Evaluation and Improvement of Procurement Process with Data Analytics

• Main Authors: TAN, Melvin H. C., LEE, Wee Leong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: procurement; text mining; clustering; data analytics; fraud detection.; Management Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/2913; https://ink.library.smu.edu.sg/context/sis_research/article/3913/viewcontent/Paper_9_Evaluation_and_Improvement_of_Procurement_Process_with_Data_Analytics.pdf
• Institution: Singapore Management University

Analytics can be applied in procurement to benefit organizations beyond just prevention and detection of fraud. This study aims to demonstrate how advanced data mining techniques such as text mining and cluster analysis can be used to improve visibility of procurement patterns and provide decision-makers with insight to develop more efficient sourcing strategies, in terms of cost and effort. A case study of an organization’s effort to improve its procurement process is presented in this paper. The findings from this study suggest that opportunities exist for organizations to aggregate common goods and services among the purchases made under and across different prescribed procurement approaches. It also suggests that these opportunities are more prevalent in purchases made by individual project teams rather than across multiple project teams.