Predicting Inventory Shipments of Oracle EBS Systems

Predicting inventory shipments can be useful for lean inventory management such as inventory planning. In this paper, we propose approaches to predict inventory shipments based on the data extracted from the inventory management module of Oracle EBS systems of a GPS-manufacturing company. First, we introduce the process to extract the inventory shipment data from the Oracle EBS system. Then, we adopt time series forecasting algorithms (i.e., ARMA) and Primitive KNN algorithms to predict the future shipments for a group of inventory items. At last, by discovering the patterns of parameter settings when optimal prediction accuracy is achieved, we develop new algorithms to reduce runtime at different levels with trade-offs in prediction accuracy.

I. Introduction

In enterprise-level business process managements, inventory management is an important area and has been a long-lasting research topic. Nowadays, it has become more challenging since business operation patterns are more intricate. To handle these challenges, the concept of lean inventory management [1], is introduced such that the performance of inventory management can be improved.