Systematic Review of Category Management and Spend Analytics in Engineering Supply Chains

This systematic review examines the role of category management and spend analytics in enhancing the performance of engineering supply chains. As supply chain complexity increases, engineering firms are under pressure to improve procurement efficiency, reduce costs, and ensure continuity of supply. Category management, a strategic approach to procurement, groups similar products or services to manage them more effectively. Spend analytics, on the other hand, provides critical insights into procurement data, enabling informed decision-making. Together, these methodologies have the potential to transform engineering supply chains by fostering supplier collaboration, improving sourcing strategies, and aligning procurement with organizational goals. The review adopts the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to identify, screen, and analyze relevant peer-reviewed literature from major academic databases including Scopus, Web of Science, and IEEE Xplore. A total of 78 articles published between 2010 and 2024 were included based on predefined inclusion criteria. The findings reveal that category management enhances standardization and supplier rationalization, leading to cost reductions and improved service levels. Spend analytics supports these initiatives by uncovering hidden savings opportunities, monitoring compliance, and facilitating performance tracking through data visualization and predictive analytics. Key challenges identified include data fragmentation, lack of integration across procurement functions, and limited skills in data analytics within engineering procurement teams. Furthermore, there is a significant gap in empirical studies specifically tailored to engineering-focused supply chains, despite the sector’s critical reliance on high-value and technically complex components. The review recommends increased investment in digital procurement tools, training in data literacy, and cross-functional collaboration to fully realize the benefits of category management and spend analytics. This study contributes to the growing body of knowledge on strategic procurement and digital transformation in engineering supply chains. It provides actionable insights for practitioners and researchers aiming to optimize procurement practices through integrated analytical and strategic sourcing approaches.

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Publication Details

Journal
International Journal of Scientific Research in Science Engineering and Technology
Published
2024-08-20
DOI
https://doi.org/10.32628/ijsrset25121176
Citations
3
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
1.59
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article

Systematic Review of Category Management and Spend Analytics in Engineering Supply Chains

Joyce Efekpogua Fiemotongha, Osazee Onaghinor, Julius Olatunde Omisola, Odira Kingsley Okenwa et al.
3 citations
International Journal of Scientific Research in Science Engineering and Technology
Big Data and Business Intelligence
1.59
article

Systematic Review of Category Management and Spend Analytics in Engineering Supply Chains

Joyce Efekpogua Fiemotongha, Osazee Onaghinor, Julius Olatunde Omisola, Odira Kingsley Okenwa, Gbenga Omoegun
article en
3 citations

Abstract

This systematic review examines the role of category management and spend analytics in enhancing the performance of engineering supply chains. As supply chain complexity increases, engineering firms are under pressure to improve procurement efficiency, reduce costs, and ensure continuity of supply. Category management, a strategic approach to procurement, groups similar products or services to manage them more effectively. Spend analytics, on the other hand, provides critical insights into procurement data, enabling informed decision-making. Together, these methodologies have the potential to transform engineering supply chains by fostering supplier collaboration, improving sourcing strategies, and aligning procurement with organizational goals. The review adopts the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to identify, screen, and analyze relevant peer-reviewed literature from major academic databases including Scopus, Web of Science, and IEEE Xplore. A total of 78 articles published between 2010 and 2024 were included based on predefined inclusion criteria. The findings reveal that category management enhances standardization and supplier rationalization, leading to cost reductions and improved service levels. Spend analytics supports these initiatives by uncovering hidden savings opportunities, monitoring compliance, and facilitating performance tracking through data visualization and predictive analytics. Key challenges identified include data fragmentation, lack of integration across procurement functions, and limited skills in data analytics within engineering procurement teams. Furthermore, there is a significant gap in empirical studies specifically tailored to engineering-focused supply chains, despite the sector’s critical reliance on high-value and technically complex components. The review recommends increased investment in digital procurement tools, training in data literacy, and cross-functional collaboration to fully realize the benefits of category management and spend analytics. This study contributes to the growing body of knowledge on strategic procurement and digital transformation in engineering supply chains. It provides actionable insights for practitioners and researchers aiming to optimize procurement practices through integrated analytical and strategic sourcing approaches.

International Journal of Scientific Research in Science Engineering and TechnologyVol. 11(4)
University of Benin (NG), Federal University of Petroleum Resource Effurun (NG)
Openalex Percentile: Top 12%
Big Data and Business Intelligence
1.59
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