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# How to Measure Anything: Finding the Value of Intangibles in Business

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,

...moreKindle Edition, 288 pages

Published
(first published July 30th 2007)

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## Community Reviews

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3,000)

Feb 05, 2014
Jurgen Appelo
rated it
liked it
·
review of another edition

Shelves:
performance-management

297 references to risk, and only 29 references to opportunity. No mention of unknown unknowns (or black swans), and no mention of the observer effect (goodhart's law). A great book, teaching you all about metrics, as long as you ignore complexity.

As the title suggests, throughout the whole book the author strongly defends the case that everything can be measured, even though the method may not be obvious at first glance. The book structure basically consists of the explanations of why this is so and various examples and methods that should help the reader to deal with many types of such problems.

Alon ...more

Hubbard's taxonomy and mine don't fully jive, but that's a minor point; I found much more to like than not. I like to highlight and make notes in good books...this book is full of both. I especially like one of his "useful measurement assumpti ...more

Ah, that is where this book was insightful an helpful. Hubbard aserts that there isn't anything ...more

The first half is very recommended as it goes into what it means to “measure” something and suggest some very fundamental questions regarding measuring. E.g.:

What is it you want to have measured? E.g. what does ...more

The first is the "moneyball" type: a phenomenon where we know intuitively that there are important differences in measurable outcomes but we lack statistically significant explanations. The challenge here is to find things to measure that are consistently revealing of the phenomenon you are ultimately interested in measuring (say team wins). Maki ...more

Sep 17, 2012
Jeff Yoak
rated it
it was amazing
·
review of another edition

Shelves:
audio-collection,
read-in-2012

This was a fantastic read. It helps with general numeracy as well as providing an overview on how to think about measurement and statistics practically. This is an area where I have some experience and I still learned a lot. This book, especially the first half, should be accessible to everyone.

The second half is a bit more technical and I wished I had been reading in paper instead of in audio. I may do that eventually. The pacing is a little hard in audio and I could have benefited from notes, ...more

The second half is a bit more technical and I wished I had been reading in paper instead of in audio. I may do that eventually. The pacing is a little hard in audio and I could have benefited from notes, ...more

1-If it's really that important, it's something you can define. If it's something you think exists at all, it's something you've already observed somehow.

2-If it's so ...more

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 understand ...more

I chose to read this book because it seems to be focused around analytics and measurements and this is a field that I would like to get back into at work.

I found after I started listening that this book is heavy on statistics and some of the parts were well beyond my curve for this topic. I did find that having taken the Grainger/CLC Intro to Statistics course, most of the terminology and references were ...more

The approach challenges decision makers to figure out what tangible outcome they actually care about, and think creatively to come up with low cost observations that can be measured. It goes on to give readers tools to determine how much they don't know an ...more

Measurement is about reducing uncertainty, reducing risk. There are many simple ways to measure anything, especially the so called intangibles.

The point is a good one. Measurements don't need to be precise (exactly how many?) if you have a lot of uncertainty.

The book is a bit slow and dry. Feels more like a text book than a good teacher. Accept the premise (you can measure it and reduce uncertainty!) and your most of the way there.

I enjoyed this book, even though it has much jargon about statistics and formulas, mainly because it helped change my presuppositions about measurements.

This book has some good concepts about measuring that anyone can benefit from; it also has more in depth explanations for those who want to really dig deep.

If you listen to this book don't forget to download the charts and graphs to look at.

May 03, 2015
Nathanael (Boehm) Coyne
rated it
it was amazing
·
review of another edition

Shelves:
work-related,
favourite

This book made me realise how ignorant I was about the fundamentals of statistics and scientific observation. I no longer fear quantitative information now that I understand that pursuing exact values is often futile and that educated estimates wrapped in a confidence interval can be more useful and more readily obtained. It has really changed the way I look at analysing information and drawing conclusions from both quantitative and qualitative information to input into my design and evaluation
...more

*Measurement: A quantitatively expressed reduction of uncertainty based on one or more observations.*;

*Uncertainty: The lack of complete certainty, that is, the existence of more than one possibility.*

*Risk: A state*...more

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“If a measurement matters at all, it is because it must have some conceivable effect on decisions and behaviour. If we can't identify a decision that could be affected by a proposed measurement and how it could change those decisions, then the measurement simply has no value”
—
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“A common simplifying approach to quantifying a risk is simply to multiply the likelihood of some loss by the amount of the loss. This is simple but can be misleading. This assumes the decision maker is “risk neutral.” That is, if I offered you a 10% chance to win $100,000, you would actually be willing to pay as much as $10,000 for it. And you would consider it equivalent to a 50% chance of winning $20,000 or an 80% chance of winning $12,500. But the fact is that most people are not really risk neutral.”
—
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