Distribution Planning: from static DRP to a live plan

Most companies still plan distribution with fixed batches, moving averages or a single network-wide coverage rule. The outcome is predictable: one DC always in stockout, another always in excess, panic transfers and freight cost climbing without clear cause.

Mature distribution planning is the opposite of that.

It is a demand-driven plan, frequently recomputed, connecting regional demand, stock per DC, transport capacity and fair-share rules — producing an executable, balanced transfer plan.

Planning distribution is not about moving boxes. It is about deciding, based on every network constraint, where to transfer, how much and when — before the problem shows up at the counter.

A structured process starts from regional demand, projects coverage per DC, generates transfers respecting capacity and applies fair share when stock is limited:

If your demand varies, replenishment must vary too. Computing transfer volume from fixed quantities or moving averages looks simple, but guarantees that coverage breaks at peaks and inflates at valleys.

The correct rule is to maintain the coverage target. If DC-North targets 14 days and demand jumped from 100 to 140 units/day, the next transfer must deliver enough volume for 14 × 140 = 1,960 units, not the old 1,400.

Coverage is a promise to the customer; fixed batch is a spreadsheet convenience.

Well-planned transfers balance the inventory health of the entire network. Instead of each DC reacting in isolation, the whole operation behaves as a single chain, with material flowing from where it is in excess to where it is short.

Each transfer plan row carries origin, destination, modal, quantity, lead time and reason. That last field is essential: it explains the why and lets the decision be audited later.

Quite often, central stock is not enough to fully serve every destination. The question shifts from "how much to send" to "whom to send first". Without a clear rule, this becomes informal pressure — the loudest gets served.

Fair Share is the allocation ruleset that systematically and auditably decides how to split scarce stock. Good implementations combine objective factors:

Fair Share is not equal justice. It is smart justice: prioritizing who has more to lose and who delivers more value to the company.

A classic DRP (DRPII) computes transfer requirements ignoring whether transport and storage can absorb them. The theoretical result becomes an execution nightmare: trucks missing or piling up, receiving clogged, freight waiting for a slot.

NPLAN distribution solutions go further: the engine considers finite transport and per-DC storage capacity, producing a plan that does not break the operation.

A distribution plan that ignores capacity creates orders; a plan that respects capacity creates execution.

Distribution is essentially a balancing problem across three tensioned variables: service level (meeting demand), cost (freight, storage, tied capital) and efficiency (fleet and warehouse usage).

Pushing service without criteria inflates urgent freight cost and parks stock at the wrong DCs. Cutting cost without criteria kills service. The right tool lets you simulate scenarios and visualize the trade-off — before committing.

The best distribution plan is not the cheapest nor the safest. It is the one that best balances service, cost and capacity usage — for the company's moment.

NPLAN's Distribution Planning projects let companies plan their product distribution logistics considering every chain constraint — seeking the best balance among service, cost and efficiency. It is the DRP tool you are looking for.