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.


Manufacturing and Distribution


Craig Kelly
VP Business Intelligence

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

Mahesh Sathenjeri
Senior ERP Specialist

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