Perishable Goods Shelf-Life Optimization and FEFO Automation

This workflow automates the costly, manual process of identifying short-dated stock and deciding where to move it before it spoils. By integrating with lot-tracking systems like SAP EWM or Oracle WMS, it continuously monitors remaining shelf-life across all distribution centers and retail stores. The core business value is direct waste reduction, which protects gross margin and reduces markdown expenses. It also improves service levels by ensuring high-velocity locations are stocked with the freshest product, enhancing customer satisfaction and compliance for regulated goods like pharmaceuticals and food.

Implementation requires building an orchestrator, likely with LangGraph or a custom microservice, that ingests real-time lot data, applies business rules for transfer cost and destination velocity, and generates prescriptive work orders. Critical controls include human review gates for high-value transfers, configurable expiration thresholds, and integration with transportation management (TMS) for execution. The system must provide full audit trails for compliance and a dashboard tracking key metrics like waste reduction percentage and transfer cost per unit saved to demonstrate clear ROI.

This workflow automates the critical, time-sensitive process of moving perishable inventory before it expires. It directly attacks the operational bottleneck of manual lot tracking and reactive markdowns, converting potential waste into revenue by dynamically routing short-dated goods to locations with the highest predicted consumption velocity. The savings come from reduced spoilage write-offs, lower discounting, and improved sell-through, while the architecture must integrate real-time data from lot-tracking systems (e.g., SAP EWM, Oracle WMS), demand forecasts, and transportation management platforms to execute transfers within shelf-life windows.

Implementation requires building a multi-agent orchestrator, likely using LangGraph or a custom microservice, that ingests lot dates and locations, scores transfer urgency, and matches with demand signals. Critical controls include approval gates for high-cost moves, confidence thresholds for demand predictions, and an immutable audit trail for food safety compliance. The system must handle exceptions—like cold chain breaches or forecast errors—by routing to human planners. Observability dashboards track key metrics: waste reduction percentage, transfer cost per unit saved, and fulfillment rate for short-dated SKUs.

This workflow automates the critical margin protection task of moving perishable goods to locations where they will sell before expiring. It ingests real-time lot data from ERP or WMS systems, calculates remaining shelf-life, and models transfer feasibility against demand forecasts and logistics costs. The operational upside comes from reducing markdowns and write-offs by 15-30%, while improving service levels for high-velocity items. Implementation requires tight integration with systems like SAP EWM or Oracle WMS for lot tracking and a TMS for executing cost-optimized transfers.

Execution requires a rules engine to prioritize transfers based on expiration proximity, local sales velocity, and transfer cost. The architecture must include an approval layer for large-value moves and a monitoring dashboard for waste KPIs and exception rates. Controls include validating lot integrity, simulating network impact pre-execution, and maintaining a full audit trail for compliance. Rollout is typically phased, starting with a single product category and distribution lane to validate logic and integration stability before scaling network-wide.

For perishable goods, margin erosion is a direct function of time. Manual tracking of lot dates and reactive transfers lead to waste and lost revenue. A custom FEFO automation workflow ingests real-time lot data from ERP or WMS systems like SAP EWM or Oracle, applies business rules for transfer cost and service-level impact, and automatically generates optimized transfer orders. This shifts aging inventory to locations with the highest predicted consumption velocity before expiry, directly reducing write-offs and protecting margin.

Implementation requires a central orchestration layer, often built with LangGraph or a custom microservice, that polls lot-tracking APIs, runs optimization logic, and integrates with Transportation Management (TMS) and Warehouse Management (WMS) systems for execution. Critical controls include approval gates for high-cost transfers, real-time reconciliation to prevent system drift, and configurable alerting for lots nearing expiry without a transfer plan. The rollout must be phased, starting with a single product category and DC pair, to validate date accuracy and transfer logic before full network deployment.