What Is Distribution Requirements Planning (DRP)?

Distribution requirements planning (DRP) is a time-phased method for planning replenishment across a multi-echelon distribution network. It projects each location's demand, nets it against stock and inbound orders, offsets by transit time, then rolls those needs up the network so the plant sees one aggregated requirement to build against.

MRP figured out how to plan materials inside the four walls of a plant. DRP is the same idea pointed outward, at the warehouses, distribution centers, and depots that sit between the plant and the customer. Without it, each location reorders on its own, the plant gets blindsided by demand it never saw coming, and stock piles up in the wrong place while another site runs dry. DRP replaces that guesswork with one connected plan. This post explains how it time-phases replenishment across the network and feeds the whole thing back to the master schedule.

What is distribution requirements planning?

Distribution requirements planning is a time-phased, gross-to-net method for planning inventory replenishment across a network of stocking locations. It takes the same computational logic as material requirements planning, gross requirements, on-hand, scheduled receipts, planned orders, and applies it to distribution: each warehouse or distribution center is planned period by period, and the results are linked up the supply chain so a supplying location knows what its downstream locations will need before they order.

The word that matters is network. A single warehouse can be run with a reorder point. The moment you have several stocking locations fed by a central source, a regional depot serving local branches, a plant warehouse serving regional distribution centers, independent reordering falls apart, because each location's orders become demand on the location above it, and nobody is planning that chain. DRP plans it, turning a scattered set of reorder points into one time-phased picture of what moves where and when. It sits downstream of demand forecasting and feeds directly into the plant's production plan.

How does the time-phased logic work?

DRP works exactly like MRP, one location at a time, then links the locations together. For each stocking point and each time period, it starts with the gross requirement, the forecast or downstream demand, subtracts on-hand inventory and scheduled receipts already in transit, and if the result would drop below safety stock it plans a replenishment order. Crucially, it offsets that planned order backward by the transit lead time, so a shipment that takes a week to arrive is released a week before the stock is needed. The output is a time-phased schedule of planned receipts and planned orders for every location.

The link between locations is what makes it a network plan. A planned order at a distribution center is not the end of the calculation, it becomes a gross requirement at the location that supplies it, in the period the order is released. So the West distribution center's planned replenishments become demand on the regional warehouse, whose planned replenishments become demand on the plant. This upward roll-up, sometimes called imploding the requirements through the bill of distribution, is how a hundred scattered local orders turn into one coherent demand signal the plant can actually plan production around.

Read that record and the logic is plain: on-hand falls toward safety stock, a planned order is timed to arrive before it breaches, and because transit takes two weeks, the order that arrives in week 2 was released two weeks earlier. Multiply this record across every location, roll the planned orders upward, and you have the network plan. That planned order in week 2 shows up as a gross requirement on the regional warehouse in the week it ships.

How does DRP feed the master schedule?

DRP feeds the master schedule by handing the plant one aggregated, time-phased demand signal instead of a stream of surprise orders. Once the network's requirements have rolled all the way up to the source, the plant sees a single projected demand, when it needs to produce, how much, and for where, and that becomes an input to the master production schedule. The plant is no longer reacting to whatever the distribution centers happen to order this week; it is building to a plan it helped shape. This closes the loop between distribution and production, which is the whole point: DRP on the outbound side and MRP on the inbound side meet at the master schedule.

How do you run DRP across the network?

Run it as a repeatable calculation, bottom-up, then top-down.

1. Map the network and lead times. Define every stocking location, who supplies whom, and the transit time on each link, since the whole plan hinges on those offsets.
2. Forecast demand at the edges. Set the gross requirement at each customer-facing location from its own local forecast, because that is where real demand enters.
3. Net and plan at each location. Run the gross-to-net calculation, subtract on-hand and in-transit stock, protect safety stock, and plan replenishment orders period by period.
4. Offset by transit time. Release each planned order early by its lead time so the receipt lands before the stock runs short.
5. Roll requirements up the echelons. Turn each location's planned orders into gross requirements on its supplying location, all the way to the plant.
6. Feed the master schedule and re-plan. Hand the aggregated requirement to the master production schedule, then rerun as forecasts, receipts, and actual demand change.

What do the standards and data say?

Context from standards bodies and primary data:

• Distribution requirements planning is defined in the supply-chain body of knowledge maintained by the Association for Supply Chain Management (ASCM/APICS) which frames DRP as the time-phased extension of MRP logic to a multi-echelon distribution network.
• DRP emerged as a formal discipline in the 1980s, extending the gross-to-net, time-phased calculation of MRP outward from the plant to warehouses and distribution centers, and it remains a standard module of distribution planning today.
• The inventory DRP positions is a large, live number: the U.S. Census Bureau's Manufacturing and Trade Inventories and Sales series tracks business inventories in the trillions of dollars, much of it sitting in exactly the distribution locations DRP plans, with the inventories-to-sales ratio in a roughly 1.3 to 1.4 range in recent years.

The practical point: DRP is not a new idea, it is proven MRP logic pointed at the distribution network, and its value is putting the right stock in the right location instead of the wrong one.

How is DRP different from a reorder point?

A reorder point reacts to each location in isolation; DRP plans the whole network ahead of time. With reorder points, every warehouse waits until its own stock hits a trigger, then orders, and the supplying location only finds out when the order lands, which is why plants get whipsawed by demand they never saw building. DRP is forward-looking and connected: it projects each location's future needs, times the replenishment, and shows the plant the demand weeks before it arrives. That foresight is what tames the bullwhip effect, the way independent reorder points amplify a small demand swing into a large one as it travels up the chain. It is the distribution-side complement to the balancing work in demand-supply balancing and rests on the same clean split between forecast and calculated demand covered in dependent versus independent demand. Good DRP also depends on disciplined lean flow and tight inbound movements like milk-run logistics to keep the transit offsets honest.

Where DRP breaks in practice

DRP is only as good as its picture of stock and transit across the network, and that picture is usually the problem. If on-hand balances at each location are wrong, receipts post late, and transit times are optimistic guesses, the whole time-phased plan drifts out of sync with reality, and locations quietly go back to reordering on feel. The math is sound; the data feeding it is scattered across a warehouse system here, a transport record there, and a spreadsheet somewhere else. Harmony is an AI-native layer that connects machines, software, and paperwork into one operational layer, with no rip-and-replace, so inventory positions, receipts, and shipment status across locations become one live record instead of several stale ones. AI search returns cited answers across those records, so a planner can ask which locations are about to short a product or where excess stock is sitting and get a grounded answer, and Harmony's digital workflows route each replenishment and receipt to the right place. It is the same paper-to-digital move Harmony makes on the plant floor (see the CLS case study), and by keeping the network's data honest it also improves inventory turnover across the distribution chain, so working capital stops hiding in the wrong warehouse.