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measuring your business

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.

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