JDE Meets ML: Unlocking Lower Inventory Levels and Higher Customer Satisfaction with ML Generated Demand Forecasts

Summary

More accurate demand forecasts allow companies to optimize their inventory levels while maximizing customer satisfaction. Legacy JD Edwards demand forecasting is limited to data that resides within the customer's instance of JDE while relying on dated algorithms, resulting in suboptimal forecast accuracy. But now some options exist where JD Edwards' data can be combined with other sources (both internal and external to the business) and leveraged to train ML-based models to generate accurate forecasts which can then be orchestrated back into JDE. The resulting effect allows JDE to run a more efficient MRP process, ultimately increasing margins for the company.

Tracks

Manufacturing and Distribution

Presenters

Craig Kelly
VP Business Intelligence
Syntax

Craig is VP of Analytics at Syntax with over 22 years JDE Analytics experience.

Mahesh Sathenjeri
Senior ERP Specialist
Syntax

Mahesh is a Senior ERP Specialist at Syntax with extensive experience in process improvement on initiatives like cost savings and performance improvement.