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Network Design in the Supply Chain 151 CASE STUDY Managing Growth at SportStuff.com In December 2008, Sanjay Gupta and his management team were busy evaluating t customer zones for planning purposes. Demand from busy evaluating the performance at Sport- each customer zone in 2007 was as shown in Table 5-15. Sanjay estimated that the next three years would see a however, was a mixed blessing growth rate of about 80 percent per year, after which f.com over the previous year. Demand had grown by Stuff.com over the previous y 80 The venture capitalists supporting the company were demand would level off very pleased with the growth in sales and the resulting increase in revenue. Sanjay and his team, however, could The Network Options clearly see that costs would grow faster than revenues if demand continued to grow and the supply chain network n t. This growth, however, was a m see that costs would grow faster than revenues ii Sanjay and his management team could see that they was not redesigned. They decided to analyze the perfor- c with the antici- space to cope with the antici- pated growth. One option was to lease more warehouse space in St. Louis itself. Other options included leasing warehouses all over the country. Leasing a warehouse involved fixed costs based on the size of the warehouse and variable costs that depended on the quantity shipped through the warehouse. Four potential locations for mance of the current network to see how it could be redesigned to best cope with the rapid growthtcie pated over the next three years. SportStuft.com Sanjay Gupta founded SportStuff.com in 2004 with a warehouses were identified in Denver, Seattle, Atlanta, mission of supplying parents with more affordable sports and Philadelphia. Leased warehouses could be either equipment for their children. Parents complained about small (about 100,000 sq. ft.) or large (200,000 sq. ft.). having to discard expensive skates, skis, jackets, and Small warehouses could handle a flow of up to 2 million shoes because children outgrew them rapidly. Sanjay's units per year, whereas large warehouses could handle a initial plan was for the company to purchase used equip- flow of up to 4 million units per year. The current ware- ment and jackets from families and surplus equipment house in St. Louis was small. The fixed and variable from manufacturers and retailers and sell these over the costs of small and large warehouses in different loca- Internet. The idea was well received in the marketplace, tions are shown in Table 5-16 demand grew rapidly, and, by the end of 2004, the com- pany had sales of $0.8 million. By this time, a variety of at a warehouse (excluding warehouse expense) was new and used products were being sold, and the corm- about $600 VF, where F is the number of units flowing pany received significant venture capital support. Sanjay estimated that the inventory holding costs through the warehouse per year. This relationship is based on the theoretical observation that the inventory In June 2004, Sanjay leased part of a warehouse in the outskirts of St. Louis to manage the large amount of held at a facility (not across the network) is proportional product being sold. Suppliers sent their product to the to the square root of the throughput through the facility warehouse. Customer orders were packed and shipped As a result, aggregating throughput through a few facili- by UPS from there. As demand grew, SportStuff.com ties reduces the inventory held as compared with disag leased more space within the warehouse. By 2007, gregating throughput through many facilities. Thus, a SportStuff.com leased the entire warehouse and orders warehouse handling I million units per year were being shipped to customers all over the United inventory holding cost States. Management divided the United States into six year If your version of Excel has problems solving incurred an of $600,000 in the course of the of Excel has problems solving the TABLE 5-15 Demand in 2007 220,000 350,000 175,000 Zone Demand in 2007 320,000 200,000 160,000 Zone Lower Midwest Upper Midwest Southeast