Solving practical business decision-making problems using predictive analytics involves much more than just data visualization or applying traditional forecasting techniques. Inclusion of domain knowledge, advanced forecasting techniques and intuition can create a successful model that avoids catastrophic failure. I’ll dive into one best practice learned from solving real world problems in the area of supply chain management.

Most supply chain management companies are frustrated with inaccurate forecasts from customers and ERP systems. They are constantly searching for more reliable forecasts so that they can dramatically slash inventory costs while providing better, more efficient service to customers.

Drawing inspiration from the applications of artificial intelligence and from mathematical problem solving skills, I will walk through some examples that illustrate how creative and innovative the solutions are, when problems are solved with AI and big data.