Chapter 8. The Transition: From What to Measure to How to Measure

If you've applied the lessons of the previous sections to your measurement problem, you've defined the issue in terms of what decision it affects and how you observe it, you've quantified your uncertainty about it, and you've computed the value of additional information. All of that was really what you do before you begin measuring. Now we need to figure out how to reduce our uncertainty further—in other words, measure it.

It's time to introduce some concepts behind powerful and practical empirical methods. Given the way we have defined measurement, the oft-heard phrase "empirical measurement" is redundant. Empirical refers to the use of observation as evidence for a conclusion. (You might also hear the redundant phrase "empirical observation.") "Empirical methods" are formal, systematic approaches for making observations to avoid or at least reduce certain types of errors that observations (and observers) are like likely to have. And observation is not limited to sight, although this is a commonly assumed notion. Observation may not even be direct; it may be augmented by the use of measurement instruments. This is, in fact, almost always the case in the modern physical sciences.

But we are focusing on those things that are often considered to be immeasurable in business. Fortunately, the approach to addressing many of these issues does not involve the most sophisticated methods. It's worth restating that the objective ...

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