Data-Driven Localization for Supply Chain Resilience: A Case Study on Up to 90% Effective Import Substitution in U.S. Critical Sectors

This study presents an innovative data-driven approach to localizing supply chains, achieving up to 90% effectiveness in import substitution within critical U.S. sectors, including semiconductors, pharmaceuticals, and rare earth minerals. Developed to address strategic vulnerabilities exposed by global disruptions, the framework reduces import dependencies while delivering 40–60% cost savings and 50% faster supplier identification. Case studies highlight its impact on reshoring initiatives, with potential annual import reductions of $45–60 billion and the creation of over 150,000 jobs. The research leverages U.S.-specific data from sources such as the Bureau of Economic Analysis, SEMI, and PhRMA, offering insights into policy implications and international comparisons. Published on October 14, 2025, this work aims to support national supply chain resilience and inform future strategies.