Predictive models are used to predict future outcomes on the basis of data collected from past. Many organizations take their crucial decisions based on the foundations laid by the predictive models. But what if the model goes wrong? "BOOM"- crash of a significant part of the strategy! Though each predictive model has some scope of error. There are chances that the input variables considered for the model were not appropriate. But we need to find out what kind of error and to what extent it is acceptable. There is a need to work on the foundation of the predictive models to prevent failures.  Read more about it in the article written by John Bates(Senior Product Manager for Data Science & Predictive Marketing Solutions) at: http://blogs.adobe.com/digitalmarketing/analytics/what-to-do-when-your-predictive-marketing-is-wrong/