It's hard because you have to constantly make "sub-optimal" decisions. If you optimise for things you can measure, or at least see right now, you get a low performing team of high performers, or you get a collection of local maxima. Optimising for a global maximum requires making decisions that have unclear pay-off, that are harder to justify. Another problem is that one of these decisions that was actually wrong, vs one that hasn't paid off yet, look the same.

I suspect executives very much get it, but realise that there's no obviously good answer here.