Automating procurement practices using artificial intelligence
Publication Type
Journal Article
Publication Date
1-2025
Abstract
Conducting a spend analysis of procurement practices is a challenging task for manufacturers. It requires deciphering large-scale spend data in the form of unstructured texts and identifying opportunities for savings. This process relies on procurement experts’ know-how and is often performed manually, a laborious task often leading to missed savings opportunities. Automating spend analysis through natural language processing and machine learning presents several challenges, such as (i) a lack of true detailed category labels for suppliers, (ii) a lack of sufficiently large sets of training data, (iii) hierarchical taxonomies that vary across manufacturers, and (iv) the reduced accuracy of hierarchical categorization algorithms beyond two levels. Our novel three-component classification model tackles these issues, facilitating the automation of spend analysis and the replication of procurement experts’ decision-making processes. By processing input data composed of unstructured spend texts from Cranswick PLC, a leading UK food producer, our model delivers accurate supplier categorizations that pinpoint areas ripe for substantial savings. This approach not only shows greater accuracy compared with existing benchmark models but also aids in identifying key product categories and suppliers for cost-saving initiatives. By simulating the application, we project that our method could bring annual savings of £16 million to £22 million ($20 million to $28 million) for Cranswick PLC, illustrating the significant advantages of automating spend analysis.
Keywords
Spend analysis, data-driven procurement, natural language processing, machine learning
Discipline
Artificial Intelligence and Robotics | Operations and Supply Chain Management
Research Areas
Operations Management
Publication
INFORMS Journal on Applied Analytics
First Page
1
Last Page
29
ISSN
2644-0865
Identifier
10.1287/inte.2023.0099
Publisher
Institute for Operations Research and Management Sciences
Citation
LI, Xingyi; REYCK, Bert De; and YOO, Onesun Steve.
Automating procurement practices using artificial intelligence. (2025). INFORMS Journal on Applied Analytics. 1-29.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/7660
Additional URL
https://doi.org/10.1287/inte.2023.0099
