Ii was expected that the implementation of dynamic time-based postponement in this research setting would improve product availability and reduce the costs identified in the business opportunity. The cost components included in the business opportunity (see Table 4.6) are inventory holding costs, obsolescence, and transshioments.
Improving product availability would reduce costs but would not affect revenue or customer service levels because there were no stockouts facing end- customers. Instead, when a restaurant was running Out of stock, product was transhipped from another restaurant in the neighborhood. Therefore, an increase in product availability would result in a cost reduction. Table 4.22 summarizes the actual product availability at the restaurants measured as the probability of no stockout.
Table 4.22 shows that the actual product availability was 91.4% and 92.3% for Ingredients A and B respectively, and that 285 transshipments between restaurants were needed to avoid end-customers from facing a stockout. Since the optimization
Number of Lead-times between Ingredient A 1637 distribution centers and restaurants | Ingredient B 1870
Number of Transshipments Ingredient A 141 91.4% 99.5% 8.2 between Restaurants Ingredient B 144 92.3% 99.5% 9.3 1) PNS stands for "Probability of No Stockout"
Table 4.22
Expected Improvement in Product Availability at Resturants and Expected Number of Transshipments Needed
209
results were based on a 99.5% probability of no stockout, and assuming that the restaurants would place the same number of orders to the distribution centers, 18 transshioments between restaurants would be needed between the two ingredients if dynamic time-based postponement was used.
The size of the business opportunity was presented in Table 4.6 and estimated at $8,266,718 for the supply chain, considering all restaurants in the franchise system.
As asummary, the totals by cost component of the business opportunity are shown on Table 4.23 as well. Table 4.23 shows, that the cost of obsolescence for the four supply chain members, for the portion of the supply chain included in the optimization model is $16,627. This amount scaled to the system (including all franchisor- and franchisee-owned restaurants } equals $ 536,355. The costs that can be reduced are $ 32,033 for to the portion of the supply chain in the model. This
Business Opportunity - Totals
Cost for LTO for the
Portion of the System-wide Cost Senet Supply Chain in the for LTO (2
Model ()
Inventory Holding Cost| $ 3523| $ 113,645 Left Over Product| $ 16,627] $ 536,355 Transshipments| $ 11,883} $ 383,323
System-wide Cost per year (8 LTOs/Year)| $ 8,266,581
1) This cost includes inventory holding cost excluding obsolescence, the cost of left-over product (obsolescence), and transshipments scaled to the portion of the supply chain represented by 177 restaurants.
2) This costs includes inventory holding costs excluding obsolescence, the cost of left-over product (obsolescence), and transshipments scaled to all restaurants in the system
Table 4.23
Summary of Business Opportunity 210
cost is equal to § 1,033,323 system-wide for one LTO. Since there were eight LTOs a year, and assuming that LTO-1 1 was representative of the other seven, the ousiness opportunity for the four members of the supply chain is $ 8,266,581.
Only part of this amount can be saved because inventories still will be held, transshipments will be used to avoid end-customers from facing stockouts, and it is reasonable to expect that some product will become obsolete. Table 4.24 summarizes the expected costs from implementing dynamic time-based postponement? for these three categories. Based on the output of the scenarios developed with the optimization model, it was estimated that the inventory holding cost excluding obsolescences wouid be §$ 1,172, shown in Table 4.24. Additionally, it was expected that restaurants would need 18 transshioments. The estimated cost of these transshioments was $ 540, Obsolescence costs depend on the obsolescence rate, which in the past averaged 84.9% acrass all stocking locations. That is, from the inventory availabie at ailstocking iocations at the end of phase eight, 84.9% became obsolete. Obsolescence represented a considerable portion of the expected casts for the LTO. Bul it was expected that the obsolescence rates would be reduced due to the increased coordination required to implement dynamic time-based postponement. Therefore, obsolescence costs were calculated for four obsolescence rates: 84% {the historic average obsolescence rate}, 66%, 48%, and 30%.
Adding the three cost components, the expecied cost for LTO-11 for the portion of the supply chain in the model was calculated for each of the obsolescence rates. The resulting costs were scaled to all restaurants in the system {for the whole supply chain formed by the two manufacturers, the nine distribution centers and ail franchisees- ana franchisor-owned restaurants) ana then multiplied by eight, which was the number of LTOs that were hela per year. These calculations result in expected annual cost savings for the four members of the supply chain of between $5.3 and
$6.9 million, depending on the obsolescence rate the supply chain wouid achieved.
211
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Table 4.24 also shows that the expected cast reduction as a percentage of actual cost was between 64.8% and 84.0%. Despite the fact that these percentages might appear to be very high, if has fo be recognized that these cost calculations did not include unavoidable cosis such as the cost of goods sold. In order to verify that these cast savings were reasonable, the total cost for the LTO for the supply chain as a whole was determined considering both avoidable and unavoidable costs. Then, the estimated cost savings were calculated as a percentage of this total cost. The expected cost savings represenied belween 5% and 6% of the fotal cast for the limited-time offer.
SUMMARY
The quaniitative analyses performed as part of this research were presented in this chapter as well as the assessment of the business opportunity for the implementation of dynamic time-based postponement, the methodology to gather information and plan for each of the three periods of dynamic time-based postponement, and the expected benefits from its implementation. Chapter 5 contains a summary of the results developed in Chapter 4, as well as the managerial Implications, limitations, and suggestions for future research. Finally, a commentary
is offered,
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213
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CHAPTER 5
SUMMARY AND CONCLUSIONS
The purpose of this chapter is to present the summary of the findings and the conclusions of the research. First, the research purpose is reviewed and each research questions is addressed individually. Second, the major conclusions are presented. Third, the managerialimplications are presented. Fourth, the limitations of this research are described. Fifth, the future research opportunities are provided.
Finally, a concluding commentary is presented.