Engineers and others attracted to comprehensive systems views often fail in a predictable way: they translate all their objectives into multi-factor optimization models and trade-off curves which then yield spectacularly mediocre results. I commented on this pathology as part of a recent answer to a question about choosing among multiple job offers on Quora and I figured I should generalize that answer.
Why is this a failure mode? Optimization is based on models, and this failure mode has to do with what you have left out of your model (either consciously or due to ignorance or a priori unknowability). If there are a couple of dozen relevant variables and you build a model that uses a half-dozen, then among those chosen variables, some will have more coupling to variables you’ve left out than others. Such variables serve as proxies for variables that aren’t represented in your model. I’ll overload a term used by statisticians in a somewhat related sense and call these variables fertile variables. Time is a typical example. Space is another. Money is a third, and particularly important because ideological opinions about it often blind people to its fertile nature. Physical fitness is a fourth.
Fertile variables feed powerful patterns of action based on what I will call rich moves.
