Johnson & Johnson Healthcare consumer packaged goods giant Johnson & Johnson's (J&J) European operations were comprised of 12 distribution centers in seven countries. The company's initial analysis showed there was little or no consolidation among facilities. The facilities had high operational costs (U.S. $10 million+), but transportation costs were relatively low (U.S. $6 million+). The distribution centers were geographically located to help meet the specific needs and service expectations of their European customers. Since J&J is always on the lookout for ways to streamline and improve its supply chain practices, it was very interested in ways to improve its manufacturing and distribution activities in Europe. An initial result of applying the network optimization software was a reduction in the number of distribution centers from 12 to 2. Although this scenario was accompanied by increases in the transportation costs to customer locations, overall systems costs decreased by U.S. $7 million. Given the strategic importance of maintaining acceptably high levels of customer service, however, it was important to incorporate the requirement of retaining reasonable stomer service levels (.e., one-day service for some customers, with two-day service for others) into the formulation of the network optimization model. In addition, it also was necessary for the model to consider factors such as the expense of long-term leases, etc. Subsequently, a network optimization model that responded to the issues discussed above was developed and utilized. The end result included a reduction in the number of distribution centers from 12 to 5, which translated into a decrease in facility costs from U.S. $10.1 million to U.S. $3.9 million. Although transportation costs increased slightly-from U.S. $6.6 million to U.S. $7.6 million, the overall network experienced a system savings of approximately U.S. $5 million. At the same time, the optimized network was able to meet customer service objectives such as those outlined above.
Johnson & Johnson
Healthcare consumer packaged goods giant Johnson & Johnson's (J&J) European operations were comprised of 12 distribution centers in seven countries. The company's initial analysis showed there was little or no consolidation among facilities. The facilities had high operational costs (U.S. $10 million+), but transportation costs were relatively low (U.S. $6 million+). The distribution centers were geographically located to help meet the specific needs and service expectations of their European customers. Since J&J is always on the lookout for ways to streamline and improve its supply chain practices, it was very interested in ways to improve its manufacturing and distribution activities in Europe.
An initial result of applying the network optimization software was a reduction in the number of distribution centers from 12 to 2. Although this scenario was accompanied by increases in the transportation costs to customer locations, overall systems costs decreased by U.S. $7 million. Given the strategic importance of maintaining acceptably high levels of customer service, however, it was important to incorporate the requirement of retaining reasonable stomer service levels (.e., one-day service for some customers, with two-day service for others) into the formulation of the network optimization model. In addition, it also was necessary for the model to consider factors such as the expense of long-term leases, etc.
Subsequently, a network optimization model that responded to the issues discussed above was developed and utilized. The end result included a reduction in the number of distribution centers from 12 to 5, which translated into a decrease in facility costs from U.S. $10.1 million to U.S. $3.9 million. Although transportation costs increased slightly-from U.S. $6.6 million to U.S. $7.6 million, the overall network experienced a system savings of approximately U.S. $5 million. At the same time, the optimized network was able to meet customer service objectives such as those outlined above.
are there other factors that the network optimization study should have considered?
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