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Predictive Analytics Functionalities in Supply Chain Management

Author

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  • Puica Elena

    (Bucharest University of Economic Studies, Bucharest, Romania Economic Informatics Doctoral School)

Abstract

This scientific paper presents a comprehensive analysis of the capabilities of IT solutions for predictive analytics in supply chain management. The study uses a multi-method approach, including a literature review, case studies by applying a machine learning model to technology solutions currently available on the market. The study examines the various software and technology platforms available today and their key features and functionalities, focusing in particular on Scripting, Data Mining, Algorithms, Data Analysis, Modeling, Data Interaction, Data Visualization, Reporting and Data Unification. The study also assesses the potential benefits and challenges associated with implementing these solutions in supply chain management. The results of the study provide valuable information for supply chain professionals, IT managers and researchers interested in the application of predictive analytics in this field. In addition, the paper also discusses the current trend and future direction in this field.

Suggested Citation

  • Puica Elena, 2023. "Predictive Analytics Functionalities in Supply Chain Management," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 17(1), pages 986-996, July.
    • Handle: RePEc:vrs:poicbe:v:17:y:2023:i:1:p:986-996:n:36
    DOI: 10.2478/picbe-2023-0090
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