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Inventory Proposal, Part 1
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Inventory Proposal, Part 1

McDonald’s is an organization that offers fast food, which includes hamburgers, French fries, and other items, to the public. McDonald’s restaurant works to provide hot and fresh food to its customers. Maintaining freshness is sometimes difficult due to the inventory problem it faces. “What used to be the case was McDonald's would pre-cook a batch of hamburgers and let them sit under heat lamps. They would keep them for as long as possible and eventually discard what couldn't be sold” (Atkinson, 2005, p. 1).
Minimizing waste is the goal of McDonald’s just in time inventory system. The benefit of making food when it is ordered is that the customer receives a fresh product and McDonald’s can eliminate waste and protect their inventory. “The only way to get a fresh hamburger under the old system was to make a special order. Now, due to more sophisticated burger-making technology (including a record-breaking bun toaster), McDonald's is able to make food fast enough to wait until it's been ordered” (Atkinson, 2005, p. 1).
Inventory Management Problem
Every business incurs operational costs and in restaurants inventory control is particularly important because the items held in inventory tend to be highly perishable. “It is not uncommon to have several hundred different types of raw food product in storage at any one moment and poor management leads to a significant waste” (Said, 2012). Each McDonald’s restaurant franchise utilizes a just in time inventory and delivery system in which the preparation of a meal does not begin until the customer has placed a specific order. This system allows McDonald’s to provide a customer with their order as fast as possible while having the finished product sitting in inventory for as little time as possible. The benefit to this type of system is that for a restaurant, it is possible to improve quality and lower costs.
There are risks associated with using the just-in-time inventory system approach. For example, there will be a significant dependence upon particular suppliers under such an inventory system. For example, if a McDonald’s were to commission a highly proprietary product to a single supplier this inventory system would put such a McDonald’s at an even higher risk of rip-off on behalf of the supplier because the McDonald’s would have no immediate inventory to buffer an interruption of supply. Such an interruption of supply might be so costly that McDonald’s might just allow the supplier to overcharge them up to the cost of this interruption. “This rip-off cost might completely cancel out or even exceed the savings that make just in time inventory systems appropriate for McDonald’s in the first place” (Atkinson, 2005).
Quarterly Sales
To mitigate some of these problems the team determined that it would be beneficial to make some modifications to the inventory management approach. We began by looking at the historical inventory data for the last four years from a seasonal perspective in order to refine the inventory plans. Figure 1 below presents this information in a quarterly format with each quarter being one period. The inventory is provided for each quarter each of the quarters and then was broken out annually for the four years for which data is available.

McDonald’s FranchiseSales by Quarter | Month | Year 1 | Year 2 | Year 3 | Year 4 | 1 | 55,200 | 39,800 | 32,180 | 62,300 | 2 | 57,350 | 64,100 | 38,600 | 66,500 | 3 | 15,400 | 47,600 | 25,020 | 31,400 | Period 1 | 42,650 | 50,500 | 31,933 | 53,400 | Total Sales | 127,950 | 151,500 | 95,800 | 160,200 | 4 | 27,700 | 43,050 | 51,300 | 36,500 | 5 | 21,400 | 39,300 | 31,790 | 16,800 | 6 | 17,100 | 10,300 | 31,100 | 18,900 | Period 2 | 22,067 | 30,883 | 38,063 | 24,067 | Total Sales | 66,200 | 92,650 | 114,190 | 72,200 | 7 | 18,000 | 45,100 | 59,800 | 35,500 | 8 | 19,800 | 46,530 | 30,740 | 51,250 | 9 | 15,700 | 22,100 | 47,800 | 34,400 | Period 3 | 17,833 | 37,910 | 46,113 | 40,383 | Total Sales | 53,500 | 113,730 | 138,340 | 121,150 | 10 | 53,600 | 41,350 | 73,890 | 68,000 | 11 | 83,200 | 46,000 | 60,200 | 68,100 | 12 | 72,900 | 41,800 | 55,200 | 61,100 | Period 4 | 69,900 | 43,050 | 63,097 | 65,733 | Total Sales | 209,700 | 129,150 | 189,290 | 197,200 |
Figure 1.
Quarterly Seasonal Indexes
After calculating the seasonal averages, the team proceeded to determine the centered moving average (CMA) which was achieved by adding the first two quarter periods and continuing the process for the remaining periods. Leveraging this information, the team was able to determine the ration to centered moving average and establish seasonal indexes for the sales to factor into the inventory recommendations for the McDonald’s franchise. With the seasonal indexes calculated the deseasonalized sales for the franchise. The aggregated data for this set of calculations is represented in Figure 2 which follows. Figure 3 demonstrates the next step in the series of calculations which was the calculation of the seasonal indexes. Centered Moving Average and Deseasonalization | t | Year | Quarter | Inventory | CenteredMovingAverage | Ratio toCMA | SeasonalIndexes | Inventory Deseasonalized | 1 | 1 | 1 | 127,950 | | | 0.990 | 129,242.4 | 2 | 1 | 2 | 66,200 | | | 0.762 | 86,876.6 | 3 | 1 | 3 | 53,500 | 117281.250 | 0.456 | 0.598 | 89,464.9 | 4 | 1 | 4 | 209,700 | 123531.250 | 1.697 | 1.448 | 158,632.6 | 5 | 2 | 1 | 151,500 | 150831.250 | 1.004 | 0.990 | 153,030.3 | 6 | 2 | 2 | 93,300 | 112331.250 | 0.830 | 0.762 | 122,440.9 | 7 | 2 | 3 | 35,100 | 95300.000 | 0.368 | 0.598 | 58,695.7 | 8 | 2 | 4 | 129,150 | 103448.750 | 1.345 | 1.448 | 89,192.0 | 9 | 3 | 1 | 95,800 | 118965.000 | 0.805 | 0.990 | 96,767.7 | 10 | 3 | 2 | 114,190 | 123137.500 | 0.927 | 0.762 | 149,855.6 | 11 | 3 | 3 | 138,340 | 142455.000 | 0.971 | 0.598 | 231,337.8 | 12 | 3 | 4 | 189,290 | 145256.250 | 1.303 | 1.448 | 13,725.1 | 13 | 4 | 1 | 160,200 | 137858.750 | 1.162 | 0.990 | 161,818.2 | 14 | 4 | 2 | 72,200 | 136698.750 | 0.528 | 0.762 | 94,750.7 | 15 | 4 | 3 | 121,150 | | | 0.598 | 202,592.0 | 16 | 4 | 4 | 197,200 | | | 1.448 | 136,187.8 |
Figure 2

| Calculation of Seasonal Indexes | | Year | 1 | 2 | 3 | 4 | | 1 | | | 0.456 | 1.697 | | 2 | 1.004 | 0.830 | 0.368 | 1.345 | | 3 | 0.805 | 0.927 | 0.971 | 1.303 | | 4 | 1.162 | 0.528 | | | | mean: | 0.990 | 0.762 | 0.598 | 1.448 | 3.799 | Figure 3
Annual Increase of Inventory
As the team evaluated the existing system for inventory management, it was important to note that the key issue to be addressed is profitability. Failure to effectively manage the inventory results in significant losses. In order to help with advanced planning the team used the slope intercept to project the annual increase of inventory needed. The formula used is y = 117.51 X + 41765.625, where y is equal to the number of units in inventory and X is the month. The slope, 117.51, is the average value of index and the intercept, 41765.625, is the average of the monthly inventory forecasted for year 5 as indicated in Figure 4 and Figure 5 below. Month (X) | | Y (number of units in inventory) | 1 | 117.51 (1) + 41765.625 | 41883.135 | 2 | 117.51 (2) + 41765.625 | 42000.645 | 3 | 117.51 (3) + 41765.625 | 42118.115 | 4 | 117.51 (4) + 41765.625 | 42235.665 | 5 | 117.51 (5) + 41765.625 | 42353.175 | 6 | 117.51 (6) + 41765.625 | 42470.685 | 7 | 117.51 (7) + 41765.625 | 42588.195 | 8 | 117.51 (8) + 41765.625 | 42705.705 | 9 | 117.51 (9) + 41765.625 | 42823.215 | 10 | 117.51 (10) + 41765.625 | 42940.725 | 11 | 117.51 (11) + 41765.625 | 43058.235 | 12 | 117.51 (12) + 41765.625 | 43175.745 |
Figure 4

Figure 5
Inventory Adjustments
Figure 6 demonstrates that there are fluctuations in sales and inventory not only from one season to the next but that there are significant variations on monthly basis. It is because of this type of inconsistency in sales that the just in time inventory management approach works for the franchise. However, it is possible to improve the profitability of the franchise by making inventory adjustments by establishing more consistency to develop more predictable inventory needs. Interpreting the Deseasonalization patterns show that there are several months that are consistently high—months four, five, six, ten and eleven—and there are other months that are consistently low. The months with the lowest inventory and sales are months seven, eight and twelve. Understanding these patterns are critical to making informed decisions in the establishment of a new inventory plan.

Figure 6
Conclusion
Making the decision to restructure the inventory system for a McDonald’s franchise is no small undertaking. Rather than launching an entirely new system, McDonald’s franchises would be better served by making adjustments within the inventory by effectively capturing and leveraging the historical inventory data that is available. The data provided in this report suggests that in the months when sales are lowest that this is very likely due to lower inventory. By making adjustments upwards but staying within the confines of a just in time inventory system the franchise is able to better meet the customers’ demands for products, and minimize loss of perishable products. The goal for the franchise then is to implement changes that are within the limits of franchisee operational agreements, but respond to the immediate local needs of customers.

Reference
Atkinson, C. (2005, November 8). McDonald's: A Guide to the Benefits of Just In Time . Retrieved February 18 , 2012, from Inventory Management Review : http://www.inventorymanagementreview.org/justintime/
Said, I. (2012, January 19). FohBoh: The Restaurant Network. Retrieved March 5, 2012, from www.fohboh.com: http://fohboh.com/profiles/blogs/importance-of-inventory-management-for-restaurant-profitability

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