Parts Emporium Synopsis Essay Example For Students

Parts Emporium Synopsis Essay This case describes the problems facing Sue Mackey, the new materials manager of a wholesale distributor of auto parts. She seeks ways to cut the bloated inventories while improving customer service. Backorder with excessive lost sales are all too frequent. Inventories were much higher than expected when the new facility was built, even though sales have not increased. Summary data on inventory statistics, such as inventory turns, are not available. Mackey decides to begin With a sample Of two products to uncover the nature Of the problems?the EGGS exhaust gasket and the DEBBY drive belt. B. Purpose The purpose of this case is to allow the student to put together a plan, using either a continuous review system (Q system) or a periodic review system (P system), for two inventory items. Enough information is available to determine the EX. and R for a continuous review system (or P and T for a periodic review system). Because cookouts are costly relative to inventory holding costs, a 95 percent cycle-service level is recommended. Inventory holding costs are 21 percent of the value tot each item (expressed at cost). The ordering costs ($20 for exhaust gaskets and for drive belts) should not be increased to include hares for making customer deliveries. These charges are independent of the inventory replenishment at the warehouse and are reflected in the pricing policy. C. Analysis We now find appropriate policies for a Q system, beginning With the exhaust gasket. Shown here are the calculations of the EX. and R, followed by a cost comparison between this continuous review system and the one now being used. The difference is what can be realized by a better inventory control system. Reducing lost sales due to backorder is surely the biggest benefit. I. EGGS Exhaust Gasket a. New plan Begin by estimating annual demand and the arability in the demand during the lead time for this first item. Working with the weekly demands for the first 21 weeks of 1994 and assuming 52 business weeks per year, we find the EX. as follows: Weekly demand average 102 gaskets/week Annual demand (D) = 102(52) = 5304 gaskets Holding cost = SSL . 85 per gasket per year (or 0. 21 0. 68. $12. 99) ordering cost $20 per order EX. SSL . 5 = 339 gaskets Turning to R, the Normal Distribution appendix shows that a 95 percent cycle-service level corresponds to a z 1. 645. We then find Standard deviation in weekly demand (tot) = 2. 6 gaskets, Where t = 10 Standard deviation in demand during lead time (LO) 2. 86 R Average demand during the lead time 4 Safety stock = 2(102) I = 210. 6, or 211 gaskets *This case was prepared by Dry. Rob Bergman, University of Houston, as a basis for classroom dis cussion. CNN-108 Chapter 13: Parts Emporium b. Cost comparison After developing their plan, students can compare its annual cost with what would be experienced with current policies. Cost Category Current Plan Proposed Plan Ordering cost $707 $313 133 314 Holding cost (cycle inventory) TOTAL $846 $627 The total of these two costs for the gasket is reduced y 26 percent (from SASS to $627) per year, The safety stock with the proposed plan may be higher than the current plan, if the reason for the excess backorder is that no safety stock is now being held (inaccurate inventory records or a faulty replenishment system are other explanations). The extra cost this safety stock is minimal, however. Only 4 gaskets are being held as safety stock, and their annual holding cost is just another $1. 5(4) = $7. 40 Surely the lost sales due to backorder is substantial with the current plan and will be much less with the proposed plan. One symptom of such losses is that 1 1 units are on backorder n week 21, A lost sale costs a minimum of $4. 16 per gasket (0. 32. 512_99)_ If 10 percent of annual sales were lost with the current policy, this cost would be $416(0. = 52,206 per yea r. Such a loss would be much reduced with the 95 percent cycle-service level implemented with the proposed plan. 2. 08032 Drive Belt a. Nevi plan The following demand estimates are based on weeks 13 through 21.