Distribution Requirements Planning
How is DRP different from MRP?
MRP plans raw materials and components for production, while DRP plans finished-goods replenishment through the distribution network. Both use time-phased logic, but DRP focuses on warehouse-to-warehouse and factory-to-warehouse flow.
What is the core input to DRP?
Location-level demand forecasts, customer orders, on-hand inventory, open supply orders, safety stock parameters, and replenishment lead times are the core inputs used to calculate net requirements and recommended shipments.
What does DRP generate in an ERP system?
It typically generates planned transfer orders, stock transport requisitions, or replenishment recommendations, depending on the ERP design and whether the receiving site is a warehouse, DC, or branch location.
Distribution Requirements Planning (DRP) is a time-phased inventory replenishment method that determines what finished goods are needed, where, and when across a distribution network. It applies MRP-style gross-to-net logic to distribution: forecast demand and customer orders minus on-hand inventory and scheduled receipts generates planned replenishment, transfer, or stock transport orders to prevent stockouts while limiting excess stock.
On the shop floor, DRP sits downstream of production planning: the factory builds to a master schedule, while DRP determines which warehouse gets finished goods, in what quantity, and when. In multi-echelon networks, it aggregates customer demand, regional signals, and safety stock targets, then allocates inventory from the supplying site based on lead time, lot size, and target stock policies. In warehouse operations, DRP drives replenishment planning by creating a forward-looking schedule of expected shortages and recommended shipments. For raw materials, DRP is indirect, but ERP suites use the same logic to send inter-site supply signals that trigger production or procurement. The DRP table includes forecast demand, on-hand inventory, open orders, safety stock, planned receipts, lead times, and recommended quantities, helping to prevent surprise replenishment waves and dock congestion. Its value is converting edge demand into time-phased supply actions, improving service while reducing ordering, transport, and carrying costs.
Safety stock misconfiguration: A target minimum set too low releases replenishment too late, leaving a branch warehouse stocked out before the next receipt. Set too high, the network over-ships and ties up working capital in slow-moving inventory.
Bad lead-time data: Understated transfer lead times, dock-to-stock time, or production release times make the plan show supply arriving earlier than possible. This causes repeated expedite orders, missed service levels, and unstable replenishment signals.
Forecast distortion at the wrong echelon: A distribution forecast not separated by location over-allocates one DC and under-allocates another, creating phantom shortages, bottlenecked receiving, and unnecessary lateral transfers.