Predictive Intelligence in Supply Network Dynamics: A Data-Driven Approach to Operational Analytics and Disruption Forecasting

Authors

  • Barbara Secchi Professor of Information Engineering, University of Pisa

Keywords:

predictive intelligence, supply network dynamics, data-driven approach to operational analytics, disruption forecasting, machine learning

Abstract

In an effort to streamline logistics and support functions, industries are leaning heavily towards supply chain analytics. The installation of sensor-based systems, RFID tagging, IoT, etc., augments the tracking of products and intensifies available historical data. In this connected era, the application of AI decouples the traditional methodology of managing the supply chain.

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Published

31-12-2025

How to Cite

[1]
“Predictive Intelligence in Supply Network Dynamics: A Data-Driven Approach to Operational Analytics and Disruption Forecasting”, Adv. in Deep Learning Techniques, vol. 5, no. 2, pp. 41–49, Dec. 2025, Accessed: Jun. 05, 2026. [Online]. Available: https://www.thesciencebrigade.com/adlt/article/view/775