Implementing an Enhanced Procurement Management System Using Decision Support Techniques

Abstract

Modeling procurement management system is important for quality decision making regarding business capacity planning, supply and scheduling. In the Procurement Services Department (PSD), most commonly used indicators to measuring performance include supply period, products rating, ranking recommendations, resource scheduling and number of goods supplied and delivered. In this paper, a Decision Support Service (DSS) technique was proposed to optimize procurement services in business and public organization. First, a study of a typical public and private organization was conducted to gain insights into the operations of the procurement department and the contributions of important system parameters to procurement management. Second, a product and supplier collaborative filtering technique were investigated to obtain transformed data for model training and testing for implementation using Partial Correlation Coefficient (PCC). The Partial Correlation Coefficient (PCC) for a particular product or supplier was utilized for generating the outcomes with tuned values which were compared with actual observed outcomes. The residuals were evaluated in terms of linearity, normality, independence and constant variance. The visualized system plots indicate a good performance as the quality and accuracy of the decision support model was evaluated using some basic metrics. The overall system implementation and performance results demonstrated the importance of Decision Support Services in assessing the performance of procurement management systems. A robust tool for this assessment and a model for procurement and supply planning indicates that the system framework offered Quality of Service (QoS) provisioning.