Title

Evaluation and Improvement of Procurement Process with Data Analytics

Publication Type

Journal Article

Publication Date

9-2015

Abstract

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.

Keywords

procurement, text mining, clustering, data analytics, fraud detection.

Discipline

Management Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Intelligent Systems and Decision Analytics

Publication

International Journal of Advanced Computer Science and Applications

Volume

6

Issue

8

First Page

70

Last Page

80

ISSN

2158-107X

Identifier

10.14569/IJACSA.2015.060809

Publisher

SAI Organization / Science and Information (SAI) Organization

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.14569/IJACSA.2015.060809

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