Bayesian Investor Blog

Book review: How to Measure Anything, by Douglas Hubbard.

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

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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.