METRO

METRO, a wholesale food distributor serving hotels, restaurants, caterers, and independent merchants across a multi-channel network of 540 stores and 70 distribution centres, faced a fragmented replenishment operation that lacked consistency across fresh categories and regions. Ultra-fresh categories — products with the tightest shelf lives and the least margin for error — demand both speed and accuracy that manual or legacy planning models cannot reliably deliver at scale. Without a unified, data-driven planning model, METRO could not systematically reduce waste, maintain consistent product availability, or respond efficiently to demand variability across its large network.

METRO launched its Ultra Fresh initiative, selecting RELEX Solutions to deliver AI-powered forecasting and replenishment across its entire network of 540 stores and 70 distribution centres. RELEX's machine learning and predictive analytics platform provides the demand signal processing and inventory optimisation required for ultra-fresh categories, where shelf-life constraints compress the decision window significantly. Accenture joined the programme as implementation and advisory partner, combining delivery expertise with RELEX's AI platform to ensure operational integration at enterprise scale. The deployment creates a unified planning model across fresh categories and regions, replacing inconsistent local processes with a single data-driven framework and giving METRO's supply chain teams the visibility needed to make smarter daily replenishment decisions.

The RELEX deployment is designed to deliver measurable improvement across METRO's fresh food supply chain. Expected outcomes include:

• Fresher products on shelf through tighter, more accurate replenishment cycles across 540 stores
• Reduced food waste at both store and distribution centre level, spanning all 70 DCs
• Lower operational effort as AI-driven automation replaces manual planning processes
• Improved availability across ultra-fresh categories where stockouts directly affect METRO's hospitality and foodservice customers

Alexander Stepannikov, Head of Supplier Collaboration & Ultra-fresh Ordering at METRO, cited improved daily decision-making and the ability to serve customers with greater confidence as core expected outcomes.

• Ultra-fresh supply chains require AI forecasting purpose-built for short shelf-life constraints — generic replenishment tools cannot match the speed and accuracy demands of this category.
• At enterprise scale, pairing a specialist AI vendor (RELEX) with a systems integrator (Accenture) is a proven approach for managing deployment complexity across large, multi-channel networks.
• Standardising the planning model across regions before optimising locally is a prerequisite: fragmented processes dilute the impact of any forecasting platform.
• Reducing waste and improving availability are not competing goals in fresh food — accurate demand forecasting addresses both simultaneously.