A good predictive model requires a stable set of inputs with a predictable range of values that won’t drift away from the training set. And the response variable needs to remain of organizational interest.
If you want to move at the speed of “now, light, big data, thought, stuff,” pick your big data analytics battles. If your business is currently too chaotic to support a complex model, don’t build one. Focus on providing solid, simple analysis until an opportunity arises that is revenue-important enough and stable enough to merit the type of investment a full-fledged data science modeling effort requires.