The two big assumptions behind 'best practices'

[Homonym alert -- another smart phone composition]

There is no notion better loved by scientific management types than 'best practices.' It has become one of the truly obligatory PowerPoint phrases and it is rare to hear a high-level executive lay out plans for fixing a large organization without promising to promote them. These days those executives often have titles like 'superintendent.' Scientific management is now extraordinarily popular in education circles, particularly in the education reform movement. This confluence of two of the major interests of this blog means there are some major threads starting that will allude to this topic quite a bit.

'Best practices' are often treated as a self-evidently good thing  – Who wouldn't want to be best? – – but the idea of finding optimal methods and strategies and applying them across an organization is based on two very big and difficult-to-justify assumptions.

The first is that you have or even can identify these behaviors. Determining "best" status usually requires a high degree of faith in your metrics and metrics almost never perfectly align with the properties they are supposed to measure. Even when handled by the most competent of people, things can go badly wrong.

And, as anyone who has worked for large corporations can tell you, the executives overseeing these programs often are not up to the job. Between various biases, office politics, and a widespread misunderstanding of how statistics works, the results are often far from "best."

Most corporate cultures strongly discourage employees from questioning whether or not a "best practice" is actually best, but at least the question does sometimes come up. The very idea of the next assumption often escapes people entirely.

In order for a best practices approach to make any sense whatsoever, the optimal level of the factors in question must remain basically the same from person to person, location to location, and sometimes even job to job. Those are extremely strong and in some cases wildly counterintuitive assumptions and yet they go unquestioned all the time.

Later in the week, we'll discuss how violating these assumptions can lead to trouble (and connect this topic with an earlier post).