Engineering Change from the Perspective of Big Data - Cost Risk Control Analysis of Supply Chain Collaboration

Abstract

In response to the frequent supply chain disruptions and the cost control issues caused by construction project changes, this article uses big data technology as a support to construct a collaborative control framework for engineering changes and supply chains. The study systematically investigates the transmission mechanism of cost risks in material supply, logistics distribution, supplier performance, inventory management, and other links under the change scenarios. Through multi-source data fusion, machine learning risk identification, dynamic evaluation models, and real-time warning systems, achieve collaborative control of the entire change supply chain cost chain. Research has shown that big data-driven collaborative models can significantly reduce additional costs caused by material shortages, expedited logistics, inventory waste, and price fluctuations, and improve change response efficiency and cost control accuracy. The control system proposed in this article can provide theoretical and practical references for achieving cost reduction, efficiency improvement, and risk control in large-scale construction projects.