Data Harmonization and Reconciliation for Transparent Digital Supply Chain Platforms

Abstract

Digital platforms for supply chain monitoring aim to provide real-time visibility across procurement, transportation, and warehousing operations. In practice, fragmented data sources limit situational awareness. This study analyzes shipment, inventory, and customs records from a multinational logistics platform processing over 240 million events annually. Discrepancies in timestamp standards, identifier formats, and update frequency were found in nearly 22% of integrated records. A normalization and reconciliation layer based on probabilistic matching was implemented. Integration accuracy improved, but exception handling remained labor-intensive. Supply chain transparency depends as much on data harmonization as on sensor deployment.