intelligence". In it they explain the case for managing BI projects as a portfolio of risky investments. They talk of the need to measure the business value of a BI project and to coordinate changes in information flow, workflow, and decision structure so as to maximize that value. Hubbard's book offers ways that business value, cultural change, and process impact can be measured, and therefore managed. The Williams' book talks of the need for Decision Engineering. Hubbard's book gives one the understanding of what a Decision Engineering group would do on a routine basis. The two books together would be of high benefit to any manager trying to develop a "value management" culture.
The Profit Impact of Business Intelligence
The field of Human Capital Management and Workforce Analytics is receiving a lot of attention today. Two books that are particularly helpful in understanding how analytics can help Human Resource managers better support (and in fact drive) organizational performance are "The HR Scorecard" (by Brian E. Becker, Mark A. Huselid, and Dave Ulrich) and "The Workforce Scorecard" (by Mark A. Huselid, Brian E. Becker, and Richard W. Beatty). These books provide a comprehensive list of elements that could be included in a workforce analytics program from recruiting and retention to compensation and talent development. Hubbard's book helps the HR executive identify the critical metrics, what metrics add value and what metrics do not in their environment, and how to prioritize one measurement need over another. Again, Hubbard's book in combination with others will be a great compliment for the leader interested in building a fact-based value oriented decision culture.
The Workforce Scorecard: Managing Human Capital To Execute Strategy
The HR Scorecard: Linking People, Strategy, and Performance
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42 of 42 people found the following review helpful:
5.0 out of 5 stars
Quantifying Soft Knowledge, June 20, 2008
This review is from: How to Measure Anything: Finding the Value of "Intangibles" in Business (Hardcover)
Perhaps the most frequent question from decision analysis team members is, "How do we get the inputs?" In most evaluations, there are several key variables about which we know little. Consider oil price, for example. We have abundant historical data, yet forecasting future prices is a daunting challenge.
Doug Hubbard has written an entire book about capturing quantitative judgments. His approach differs from the usual decision analysis process. In a conventional analysis, we assume that that a subject matter expert (SME) can be identified for each key variable. Then, a skilled interviewer carefully elicits the SME's judgment through an interview process.
Hubbard takes a different approach. People familiar with the type project are assembled and given calibration training. Becoming calibrated might take perhaps a half-day of practice exercises and feedback. Basically, being "calibrated" means that one can consistently provide judgments of 90% confidence intervals that avoid the "overconfidence" bias. The book provides several example quizzes for the reader to self-assess.
Even though I was well-aware of the overconfidence bias, I still performed poorly on the self-assessment tests (history was never my strong subject!). Of course, the questions for a technical group would be crafted from topics within the area of interest. Whether (a) expert in the quiz subject matter or not and (b) being told in advance that people tend to be overconfident about the quality of their knowledge doesn't seem to affect the overconfident bias. Practice and feedback are the antidotes.
Hubbard's training and consulting examples are engaging. It has been years since I've devoured a technical book so thoroughly. While the reader will pick-and-choose methods of most interest, the "measurement" topic is well-covered.
The book contains many shortcuts and heuristics for rapid problem-solving. Many people never attempt to quantify intangibles. Yet, most people with some modest training are able to provide credible judgments in quantitative form.
A sampling of topics includes:
* Modeling and Monte Carlo simulation
* Designing experiments for measurement
* Decomposition
* Heuristics for obtaining simple statistics
* Value of perfect information, for screening which variables are worthwhile measuring
* Bayes' rule (because we almost always have some prior information about the subject of the observation)
* Cognitive biases
How to Measure Anything is well-written and carefully edited. The companion Web site, [..], offers additional calibration questions, several calculation spreadsheets, and additional information.
Persons reading this book will be the better for it.
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