Dubey and Rajaram at Information Management:

In this approach, business understanding is used to validate the outcome of analytics — not necessarily the analytics process. A common symptom of this problem is the prevalence of esoteric modeling and data mining techniques without enough inquiry in to their appropriateness and applicability for the problem at hand. Unfortunately, it is model accuracy that often becomes the final arbiter. This results in a classic trap of choosing the technique that gives maximum accuracy over the one that makes most business sense. This can be best avoided by striking a balance between algorithmic and heuristic approaches, which is essentially a balance between a highly accurate model and a model that makes business sense. Tilting to either extreme is dangerous.

This understanding extends to all things, especially ed. stats and models. Whole article is good.