ArticleOpen Access http://dx.doi.org/10.26855/acc.2026.06.009
Data-driven Pathways for Optimizing Supply Chain Operational Efficiency in Physical Industries
Zelin Wang
Hangzhou Shennong Jinjian Agricultural Technology Co., Ltd., Hangzhou 310000, Zhejiang, China.
*Corresponding author: Zelin Wang
Published: June 30, 2026
Abstract
Physical-industry supply chains connect procurement, production, warehousing, transportation and delivery, where demand fluctuations, inventory stagnation, equipment waiting and route delays can spread across operating nodes and weaken efficiency, cost control and response stability. A data-driven optimization framework is developed around material flow, order flow, equipment flow, inventory flow and delivery flow, integrating multi-source data capture, field-level validation, predictive modelling, inventory segmentation and digital twin scheduling into a closed-loop logic of data access, model judgement, field execution and metric feedback. Scenario-based comparison indicates that data-driven solutions can improve demand forecast accuracy, inventory turnover, order cycle time, on-time delivery and unit delivery cost by converting fragmented operational records into executable decisions. Reliable implementation depends on embedding algorithmic outputs into procurement planning, production scheduling, warehouse allocation, transportation routing and exception handling, rather than treating analytics as an isolated reporting tool. The findings suggest that supply chain efficiency gains in physical industries rely on data quality, system interoperability, model interpretability and role-based execution across operational nodes.
Keyword
Data-driven supply chain; physical industries; operational efficiency; predictive analytics
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Copyright
© 2026 by the author(s).
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) license, which permits non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited and is not modified or adapted.
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How to cite this paper
Data-driven Pathways for Optimizing Supply Chain Operational Efficiency in Physical Industries
How to cite this paper: Zelin Wang. (2026) Data-driven Pathways for Optimizing Supply Chain Operational Efficiency in Physical Industries. Advances in Computer and Communication, 7(2), 106-110.
DOI: http://dx.doi.org/10.26855/acc.2026.06.009