I'm curious about the real world implementation risk and if anyone has a methodology to proactively deal with external factors affecting the model performance. Such as if a feature is highly predictive of a certain outcome is there a framework to measure the volatility based on information outside of the dataset ie. product changes, marketing campaigns etc.