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prices. In addition, there is the problem of storing that inventory during the season. The TOC solution, as described by Schragenheim et al. (2009), begins with a plan to deliver rather frequently during the season an amount equal to actual sales during the previous delivery period. This requires the retailer to begin the season (and each replenishment cycle) with a stock equal only to the maximum likely sales during the replenishment period. The regional warehouses will hold some stock but most stock will be held in a central warehouse at the manufacturer. This approach takes advantage of the fact that relative variation is much smaller at the manufacturer than it is at the typical retailer. There is less stock in the system, but availability of the item at the retailer is increased because of the frequent deliveries. This is essentially a DBR process applied over the supply chain. Experience has shown that the increase in Throughput far surpasses any increase in the transportation costs for more frequent deliveries.

Supply Chain Management

Simatupang et al. (2004) discuss the application of TOC to supply chain management. A supply chain consists of different firms that deliver products and services from raw materials to end customers. All the different players such as manufacturers, distributors, and retailers play significant roles in creating value for the ultimate customer. They also note that reliable global performance measures help the chain members to measure progress. They introduce the performance measures Throughput Dollar Days (TDD), a measure of things done too late and thus endangering Throughput, and Inventory Dollar Days (IDD), a measure of things done too early (or that should not have been done) and thus incurring extra inventory carrying costs.

An important aspect of supply chain management is the decision of whether to out-source particular components—the make-or-buy decision. Of course, component quality is one of the most important aspects of this decision, if not the single most important aspect. Traditionally, cost has been the second most important factor—the cost to make versus the cost to buy. However, in TOC, the decision’s impact on Throughput is important and Throughput is impacted in different ways depending on whether making the component requires time at a resource constraint (and perhaps also whether it requires time at a CCR). If making the part requires only non-constraint time and no worker will be laid off because of outsourcing, then traditional cost accounting overestimates the marginal cost of making the part. If the part does require constraint time, then purchasing the part allows additional units of the least profitable part to be added to the drum schedule, thus increasing Throughput. Traditional cost accounting underestimates the opportunity cost of making the part. Either way, TOC arrives at different numbers for the decision than does traditional accounting. This decision is discussed at length in Gardiner and Blackstone (1991) and is updated by Balakrishnan and Cheng (2005), who point out that if the part is a strategic part, then the cost to buy may not be the most important consideration. The make-or-buy decision is also mentioned in Hilmola (2001).

Walker (2002) provides an excellent discussion of the application of DBR to a supply chain. He discusses how to choose which partner should be the drum, how to tie the rope, total system Inventory measures, and managing as demand goes up and down. Walker (2005) states that the applicability of DBR has been expanded to include the entire supply chain network.

Cox and Walker (2006) have published a board game that uses poker chips in a stochastic supply chain. The players can alter the order policies and batching policies at various points in the supply chain and observe directly the impact on Inventory and service levels.

Service Environment

One of the reasons for keeping buffers as small as practical while not starving the constraint is that if there is too much work in a facility, then workers have a tendency