>In a sense, you are programming your team, in all the things you emphasize and spend time talking about at meetings.

I'm saying that the analogy is just an analogy, and doesn't apply strongly enough. What you're doing has strong components of feeding an ML algorithm training data. Yes, people have intentions and can understand processes, but that's as far as it does. We're certainly not writing neuroassembly.

I don't mean to imply that there are no predictors for better performance, but I bet there are fewer than one might think. A lot of the factors interact in discontinuous or nonlinear fashion, making it very hard to just draw correlations and call it a day.