The first theme is a company’s 5 levels of analytical maturity and its application to several companies.
Level 1: reporting data Level 2: building predictive models Level 3: streamline predictive process and make it repeatable Level 4: repeat the process at large to have whole organization catch on Level 5: define strategies that allow sustainability
Many companies get stuck from level 2 to 3 that they cannot turn the predictive models into a repeatable process for analytics. The difficulty lies within communication and collaboration between data scientist building models and data engineers deploy models. There’s a general chasm between modeling environment and deployment environment. It can be filled with the right people, right senior buy in and a LOT of meetings.