Predicting the future is an impossible task. Even a 10-day weather forecast is only right about half the time. Then how can you plan for next month, next quarter or next year?

Traditional supply chain forecasting largely predicts the future based on patterns in historical data. While this can work with cyclical products or operations, in most cases it’s often only part of the data. There’s still a chance the forecast will be close to accurate, but there’s room for improvement.

Artificial intelligence (AI) is improving forecast accuracy by identifying more complex relationships in historical data, incorporating more data sources and continuously learning from new information.

Join this microlearning to explore how AI is being used to enhance forecasting processes across supply chains. You’ll compare traditional and AI-driven forecasting approaches, examine the steps involved in developing and using AI forecasts, and discover how planners work alongside AI to improve decision-making.

Developed in collaboration with ASCM member Janetta Barker, CSCP, CPIM.