How to Measure Anything (edit title/settings)

Ridiculously Simplified Synopsis edit

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Characters/People edit see section history

• Emily: Add a description of this character.
• Dawes
• Enrico
• Tippett
• Dr. Ram
• Fermi
• Bayes
• Deming
• Randi

Quotes edit see section history

• “If a thing can be observed in any way at all, it lends itself to some type of measurement method”

• “The fact is that the preference for ignorance over even marginal reductions in ignorance is never the moral high ground”

• “Anything you need to quantify can be measured in some way that is superior to not measuring it at all”

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• Rule of Five There is a 93.75% chance that the median of a population is between the smallest and largest values in any random sample of five from that population.

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• Clarification Chain 1. If it matters at all, it is detectable/observable. 2. If it is detectable, it can be detected as an amount (or range of possible amounts). 3. If it can be detected as a range of possible amounts, it can be measured.

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• Four Useful Measurement Assumptions 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. An adequate amount of new data is more accessible than you think.

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• what really makes a measurement of high value is a lot of uncertainty combined with a high cost of being wrong.

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• The concept of measurement as “uncertainty reduction” and not necessarily the elimination of uncertainty is a central theme of this book.

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• If you can define the outcome you really want, give examples of it, and identify how those consequences are observable, then you can design measurements that will measure the outcomes that matter.

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• Once managers figure out what they mean and why it matters, the issue in question starts to look a lot more measurable. This is usually my first level of analysis when I conduct what I’ve called “clarification workshops.” It’s simply a matter of clients stating a particular, but initially ambiguous, item they want to measure. I then follow up by asking “What do you mean by <fill in the blank>?” and “Why do you care?”

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• 1. Define a decision problem and the relevant uncertainties.

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• 2. Determine what you know now.

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• Definition of Measurement Measurement: A quantitatively expressed reduction of uncertainty based on one or more observations.

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Setting & Locations edit see section history

• Chicago
• Monte Carlo
• New York

Series & Lists edit see section history

Authors & Contributors edit see section history

1. Douglas W. Hubbard (Author)

Classification edit see section history

• Library of Congress: Add the Library of Congress Classification.
• Dewey: 657.7

Subjects edit see section history

• Books › Business & Investing › Management & Leadership › Management
• Books › Business & Investing › Skills › Math for Business