DC Velocity - Tip Sheet 2012

are losers, and then to structure supply chain policies such that some or all of the losers are turned into winners. This may require changing the replenishment model and service-level agreements for a specific customer/product combination. For example, a tire manufacturer that provides the same one-day lead time for both A customers and D customers may want to change the policy to three days for the D customers. This would move the inventory buffer point upstream in the supply chain, reducing overall inventory. The upstream buffer would hold a larger pool of inventory, thus increasing the odds that downstream demand will be satisfied with the exact product required. This change may have the effect of turning D customers into B customers.

2. Implement differentiated demand policies in core
functions

It was not too long ago that demand was thought of as a single requirement to which the supply chain reacted. Today, we know that demand signals can come in the form of orders, forecasts, and safety stock, and that they can come from different channels (retail, Web, distributors, and enterprise) and from different sources (original equipment manufacturers [OEMs], aftermarket/spares). Furthermore, demand signals can come from different customer types, as discussed in the previous section (large, highly profitably customers versus small, unprofitable customers).

In order for the supply chain to align with segmenta-
tion strategies, the demand signals within core supply
chain management functions—such as master planning,
transportation planning, distribution planning, and fac-
tory planning—must be prioritized in a way that aligns
with those strategies. The demand priorities must be
driven by the overall segmentation strategy that is tied to
the service/profitability framework discussed in the pre-
vious section.

3. Implement differentiated inventory policies

Inventory may be the area where supply chain segmentation has been employed most often in the past five years. Inventory optimization has progressed during that period to become a process-driven discipline of regularly determining what inventories to carry, where, in what form, and in what quantities across a multiechelon network. Once again, this starts with the foundational step of understanding the value propositions offered for each customer/product intersection. Based on this information, companies use analytic tools to evaluate the entire network and determine the stocking policies for each product at each stocking location.

This process will include determining how much fin-ished-goods inventory to carry downstream at regional distribution centers (DCs), upstream at central DCs, and at factory locations. It will also include deciding where to incorporate postponement strategies by determining how much inventory to carry in semifinished mode or as com-