Data-Driven Approaches to Manage Fashion Supply Chains: A Review

The fashion supply chain is complex and dynamic, driven by short product life cycles, high demand volatility, and the need for fast response to market trends. In this context, the supply chain management requires robust data-driven solutions. This study presents a Systematic Literature Review, following the PRISMA protocol, based on data from Scopus and Web of Science. The review focuses on the application of data-driven approaches in fast fashion supply chains. The findings identify the most common methods (linear programming, fuzzy logic and simulations) and the types of data used (sales history, customer behavior, and environmental and social KPIs). Results show a clear trend toward the integration of AI tools across all supply chain stages, the growing use of external and unstructured data sources, and a recent emphasis on circular economy and supply chain resilience. These findings provide a comprehensive overview of how data-driven approaches are shaping the future of fashion supply chain management.