Decisions are the core of every business. From market research to operations planning, from manufacturing schedules to inventory strategy, from pricing decisions to distribution strategy; our businesses are basically “decision machines”.
But today’s “decision machines” are struggling. Our rapidly-changing business world requires better, faster decisions; but many of our IT systems don’t produce the data we need and we’re not organized to fully leverage the data we do have. Our gut tells us (along with a host of vendors and consultants) that advances in AI and Machine Learning will be critical to compete, but we don’t know where to even begin.
Are you struggling with the question of how to organize and build a team that supports next-generation decision-making? Do you have questions about architecture, structure, staff (roles and responsibilities) and how to plan for and manage skillsets to support data science? Is this even IT? …if not IT, who?
In this session, we will see the approach taken by Eastman Chemical Company. We will see how Eastman built a Data Science organization, how this organization continues to grow/mature, and learn how several early successes are beginning to shape the way the “decision machine” operates at Eastman.