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Sport obermeyer

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Case analysis of the famous sport obermeyer SCM issue

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Sport obermeyer

  1. 1. SPORT OBERMEYER Pratap Singh Khangarot Anand S. Thokal 1
  2. 2. SPORT OBERMEYER’S TIME LINE AND “SPECULATIVE” VERSUS “REACTIVE” PRODUCTION 2 Feb … Oct Nov … Mar April … Aug Sept Oct Nov Dec Jan Feb Mar Apr 1992 … 1992 1992 … 1993 1993 … 1993 1993 1993 1993 1993 1994 1994 1994 1994 Line. of 1993-94 Line 8 months Production of 1993-94 Line (peak selling in Dec & Jan) "Reactive" Production 5 months9 months 5 months "NOW" Initial Forecast In Feb 1994, start design of 1995-96 line. Selling of In Feb 1993, start design of 1994-95 line. Las Vegas Revised Forecast 27 Months 1993-94 Line Design of 1993-94 "Speculative" “Speculative” Production “Reactive” Production
  3. 3. SPECULATIVE PRODUCTION: OVERSTOCK VERSUS STOCKOUT? 3 Assume that Sport Obermeyer: is in the Speculative Production phase, forecasts that demand (D) for the Andy parka has a Normal Probability Distribution with a mean of 1000 and a standard deviation of 250, and has decided that the Andy parka’s Speculative Production should be Q=750. During the Speculative Production, Sport Obermeyer should be more concerned about 750 Q Pr{Overstock}=Pr{D<Q} =0.159 Pr{Stockout}=Pr{D>Q} =0.841
  4. 4. SPECULATIVE PRODUCTION: GUIDELINES FOR CHOOSING A PARKA TO PRODUCE 4 In this slide and the next 4 slides, we will assume that Sport Obermeyer is in the Speculative Production phase and must decide whether to produce the Andy parka or the Peter parka. We will also assume that a parka’s demand has a Normal Probability Distribution. We will investigate how this decision is affected by: the parka’s standard deviation of demand, the parka’s mean demand, and the parka’s unit cost of production.
  5. 5. THE EFFECT OF A PARKA’S STANDARD DEVIATION OF DEMAND 5 Assume that Andy and Peter have the same unit cost of production and the same mean demand of 1000, but that Andy’s demand has a standard deviation of 100 while Peter’s demand has a standard deviation of 200. During Speculative Production, Q Pr{Overstock}=Pr{D<Q} = Area to Left of Q
  6. 6. THE EFFECT OF A PARKA’S MEAN DEMAND 6 Assume that Andy and Peter have the same unit cost of production and the same standard deviation for demand of 200, but that Andy’s demand has a mean of 1000 while Peter’s demand has a mean of 1200. During Speculative Production, Pr{Overstock}=Pr{D<Q} = Area to Left of Q Q
  7. 7. THE EFFECT OF A PARKA’S UNIT COST OF PRODUCTION 7 Assume that Andy and Peter have the same mean demand of 1000 and the same standard deviation for demand of 1000, but that Andy’s demand has unit cost of production of $10 while Peter’s demand has a unit cost of production of $20. During Speculative Production,
  8. 8. SPECULATIVE PRODUCTION: SUMMARY OF GUIDELINES FOR CHOOSING A PARKA TO PRODUCE 8 In the previous 3 slides, we have seen that a parka is a better candidate for Speculative Production if: It has a relatively ______ standard deviation of demand. It has relatively ______ mean demand. It has a relatively ______ unit cost of production. Low High Low
  9. 9. EQUALIZING OVER 2 PARKAS THE PROBABILITY OF AN OVERSTOCK 9 Assume that Andy and Peter have the same unit cost of production but that Andy’s demand has a mean of 1000 & standard deviation of 250, Peter’s demand has a mean of 2500 & standard deviation of 500. QUESTION: How can we set the production quantities so that Pr{Overstock of Andy} = Pr{Overstock for Peter}? Q=2500 – k500Q=1000 - k250
  10. 10. SOLVING WALLY’S SAMPLE PROBLEM (ON PAGE 8 OF THE CASE) 10 Using the concept on the previous slide and the sample data in Exhibit 10, we will determine for Wally the order quantity for each style during Speculative Production. To simplify, we will assume that: all 10 styles in the sample problem are made in Hong Kong, no style has a minimum order quantity, all styles have the same unit cost of production, and total Speculative Production must be about 10,000 units.
  11. 11. SOLVING WALLY’S SAMPLE PROBLEM (WITH K=0) 11 Too much! DETERMINING SPECULATIVE PRODUCTION QUANTITIES k = 0 <---Find value of k that makes last column sum to about 10,000 STANDARD FIRST-PERIOD MEAN OF DEVIATION PRODUCTION QUANTITY DEMAND OF DEMAND STYLE Gail 1017 388 1017 Isis 1042 646 1042 Entice 1358 496 1358 Assault 2525 680 2525 Teri 1100 762 1100 Electra 2150 807 2150 Stephanie 1113 1048 1113 Seduced 4017 1113 4017 Anita 3296 2094 3296 Daphne 2383 1394 2383 Sum---> 20,001 20,001 <---Sum µ σ ),0( σµ kMax −
  12. 12. SOLVING WALLY’S SAMPLE PROBLEM (WITH K=2) 12 DETERMINING SPECULATIVE PRODUCTION QUANTITIES k = 2 <---Find value of k that makes last column sum to about 10,000 STANDARD FIRST-PERIOD MEAN OF DEVIATION PRODUCTION QUANTITY DEMAND OF DEMAND STYLE Gail 1017 388 241 Isis 1042 646 0 Entice 1358 496 366 Assault 2525 680 1165 Teri 1100 762 0 Electra 2150 807 536 Stephanie 1113 1048 0 Seduced 4017 1113 1791 Anita 3296 2094 0 Daphne 2383 1394 0 Sum---> 20,001 4,099 <---Sum µ σ ),0( σµ kMax − Too little!
  13. 13. SOLVING WALLY’S SAMPLE PROBLEM (WITH K=1) 13 DETERMINING SPECULATIVE PRODUCTION QUANTITIES k = 1 <---Find value of k that makes last column sum to about 10,000 STANDARD FIRST-PERIOD MEAN OF DEVIATION PRODUCTION QUANTITY DEMAND OF DEMAND STYLE Gail 1017 388 629 Isis 1042 646 396 Entice 1358 496 862 Assault 2525 680 1845 Teri 1100 762 338 Electra 2150 807 1343 Stephanie 1113 1048 65 Seduced 4017 1113 2904 Anita 3296 2094 1202 Daphne 2383 1394 989 Sum---> 20,001 10,573 <---Sum µ σ ),0( σµ kMax − Too much!
  14. 14. SOLVING WALLY’S SAMPLE PROBLEM (WITH K=1.0608) 14 DETERMINING SPECULATIVE PRODUCTION QUANTITIES k = 1.0608 <---Find value of k that makes last column sum to about 10,000 STANDARD FIRST-PERIOD MEAN OF DEVIATION PRODUCTION QUANTITY DEMAND OF DEMAND STYLE Gail 1017 388 605 Isis 1042 646 357 Entice 1358 496 832 Assault 2525 680 1804 Teri 1100 762 292 Electra 2150 807 1294 Stephanie 1113 1048 1 Seduced 4017 1113 2836 Anita 3296 2094 1075 Daphne 2383 1394 904 Sum---> 20,001 10,000 <---Sum µ σ ),0( σµ kMax − Just right!
  15. 15. THE EFFECT OF MINIMUM ORDER QUANTITIES 15 Ideally, during Speculative Production, we want to order a specific quantity of a parka style, and then, during Reactive Production, we want to “fine tune” the parka’s remaining supply by ordering as few or as many as the indicated by the revised forecast after Las Vegas. However, a large minimum order quantity for a particular style of parka forces us to order either many parkas or none. Thus, a minimum order quantity significantly reduces the ability to “fine tune” during Reactive Production.
  16. 16. MINIMUM ORDER QUANTITIES (CONTINUED) 16 Let “Mean” denote a parka’s mean demand. Let “minQ” denote the parka’s minimum order quantity. Consider the following three cases: 0 <= Mean <= minQ <= Mean <= 2minQ <= Mean Case 1 Case 2 Case 3 During Speculative Production, which of the above three cases are “safe” to order, and which are “risky”? Case 1: Case 2: Case 3:
  17. 17. RECOMMENDATIONS TO WALLY 17 RECOMMENDATION #1. Improve the demand forecasts made internally by the Buying Committee in November just before Speculative Production. Instead of using just a simple average of the individual forecasts made by Laura, Carolyn, Greg, Wendy, Tom, & Wally, use a weighted average, with the weights reflecting past accuracy.
  18. 18. RECOMMENDATIONS TO WALLY (CONTINUED) 18 RECOMMENDATION #2. Obtain market feedback earlier than Las Vegas, thereby converting some Speculative Production to Reactive Production. Sport Obermeyer can invite selected retailers to come in January to Aspen for an all-expenses-paid “Early Order Weekend”, where there is time for a”sneak preview” of the new line, some recreational skiing and socializing, and then the early placement of orders at a discount. To maximize the value of the market feedback, Sport Obermeyer’s “guest list” should include both large and small retailers and both urban and resort retailers.
  19. 19. RECOMMENDATIONS TO WALLY (CONTINUED) 19 RECOMMENDATION #3. Decrease lead times for both raw materials and finished goods, thereby allowing more time to utilize existing capacity. Since the business strategy should emphasize Dependability more than Cost, lead-times can be reduced using some or all of the following methods: Choose suppliers of raw materials more on the basis of D than C. Expedite orders through information sharing with suppliers. Expedite shipments using faster (but more expensive) shippers. Establish some local (but more expensive) production capacity for “last minute” production.
  20. 20. RECOMMENDATIONS TO WALLY (CONTINUED) 20 RECOMMENDATION #3 (continued). Other ways to reduce lead times include: From the items with long lead times, increase the amount of “safety stock” inventory for those items that are inexpensive (e.g., buttons) and/or shared by many parkas (e.g., black fabric). Simplify the parkas’ designs so that they can share as many components as possible. For example, are 100,000 varieties of zippers really necessary?
  21. 21. RECOMMENDATIONS TO WALLY (CONTINUED) 21 RECOMMENDATION #4. Increase production capacity by: Using more subcontractors, Using more overtime in China, and/or Exploring an alliance with a swimwear manufacturer who can “supply” excess capacity when Sport Obermeyer needs it and “consume” capacity when Sport Obermeyer has excess capacity.
  22. 22. RECOMMENDATIONS TO WALLY (CONTINUED) 22 RECOMMENDATION #5. Decrease minimum order quantities, thereby improving the ability to “fine tune” during Reactive Production. Minimum order quantities occur because there are long “set-up times” when switching from the production of one style of parka to another, thereby making it uneconomical to have “short runs”. Sport Obermeyer can decrease the minimum order quantities by providing incentives to its suppliers to have more flexible production lines. This increased flexibility can come from: Improved process design (e.g., a cellular production system). Improved equipment (e.g., more flexible cutting machines).
  23. 23. SPORT OBERMEYER’S RELATIONSHIP WITH OBERSPORT 23 In this global supply chain, Sport Obermeyer operates in the US and specializes in the demand side by coordinating activities such as monitoring fashion trends, designing the parkas, and selling the parkas by entering into relationships with retailers. Obersport operates in Hong Kong and China and specializes in the supply side by coordinating activities such as procuring fabric and components (e.g., zippers) and arranging for production using either independent subcontractors or factories of Alpine (a company owned by Obersport’s managing director).
  24. 24. SPORT OBERMEYER’S RELATIONSHIP WITH OBERSPORT (CONTINUED) 24 Global supply chains are frequently composed of different companies, with each company having a a different geographical location, a different knowledge set a different skill set, and/or a different set of business relationships. Sport Obermeyer should NOT eliminate its business relationship with Obersport. Instead, it should retain its relationship and seek to improve the coordination between Sport Obermeyer’s demand-side activities and Obersport’s supply-side activities.
  25. 25. THANK YOU 25

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