Supply Chain
How is AI used in the fashion supply chain?
From demand planning to warehouse robots and supplier monitoring: where AI already works in fashion supply chains, what data it needs and where its limits are.
How does AI detect defects in fabrics and garments?
Computer vision is moving textile inspection from the human eye to cameras and models. How it works, where it is used, and why data and defect definitions matter most.
How Inditex uses AI and data: RFID and a demand-driven supply chain
Inditex's edge rests on item-level RFID data, integrated stock and production close to home. Where AI now enters, what results are public and what remains undisclosed.
How Uniqlo and Fast Retailing use AI and data in the Ariake Project
Fast Retailing's Ariake Project aims to make and sell exactly what customers want, when they want it. How AI, shared data and automated warehouses fit in, and what the group has disclosed.
AI for sourcing and supply chain managers in fashion
How fashion sourcing and supply chain managers use AI for demand and production planning, cost and tariff scenarios, supplier risk, compliance and quality, with data needs, limits and a 30-day plan.
Lead times in fashion: why a season starts a year early
From trend research to delivery in store, a traditional fashion season takes many months to build. Where the time goes, what drives it and how brands compress it.
Nearshoring in fashion: the trade-offs
Moving production closer to end markets promises speed, flexibility and resilience. It also raises unit costs and narrows capability. How to decide what to bring closer and what to leave.
Supply chain traceability in fashion: where to start
Regulators, retailers and consumers increasingly ask where clothes come from. A practical guide to mapping suppliers, collecting data and building traceability step by step.