Predict and Control versus Inspect and Adapt

 I came across an interesting idea the other day in the context of data governance (or, rather, governance in general at a tech-heavy company). The argument is that traditional management tends to adopt a "predict and control" mindset, which will only work well in situations in which the leaders really do know best and the workers are not used to (or capable of) any kind of autonomy. Such an approach might be appropriate for people working on a construction site, where there is a clear plan that should result in success if followed, assuming it was created by competent engineers. (Even in this scenario, there may still be some amount of local "troubleshooting" that requires the ingenuity of those closest to the work to handle.)

 For knowledge work, the situation is different, especially in a quickly changing landscape. Although there is obviously repetition at some level, knowledge work tends to be much less predictable than e.g., building widgets from known materials using a well-tested methodology. For this reason, a better approach is "inspect and adapt" -- make whatever course corrections are warranted given what you observe in the current situation. It is rarely possible to mindlessly repeat what was done before and expect a positive result.

The problem arises when there is a push to impose a predict and control structure on a group of workers who are expecting more of an inspect and adapt approach. Workers want to solve the problem, but they know that they will not be able to give specific details about exactly how that will be accomplished. Managers, on the other hand, want "certainty" and create more and more cumbersome processes to ensure that everything is "on track." This leads to frustration on both sides.