Distribution Scheduling

Two companies' approaches to exception-managing their DRP systems illustrate the different solutions required by different environments.

In the first of these companies, a large consumer nondurables manufacturer, very real capacity constraints and clear demand priorities were not being recognized by the distribution resource planning process. This company produces in excess of 500 SKUs, for which demand is promotion-driven and difficult to predict. With two levels of distribution infrastructure (plant warehouses and regional distribution centers) and dedicated contract carriage, the company has a high degree of distribution flexibility.

Given its manufacturing capacity constraints, management knew it must do a better job of maximizing the utilization of production assets and stabilizing production. To accomplish this, they imple­mented a finite capacity master scheduling tool. By importing DRP-generated net requirements into the package, setting on-hand levels to zero, and employing frozen time fences of three weeks, they were able to improve utilization and stability.

Unfortunately, the issues presented by differing demand priorities remained. Although the master scheduling tool had the ability to distinguish between demand for actual orders and demand for stock replenishment (and prioritize accordingly), it was being fed by a DRP system that could not convey that information. To correct for the inevitable service shortfalls, the company must frequently rebalance stock between warehouses. But it considers these redeployment costs acceptable in light of the returns it is experiencing from better asset utilization and stability in produc­tion.

The situation was quite different for a second company, a leading food manufacturer, which was eager to improve its ability to provide quick-response service to customers. Here, capacity constraints were not a problem; demand is relatively predictable and the company produces just 150 SKUs. Still, the company's DRP system was not equal to the challenge of containing inventory and distribution costs in a high-service environment.

Like the first company, this company made use of more sophis­ticated production scheduling software, but with different goals in mind. Rather than importing DRP-generated requirements, they fed the package from a variety of sources, giving it visibility into forecasted orders, actual demand, on-hand inventory levels, and inventory targets. As a result, the production schedules it generated allowed for distribution to warehouses much closer to the order stream, reducing systemwide inventory and decreasing distribution costs. Accomplishing this, however, meant forcing manufacturing to be much more flexible, at greater per-unit production cost.

To be Continued

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