Its common to see predictive analytics as a sort of “crystal ball” for your business. This crystal ball image makes for great marketing. Unfortunately, predictive analytics is not a crystal ball.
It will not provide the correct prediction every time. Its primary purpose is to help you make better decisions by giving you the power to unlock the patterns inside your data. When performed correctly this gives you the ability to simplify decisions. When performed incorrectly it can spell disaster for your company.
Predictive analytics is both an art and science. It requires a combination of both empirical and subjective experience to verify that models reflect reality. This is why CAN takes into consideration three main aspects when building predictive models: Data, Theory, and Math. In our experience your predictive models will not reflect reality if all of three of these aspects are not held up.