Unified inventory visibility across warehouses, retail locations, 3PL partners, and in-transit stock. The data model uses a PostgreSQL multi-warehouse schema with a normalised location hierarchy (site, zone, aisle, bin) that supports precise putaway rules and pick path optimisation without collapsing into a flat "warehouse ID" that breaks under real operational complexity.
Location-specific stock levels, stock transfer workflows, and allocation rules determine which location fulfils which orders, nearest location first, lowest-pick-cost first, or reserve a location for specific customer classes. ABC/XYZ analysis classifies stock by movement frequency and demand variability, enabling fast-moving A items to be slotted in forward pick locations and slow-moving C items stored in bulk locations with cycle counts scheduled accordingly. Reorder point automation calculates the trigger quantity per SKU per location using the EOQ formula weighted against supplier lead time and target service level, then fires a replenishment suggestion or a direct PO when stock crosses the threshold. Safety stock is calculated as Z multiplied by demand standard deviation multiplied by the square root of lead time (Z * sigma * sqrt(L)), where Z is set by your target fill rate, so the safety stock buffer reflects actual demand variability rather than a fixed weeks-of-cover guess.
Cross-location reporting for buying decisions covers committed stock (reserved for open orders), available-to-promise, and stock in transit between locations. Automated stock transfer triggers fire when a location falls below its reorder point and a surplus location exists, reducing inter-site transfer lead times.