Supplier Evaluation Model On SAP ERP Using Machine Learning Algorithms

Paper Title: Supplier Evaluation Model on SAP ERP Application using Machine Learning Algorithms

Authors: Manu Kohli

Summary: For business enterprises, evaluating a supplier is a mission critical process. On ERP (Enterprise Resource Planning) applications such as SAP, the supplier evaluation process is performed by configuring a linear score model, however this approach has a limited success. Therefore, author in this paper has proposed a two-stage supplier evaluation model by integrating data from SAP application and ML algorithms. In the first stage, author has applied data extraction algorithm on SAP application to build a data model comprising of relevant features. In the second stage, each instance in the data model is classified, on a rank of 1 to 6, based on the supplier performance measurements such as on-time, on quality and as promised quantity features. Thereafter, author has applied
various machine learning algorithms on training sample with multi-classification objective to allow algorithm to learn supplier ranking classification.

The application of supplier evaluation model proposed in the paper can be generalised to any other other information management system, not only limited to SAP, that manages Procure to Pay process.

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