Decisions in Noisy Contexts

Good piece in Dan Ariely's always interesting blog: Good Decisions, Bad Outcomes.  About attempting to make predictions in difficult environments, this can often come up in forecasting situations in the enterprise:

" ...  In the real world, the random noise is often more subtle and various—a hundred little things rather than one big thing. But the effect is the same. Rewarding and penalizing leaders based on outcomes overestimates how much variance people actually control. (This works both ways: Just as good managers can suffer from bad outcomes not of their own making, bad managers can be rewarded for good outcomes that occur in spite of their ineptitude.) In fact, the more unpredictable an environment becomes, the more an outcomes-based approach ends up rewarding or penalizing noise ... "