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Diego Amara BUSI-740 Assignment: Reebok NFL Replica Jerseys Given the uncertainty associated with player demand, how should Reebok approach inventory planning for the NFL
Diego Amara BUSI-740 Assignment: Reebok NFL Replica Jerseys Given the uncertainty associated with player demand, how should Reebok approach inventory planning for the NFL replica jerseys? As stated by Simchi-Levi et al. (2021, p. 34) "customer demand had always been hard to predict but a few techniques can be utilized to minimize those risks, like for example Risk Pooling. A technique that protects organizations from the variability on customers' demands, by leveraging multiple inventories (Oded et al., 2011). A second alternative is to increase the order number of blank jersey versus dressed jerseys, lowering the risk of discounting or hooding inventory from one year to the next, while only adding an extra dollar fifty to the cost of each blanked jersey tha should have been dressed. What should Reebok's goal be? Should Reebok minimize inventory at the end of the season? Or maximize profits? Can Reebok achieve both? What service level should Reebok provide to its customers? Reebok should take advantage of the fact that they are the only licensed manufacture of the NFL and order inventories that allow the organization to maximize profitability. Which according to the business case is a "high margin and lucrative business" (Simchi-Levi et al., 2021, p. 156). By increasing the number of blank Jerseys Reebok could manage risk, maximize revenue opportunities, and provide great service levels. Since the overall cost of ordering and holding a blank jersey from one season to the next is $12.95 per unit, leaving $11.06 in gross margin, and the losses of discounting a blank jersey after one season is only -$5.95 (Table 1). Table 1 Gross Margin Analysis Blank Jersey $ (9.50) Dress cost at Indianapolis $ (2.40) Manufacture cost/unit $ (11.90) Cost of holding inventory $ (1.05) Unit Cost for next season $ (12.95) Wholesale Price $ 24.00 Gross Margin $ 11.05 Discounted Inventory Price $ Unit Cost for next season $ Discounted Gross Margin $ 7.00 (12.95) (5.95) Are the models in Section 2.2.2 helpful here? What is the cost of underage for a dressed jersey? What is the cost of overage for a dressed jersey? How might Reebok decide between dressed jersey and blank jerseys? The model of Section 2.2.2 is definitely helpful in a scenario such as the one presented on this case study. Reebok faces high levels volatility based on weekly performances of teams and players, and by using a demand projection that can change over time the organization could minimize costs, as well as maintaining only the necessary levels of inventory (Simchi-Levi et al., 2021; Ryu et al., 2014). Reebok cost of underage for a dressed jersey is $1.50 if the unit in question is replaced by a blank jersey that could be dressed in Indianapolis (Table 2). Reeboks cost of overage for a dressed jersey is $3.40 if the organization has to sale this unit at a discounted price of $7.00 (Table 3). Reebok's decision on which type of jersey to order should be a reflection of the organizations risk pooling analysis and the minimum number of units that manufactures require to produce dressed jerseys. Table 2 Blank Jersey $ (10.40) $ 0.90 $ Dress cost at Indianapolis $ (9.50) Dressed Jersey $ (2.40) $ (2.40) Manufacture cost/unit $(11.90) Manufacture cost/unit $ (10.40) $ (1.50) Table 3 Discounted Inventory Price $ 7.00 Dressed Jersey $ (10.40) Discounted Gross Margin $ (3.40) Using the forecast for the New England Patriots, what is the optimal quantity to order for each player? For blank jerseys? What profit do you expect for Reebok? How much and what type of inventory is expected to be leftover at the end of the season? What service level? By using the information provided at the case study, Reebok should order a total of 68,469 New England Patriots jerseys, the breakdown of how many jerseys for each player and blanks jerseys is presented at Table 4. Out of the 68,469 jerseys ordered Reebok can expect a total profit of $901,434.44, due to average cost of $10.40 for dressed jerseys and $11.90 for blank jerseys, minus a wholesale price of $24.00 per unit sold. (Table 5). It is important to mention that with the current order, Reebok can potentially have 22,944 jerseys left at the end of the season, with 6,645 of those being Blank Jerseys and the remaining 16,299 being Dressed Jerseys (Table 6). Overall with the order presented, Reebok would be able to maintain a fair but safe service levels, ordering 78% of total inventory mean and 86% of the blank inventory mean (Table 7). According to Wang et al. (2018) even though holding high inventory levels could increase flexibility, that strategy can be very expensive offsetting some of the potential profitability gained by Reebok. Table 4 Description Units Order Brady, Tom, #12 24,023 Law, TY, #24 8,253 Brown, Troy, #80 6,371 Vinatieri, Adam, #04 5,677 Bruschi, Tedy, #54 4,315 Smith, Antowain, #32 0 Blank Jerseys 19,829 New England Patriots Total 68,469 Table 5 Description Units Order Cost/Unit Total Cost Revenue/Unit Total Revenue Brady, Tom, #12 24,023 $ Law, TY, #24 8,253 $ 10.40 $249,836.26 $ 10.40 $ 85,834.26 $ Profit 24.00 $ 576,545.21 $326,708.95 24.00 $ 198,079.07 $112,244.81 Brown, Troy, #80 6,371 $ 10.40 $ 66,261.87 $ 24.00 $ 152,912.02 $86,650.14 Vinatieri, Adam, #04 5,677 $ 10.40 Bruschi, Tedy, #54 4,315 $ 10.40 $ 59,042.02 $ $44,878.43 $ 24.00 $ 136,250.81 $ 77,208.79 Smith, Antowain, #32 0 $ $ Blank Jerseys 19,829 $ New England Patriots Total 68,469 10.40 11.90 $235,968.71 $ $741,821.56 $ 24.00 $ 24.00 $ 24.00 $ 475,903.28 $ 1,643,256.00 103,565.61 $ 58,687.18 $ $239,934.57 $901,434.44 Table 6 Description Units Order Risk Brady, Tom, #12 24,023 7,102 Law, TY, #24 8,253 2,440 Brown, Troy, #80 6,371 1,883 Vinatieri, Adam, #04 5,677 2,769 Bruschi, Tedy, #54 4,315 2,105 Smith, Antowain, #32 0 Blank Jerseys 19,829 6,645 New England Patriots Total 68,469 22,944 Table 7 Description Mean Units Order % of Mean New England Patriots Total 87,680 68,469 78% Blank Jerseys 23,000 19,829 86% References Wang, H., Wei, Y., & Simchi-Levi, D. (2018). Increasing Supply Chain Robustness through Process Flexibility and Inventory. Production and Operations Management, 27(8), 1476- 1491. https://doi-org.ezproxy.liberty.edu/10.1111/poms.12887 Oded, B., Dmitry K., & Mahdi, T. (2011). On the Benefits of Risk Pooling in Inventory Management. Production and Operations Management, 20, 57-71. https://doi- org.ezproxy.liberty.edu/10.1111/j.1937-5956.2010.01134.x Ryu, S., Chen, A., & Choi, K. (2014). A modified gradient projection algorithm for solving the elastic demand traffic assignment problem. Computers & Operations Research, 47, 61- 71. https://doi-org.ezproxy.liberty.edu/10.1016/j.cor.2014.01.012 Simchi-Levi, D., Kaminsky, P., & Simchi-Levi, E. (2021). Designing and managing the supply chain: Concepts, strategies, and case studies. Boston: McGraw-Hill/Irwin.
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