Read this article, which documents how data-driven policing has caused police to report statistics wrongly, classify crimes as more or less serious depending on the quota needed to fill, and has created constructs of “productivity” that warp the goals of policing.

What is the primary goal of policing? To keep our communities safe and crime-free. What is the primary goal of education? To assure that the younger generation is prepared in mind, character and body to assume the responsibilities of citizenship in our society. But what are the goals of education in a data-driven environment? To raise test scores, by whatever means necessary. This is akin to setting a quota for felony arrests for police or directing them that the crime statistics must go down.

Here we see a restatement of Campbell’s Law. When the stakes are high, people will not only forget the goals of their activity but the measure itself becomes corrupted. Thus, the data that are generated–whether by police or teachers–become meaningless because of the pressure applied to get them. In effect, we are paying people bonuses to generate good news that is not true. The good news is not true, the data are not trustworthy, the measures are no longer useful, and we are not achieving the purposes of policing or teaching. It’s what you might call a lose-lose.

But it does have certain benefits. It creates new industries for those who love counting and measuring and reporting. It creates new work for the consultants who will tell you how to reach your targets. It provides a rationale for endless workshops and professional development and study groups, all of which divert even more time from the original goals. It creates new work for the experts who will opine about better ways to reach the targets. And it gives bragging rights to the politicians who think they accomplished something.