Optimizing procurement efficiency: Frameworks for data-driven cost reduction and strategic vendor management
1 Bowling Green State University, Ohio USA.
2 Independent Researcher, USA.
3 Independent Researcher, UK.
4 Labatt Breweries of Canada.
Review Article
Magna Scientia Advanced Research and Reviews, 2024, 12(02), 164–171
Article DOI: 10.30574/msarr.2024.12.2.0192
Publication history:
Received on 14 October 2024; revised on 20 November 2024; accepted on 23 November 2024
Abstract:
This paper explores data-driven frameworks for optimizing procurement efficiency, focusing on cost reduction strategies and strategic vendor management. Procurement is critical in enhancing operational resilience and supporting organizational objectives in an era of increasing financial pressures and complex supply chains. The study examines data analytics approaches, such as spend analysis, predictive cost modeling, and demand forecasting, which enable organizations to uncover cost-saving opportunities and streamline procurement processes. Additionally, it highlights how data-driven vendor management, through continuous evaluation, risk assessment, and performance tracking, contributes to sustainable supply chain efficiency. Key recommendations include establishing data governance frameworks, investing in advanced analytics tools, enhancing data literacy among procurement teams, and fostering transparent supplier relationships. By integrating analytics into procurement strategies, organizations can achieve long-term cost efficiency, build stronger supplier partnerships, and support sustainable growth.
Keywords:
Procurement efficiency; Data analytics; Cost reduction; Strategic vendor management; Spend analysis
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0