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Case study sport obermeyer

Sport Obermeyer is a high-end skiwear company that produces around 800 stock keeping units each year through a global supply chain. It works with a joint venture partner Obersport in Hong Kong and China to source materials and manufacture products. Sport Obermeyer is looking for ways to improve its forecasting accuracy and production flexibility to better meet demand. Some options it is considering include adjusting production allocation between Hong Kong and China factories and revising minimum order quantities.

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Prepared by: Shaheen Sardar SCM Lab. Department of Industrial and Management Engineering, Hanyang University, South Korea. Case Study: Sport Obermeyer
Company History: “Skiing is a celebration of life” Klaus Obermeyer 1947: Klaus Obermeyer, a German immigrant began teaching at the Aspen (U.S.) Ski School
Company History: 1985: Obersport; a joint venture in Hong Kong, the company began to increase productivity to meet their new demands.
Women’s Collection
Competitors The Jacobs Corporation founded by David L. Jacobs Biography
Competitors The North Face, Inc. : subsidiary of VF Corporation
Competitors Burton Snowboards founded by Jake Burton Carpenter Innovative Burton outerwear performance meets leading Motorola Bluetooth ® technology
Sport Obermeyer • Sport Obermeyer – a high end fashion skiwear designer and merchandising company • Commitment for producing line of fashion skiwear for 1993-94 Long lead times:  Long lead times: It’s November 1992 and the company is starting to make firm commitments for its 1993 – 1994 season.  Based on experience, Intuition and sheer speculation  No feedback from retailers (Las Vegas trade show in March 1993)  Inaccurate forecasts of retailer demand • Company’s inability to predict correctly (which product would become best seller) resulted in:  Excess merchandise and sold at deep discount  Or company ran out of most popular items (lost sales)
Problem Statement • How can Sport Obermeryer Ltd.:  Improve its forecasting method  Achieve a more dynamic manufacturing capability in order to reduce final inventory  Increase profits  Become more competitive in the industry
Manufacturing Structure: Sport Obermeyer Ltd. Obersport Ltd. Alpine Ltd • Hong Kong • Macau • China Lo Village Other subcontractors
COMPANY NETWORK: Recently, a number of contractual ventures were added and a new complex in Lo Village Guangdong China
Product and Segmentation:
Product Variety:
Obermeyer Product Fashion Ski Apparel • Parkas, Vests, Sweater, ski suits, shells, ski pants, turtlenecks and accessories • Parkas : Most critical design • Products offered in five different genders (Men, Women, Boys, Girls, Preschoolers) • Company segmented each gender market according to price, type of skier and fashion forwardness. • U.S. Skiwear estimated sales in 1992: US$ 32.8 million • Obermeyer’s Share: • 45% of children skiwear mkt. • 11% of adult skiwear mkt. • Offering an excellent price/ value relationship to target group
Obermeyer Product • Example (Adult man) – Fred (conservative, basic) – Rex (rich, latest fabrics and technologies) – Beige (mountaineering type skier, high technical performance) – Klausie (showy, latest fashions) • Each Gender – Styles – Colors – Sizes • Total Number of SKU’s (stock-keeping units): ~800 • Deliver matching collections simultaneously • Deliver early in the season
The Supply Chain (Asia to Aspen (U.S.)) • Obermeyer sourced most of its products through Obersport • Obermeyer would contract with fabric supplier for specified amount of fabric each month • Lead time taken into account for all materials • Most tasks performed only after production quantity planned by Obermeyer • Obersport: Joint venture between Sport Obermeyer and its Hong Kong partner. • Obersport is responsible for fabric and component sourcing for apparel production and monitoring product quality at subcontractor factories. Textile and Accessories Suppliers Apparel Manufactures Obersport Retailers
The Supply Chain Textile and Accessories Suppliers Apparel Manufacturers Sport Obermeyer Retailers Obersport Produce, dye and print shell and lining fabrics, supply insulation, zippers, thread, logo patches and snaps. Subcontractors, receive production orders and materials from Obersport. Cut, sew and final assembly. Responsible for material and production sourcing in the Far East. It also acts as a distribution centre for materials and finished goods. Product design, production planning and sales. Purchase from Sport Obermeyer and sell products to consumers.
Product Transportation Hong Kong Warehouse Seattle Obermeyer’s Denver Warehouse then transported by trucks goods produced in August were air-shipped Retailers orders were finally shipped via small-package carriers such as UPS (United Parcel Service) at the end of August 1993 Cost $5 per parka products made in June and July were transported by ships
Retailers Specialty Ski- Retail Stores Department Stores Direct Mail Retailers Consumers Most sales occur between September and January Delivering products by early September Sport Obermeyer
Production Options • Hong Kong – More expensive – Smaller lot sizes – Faster – More flexible • Mainland (Guangdong, Lo Village) – Cheaper – Larger lot sizes – Slower – Less flexible
Obersport Limited Obersport Ltd • To coordinate production of sport obermeyer’s products in Far East • Responsible for fabric and component sourcing Joint Venture formed in 1985 by • Klaus Obermeyer’s Son – Wally (Harvard Educated) • Raymond Tse – Owner of Alpine- 80% order of Sport obermeyer • Klaus entrusts Raymond Tse to make all decisions regarding production and investment
Design Process Las Vegas Concept Sketches sent Designs begins Show Finalise to Obersport Finalised Feb 92 Mar 92 May 92 Jul 92 Sep 92 Nov 92 Mar 93 Apr 93 - Jul 93 Dec 93-Feb 94 Place 1st Production Las Vegas Additional Replenishment Order with Obersport Show orders received orders received Prototype, Sample Production Full scale production Planning and Production Cycle:
The Effect of Minimum Order Quantities • 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.
Sport Obermeyer’s Time Line and “Speculative” versus “Reactive” Production 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
Components Greige Shell Fabric Finishing of Shell Fabric (Dying & Printing) Finished Lining Fabric Insulation Zippers Thread Logo Patches, Drawcords, Hang Tags, etc. Snaps (undyed) Dyeing of Snaps Procurement lead time 45 – 90 days 45 – 60 days 45 – 60 days 2 – 3 weeks Standard (HK) 60 days, Custom (JP) 90+ days 30 days 15 – 30 days 1 – 2 months 15 – 30 days Asia 6 weeks Fabric Producer Fabric Dyer Cut/Sew Factory Denver Warehouse Retailer Un-dyed greige goods Consumer6 weeks 6 weeks Production Process:
Factories in Hong Kong Seattle warehouse 800 Ski RetailersProduct Sketches Forecast Committee Forecasts Order 20% in Apr-Jun 93 Order 80% in Mar 93 Retailers order in Apr-Jun 93 Denver warehouse 6 weeks Ordering and Shipment Process:
Sales and Replenishing Process: Peak Sales Aug 93 Sep 93 Oct 93 Nov 93 Dec 93 Feb 94 Sales Re-Sales Stock outs (+24 % of whole sale price) Market downs (-8% of wholesale price)
Parkas • Obermeyer produce 200,000 parkas every year • Capacity: 3,60,000 each year • Earn 24% of wholesale price on each • Unsold in season: sold at a loss of 8% • Profit of US$ 27 and loss of US$9 on each parkas • Buying committee forecasts for 10 style of Parkas
Issue faced by Wally • How to make best use of forecasts by various members for production commitment • How to allocate production between factories at Hong Kong and China • Last year 1/3rd Parkas was made in China. • Company plan to produce 50% parkas in China as  labor cost in China is low  require larger minimum order  some concern of quality and reliability is there
Obermeyer Landed Cost: Cost FOB Obersport $42.68 Agent’s fee (to Obersport, 7%) $2.98 Freight (Ocean Carrier) $1.40 Duty, insurance and miscellaneous $4.90 Total landed cost $51.92 Cost FOB Obersport: Material $30.00 Labour $0.78 Transportation within China and China overhead $2.00 China quota, obersport profit and overhead $9.90 Total $42.68 ESTIMATED COST INFORMATION FOR ROCOCO PARKA (IF ASSEMBLED IN CHINA)
Parkas • Wally studied the committee forecasts • Estimated the early production of each style • Demand and forecasts for last year analyzed • Standard deviation of demand was twice the standard deviation of buying committee forecasts • Forecast distribution for each style as a normal random variable With mean equal to average of committee forecasts Standard deviation twice of committee forecasts
COMMITTEE FORECAST- 10 STYLES OF WOMEN’S PARKA – Individual Forecast Style Price Laura Carolyn Greg Wendy Tom Wally Gail $110 900 1,000 900 1,300 800 1,200 Isis $99 800 700 1,000 1,600 950 1,200 Entice $80 1,200 1,600 1,500 1,550 950 1,350 Assault $90 2,500 1,900 2,700 2,450 2,800 2,800 Teri $123 800 900 1,000 1,100 950 1,850 Electra $173 2,500 1,900 1,900 2,800 1,800 2,000 Stephanie $133 600 900 1,000 1,100 950 2,125 Seduced $73 4,600 4,300 3,900 4,000 4,300 3,000 Anita $93 4,400 3,300 3,500 1,500 4,200 2,875 Daphne $148 1,700 3,500 2,600 2,600 2,300 1,600 Totals 20,000 20,000 20,000 20,000 20,000 20,000
COMMITTEE FORECAST- 10 STYLES OF WOMEN’S PARKA – Individual Forecast Style Average Forecast Standard deviation 2 x Standard Deviation Gail 1,017 194 388 Isis 1,042 323 646 Entice 1,358 248 496 Assault 2,525 340 680 Teri 1,100 381 762 Electra 2,150 404 807 Stephanie 1,113 524 1,048 Seduced 4,017 556 1,113 Anita 3,296 1,047 2,094 Daphne 2,383 697 1,349 Totals 20,000
Parkas • Wally also had to decide the location for production for each style ( Hong Kong or China) • It was planned this year to produce 50% of products in China • There was risk of managing production and inventory in longer term • The larger minimum order size of China limits the capacity of company’s ability to increase the range of products • China trade relationship with USA - Risky
Topic Hong Kong China Hourly wage HK$30 RMB 0.91 Exchange rate HK$7.8 = US$1 RMB (Renminbi) 5.7 = US$1 Working hours 8 hours/day, 6 days/week 9 hours/day, 6.5 days/week Total = 48 hours/week Total = 58.5 hours/week Maximum overtime allowed = 200 hours/years During peak production periods, workers work 13 hours/day, 6.5 days/week Weekly (non-peak output/worker) 19 parkas 12 parkas COMPARISON OF OPERATIONS IN HONG KONG AND CHINA
Topic Hong Kong China Actual labour content per parka (incl repair work) -2.35 hours -3.6 hours Paid labour time per parka (incl repair work) -2.53 hours/parka -4.88 hours/parka Labour cost /garment HK$75.6 RMB 4.45 Line configuration 10-12 people/line 40 people/line Training Cross-trained Trained for single operation only Min order quantity 600 units in same style 1200 units in same style Repair rate 1-2% -10% Challenges Wage rate, Workforce Low unemployment Younger worker prefer office job Workforce Less quality and cleanliness conscious Training requirements COMPARISON OF OPERATIONS IN HONG KONG AND CHINA
Sport Obermeyer’s Relationship with Obersport • 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).
Sport Obermeyer’s Relationship with Obersport (Continued) • 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.
SWOT Analysis Strengths: • History of product innovation • Buying committee forecasts balance expectations • Experienced leadership and focused management team • Deliver products to retailers early in the selling season • Variety of SKUs, with color/size product diversity • Use of greige fabric delays product differentiation Weaknesses: • Excessively long lead times, though this is the nature of the industry • Minimum order quantity at Chinese manufacturers • Leftover unpopular merchandise at end of selling period. • Stock outs on most popular items during peak selling Opportunities: • Aggressive marketing campaign • Expanding sales to European/ South American markets • Sponsorship of major winter sports events Threats: • Competition from value- oriented sellers like Columbia. • Regulatory limits of goods that can be imported into US.
Case Discussion Questions 1. Using the sample data given in Table 2-20, make a recommendation for how many units of each style Wally should make during the initial phase of production. Assume that all of the 10 styles in the sample problem are made in Hong Kong and that Wally’s initial production commitment must be at least 10,000 units. Ignore price differences among styles in your initial analysis. 2. Can you come up with a measure of risk associated with your ordering policy? This measure should be quantifiable.
Case Discussion Questions 3. Repeat your methodology and assume now that all 10 styles are made in China. What is the difference (if any) between the two initial production commitments? 4. What operational changes would you recommend to Wally to improve performance? 5. How should Wally think (both short-term and long-term) about sourcing in Hong Kong versus China? What kind of sourcing policy do you recommend?
Solving Wally’s Sample Problem (with k=0) 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   ),0(  kMax 
Solving Wally’s Sample Problem (with k=2) 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   ),0(  kMax  Too little!
Solving Wally’s Sample Problem (with k=1) 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   ),0(  kMax  Too much!
Solving Wally’s Sample Problem (with k=1.0608) 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   ),0(  kMax  Just right!
Question 1. and 3. Comparison units of each style when produced in HK and China
Differences between production in HK and China • Inventory • Total Cost • Operation Time • Quality (% Repair)
Question 1. and 3. The differences between production in HK and China
Question 1 (Alternative approach) • We have three types of products: -Low risk: risk % between 0 and 40 -Medium risk: risk % between 41 and 59 -High risk: risk % above 60 • To minimize the risk, we decided to order the following quantity: -Low risk items: 75% of the average forecast -Medium risk items: 50% of the average forecast -High risk items: 25% of the average forecast
Question 1 (Alternative approach)
2. Can you come up a measure of risk associated with an your ordering policy? This measure should be quantifiable.
-Stock outs (-24 % whole sale price) -Market downs( -8% of wholesale price) -(Old) designs -High inventory holding cost -Unable to fully profit from hit products What’s the result if there is demand forecasting uncertainty?
Forecasts are always uncertain Why does risk happen? Demand Average Standard deviation Standard deviation
How we assess forecast certainty? 1 . Based on historical data - Past forecast error - Variability of demand
2. Rather than producing one joint forecast, each member of the purchasing committee produces his/her own forecast . Obermeyer’s Buying committee
3. The deviation in views (of Buying committee) is good estimator of forecast reliability Table of standard deviation vs. Coefficient of variation C.V. = Standard Deviation / Mean
4. How is this information helpful? - Using Early production Capacity (Speculative capacity) for Assault and Seduced - Reserve later production Capacity (reactive capacity) for Daphne and Anita as demand become more apparent “Risk –based production planning”
4. What operational changes would you recommend to Wally to improve performance?
• Ski Clothes is fashionable product, Its life cycle is short • Long time of planning and production activities • Uncertain forecasting due to customer demand • Fashion taker >> No R&D KEY Problems:
• Reducing number of styles handled and to predict customer demand for individual style. • To create promotion strategy to persuade retailers to order. OPERATIONAL Changes:
PRODUCTION SYSTEM •Increasing production Quality of China to be closed to Hong Kong. • To reduce lead time of production especially the preparation of raw materials. OPERATIONAL Changes:
Lead time reduction • Fabric dyer lead time of several months • Dyer has long lead time on greige goods and needed to keep their capacity utilized year round but can change colors overnight • Obermeyer can predict total annual sales and sales of basic colors, but can’t predict fashion colors Fabric Producer Fabric Dyer Cut/Sew Factory Denver Warehouse Retailer undyed greige goods Sport Obermeyer Asia Consumer
Solution: • Offer dyer one year commitment on greige goods and capacity • Dye basic colors early in year and fashion colors late in season on few days notice
SUPPLY CHAIN SYSTEM • Increase bargaining power with suppliers by ordering via big supplier that can commit on timeline • Collect stock raw materials which is base on Ski cloth production OPERATIONAL Changes:
•Increase distribution channel to a country that have different period of product usage •Increase services level requirements •Establish DC in Seattle to reduce lead time and cost from inland transportation from Seattle to Denver OPERATIONAL Changes:
Hong Kong Seattle Original distribution process Establish Distribution Center in Seattle without through Denver
INFORMATION SYSTEM • Collect the data backward and analyze the demand of the show in Vegas and compare with actual purchase. • Speedup data/information analysis and utilize historical data / Committee forecasting / Research and Trend & Market Movement. OPERATIONAL Changes:
5. How should Wally think (both short term and long term) about sourcing in Hong Kong versus China? What kind of sourcing policy do you recommend?
Production Options • Hong Kong – Faster – More flexible – High / Reliable Quality – Better for higher risk designs • Concern – Smaller lot sizes – Higher labor cost • China (Guangdong, Lo Village) – Lower labor cost – Larger lot sizes – Better for lower risk designs • Concern – Quality & Reliability – Slower – Less flexible
Where is better? Short term Long term Hong Kong China
Recommendations to Wally RECOMMENDATION #1. Improve the demand forecasts made internally by the Buying Committee in November (1992) just before Speculative Production. Instead of using just a simple average of the individual forecasts made by Laura, Carolyn, Greg, Wendy, Tom and Wally use a weighted average, with the weights reflecting past accuracy.
Recommendations to Wally (continued) 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.
Recommendations to Wally (continued) 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. •Speed up orders through information sharing with suppliers. •Speed up shipments using faster (but more expensive) shippers. •Establish some local (but more expensive) production capacity for “last minute” production.
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? Recommendations to Wally (continued)
Recommendations to Wally (continued) 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.
Recommendations to Wally (continued) 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”.
Recommendations to Wally (continued) 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). RECOMMENDATION #5 (continued)
Thank You

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Case study sport obermeyer

  • 1.
    Prepared by: ShaheenSardar SCM Lab. Department of Industrial and Management Engineering, Hanyang University, South Korea. Case Study: Sport Obermeyer
  • 2.
    Company History: “Skiing isa celebration of life” Klaus Obermeyer 1947: Klaus Obermeyer, a German immigrant began teaching at the Aspen (U.S.) Ski School
  • 3.
    Company History: 1985: Obersport;a joint venture in Hong Kong, the company began to increase productivity to meet their new demands.
  • 4.
  • 6.
    Competitors The Jacobs Corporation foundedby David L. Jacobs Biography
  • 7.
    Competitors The North Face,Inc. : subsidiary of VF Corporation
  • 8.
    Competitors Burton Snowboards founded byJake Burton Carpenter Innovative Burton outerwear performance meets leading Motorola Bluetooth ® technology
  • 9.
    Sport Obermeyer • SportObermeyer – a high end fashion skiwear designer and merchandising company • Commitment for producing line of fashion skiwear for 1993-94 Long lead times:  Long lead times: It’s November 1992 and the company is starting to make firm commitments for its 1993 – 1994 season.  Based on experience, Intuition and sheer speculation  No feedback from retailers (Las Vegas trade show in March 1993)  Inaccurate forecasts of retailer demand • Company’s inability to predict correctly (which product would become best seller) resulted in:  Excess merchandise and sold at deep discount  Or company ran out of most popular items (lost sales)
  • 10.
    Problem Statement • Howcan Sport Obermeryer Ltd.:  Improve its forecasting method  Achieve a more dynamic manufacturing capability in order to reduce final inventory  Increase profits  Become more competitive in the industry
  • 11.
    Manufacturing Structure: Sport ObermeyerLtd. Obersport Ltd. Alpine Ltd • Hong Kong • Macau • China Lo Village Other subcontractors
  • 12.
    COMPANY NETWORK: Recently, a numberof contractual ventures were added and a new complex in Lo Village Guangdong China
  • 13.
  • 14.
  • 15.
    Obermeyer Product Fashion SkiApparel • Parkas, Vests, Sweater, ski suits, shells, ski pants, turtlenecks and accessories • Parkas : Most critical design • Products offered in five different genders (Men, Women, Boys, Girls, Preschoolers) • Company segmented each gender market according to price, type of skier and fashion forwardness. • U.S. Skiwear estimated sales in 1992: US$ 32.8 million • Obermeyer’s Share: • 45% of children skiwear mkt. • 11% of adult skiwear mkt. • Offering an excellent price/ value relationship to target group
  • 16.
    Obermeyer Product • Example(Adult man) – Fred (conservative, basic) – Rex (rich, latest fabrics and technologies) – Beige (mountaineering type skier, high technical performance) – Klausie (showy, latest fashions) • Each Gender – Styles – Colors – Sizes • Total Number of SKU’s (stock-keeping units): ~800 • Deliver matching collections simultaneously • Deliver early in the season
  • 17.
    The Supply Chain(Asia to Aspen (U.S.)) • Obermeyer sourced most of its products through Obersport • Obermeyer would contract with fabric supplier for specified amount of fabric each month • Lead time taken into account for all materials • Most tasks performed only after production quantity planned by Obermeyer • Obersport: Joint venture between Sport Obermeyer and its Hong Kong partner. • Obersport is responsible for fabric and component sourcing for apparel production and monitoring product quality at subcontractor factories. Textile and Accessories Suppliers Apparel Manufactures Obersport Retailers
  • 18.
    The Supply Chain Textileand Accessories Suppliers Apparel Manufacturers Sport Obermeyer Retailers Obersport Produce, dye and print shell and lining fabrics, supply insulation, zippers, thread, logo patches and snaps. Subcontractors, receive production orders and materials from Obersport. Cut, sew and final assembly. Responsible for material and production sourcing in the Far East. It also acts as a distribution centre for materials and finished goods. Product design, production planning and sales. Purchase from Sport Obermeyer and sell products to consumers.
  • 19.
    Product Transportation Hong Kong Warehouse Seattle Obermeyer’sDenver Warehouse then transported by trucks goods produced in August were air-shipped Retailers orders were finally shipped via small-package carriers such as UPS (United Parcel Service) at the end of August 1993 Cost $5 per parka products made in June and July were transported by ships
  • 20.
    Retailers Specialty Ski- Retail Stores Department Stores DirectMail Retailers Consumers Most sales occur between September and January Delivering products by early September Sport Obermeyer
  • 21.
    Production Options • HongKong – More expensive – Smaller lot sizes – Faster – More flexible • Mainland (Guangdong, Lo Village) – Cheaper – Larger lot sizes – Slower – Less flexible
  • 22.
    Obersport Limited Obersport Ltd •To coordinate production of sport obermeyer’s products in Far East • Responsible for fabric and component sourcing Joint Venture formed in 1985 by • Klaus Obermeyer’s Son – Wally (Harvard Educated) • Raymond Tse – Owner of Alpine- 80% order of Sport obermeyer • Klaus entrusts Raymond Tse to make all decisions regarding production and investment
  • 23.
    Design Process LasVegas Concept Sketches sent Designs begins Show Finalise to Obersport Finalised Feb 92 Mar 92 May 92 Jul 92 Sep 92 Nov 92 Mar 93 Apr 93 - Jul 93 Dec 93-Feb 94 Place 1st Production Las Vegas Additional Replenishment Order with Obersport Show orders received orders received Prototype, Sample Production Full scale production Planning and Production Cycle:
  • 24.
    The Effect ofMinimum Order Quantities • 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.
  • 25.
    Sport Obermeyer’s TimeLine and “Speculative” versus “Reactive” Production 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
  • 26.
    Components Greige Shell Fabric Finishingof Shell Fabric (Dying & Printing) Finished Lining Fabric Insulation Zippers Thread Logo Patches, Drawcords, Hang Tags, etc. Snaps (undyed) Dyeing of Snaps Procurement lead time 45 – 90 days 45 – 60 days 45 – 60 days 2 – 3 weeks Standard (HK) 60 days, Custom (JP) 90+ days 30 days 15 – 30 days 1 – 2 months 15 – 30 days Asia 6 weeks Fabric Producer Fabric Dyer Cut/Sew Factory Denver Warehouse Retailer Un-dyed greige goods Consumer6 weeks 6 weeks Production Process:
  • 27.
    Factories in Hong Kong Seattle warehouse 800Ski RetailersProduct Sketches Forecast Committee Forecasts Order 20% in Apr-Jun 93 Order 80% in Mar 93 Retailers order in Apr-Jun 93 Denver warehouse 6 weeks Ordering and Shipment Process:
  • 28.
    Sales and ReplenishingProcess: Peak Sales Aug 93 Sep 93 Oct 93 Nov 93 Dec 93 Feb 94 Sales Re-Sales Stock outs (+24 % of whole sale price) Market downs (-8% of wholesale price)
  • 29.
    Parkas • Obermeyer produce200,000 parkas every year • Capacity: 3,60,000 each year • Earn 24% of wholesale price on each • Unsold in season: sold at a loss of 8% • Profit of US$ 27 and loss of US$9 on each parkas • Buying committee forecasts for 10 style of Parkas
  • 30.
    Issue faced byWally • How to make best use of forecasts by various members for production commitment • How to allocate production between factories at Hong Kong and China • Last year 1/3rd Parkas was made in China. • Company plan to produce 50% parkas in China as  labor cost in China is low  require larger minimum order  some concern of quality and reliability is there
  • 31.
    Obermeyer Landed Cost: CostFOB Obersport $42.68 Agent’s fee (to Obersport, 7%) $2.98 Freight (Ocean Carrier) $1.40 Duty, insurance and miscellaneous $4.90 Total landed cost $51.92 Cost FOB Obersport: Material $30.00 Labour $0.78 Transportation within China and China overhead $2.00 China quota, obersport profit and overhead $9.90 Total $42.68 ESTIMATED COST INFORMATION FOR ROCOCO PARKA (IF ASSEMBLED IN CHINA)
  • 32.
    Parkas • Wally studiedthe committee forecasts • Estimated the early production of each style • Demand and forecasts for last year analyzed • Standard deviation of demand was twice the standard deviation of buying committee forecasts • Forecast distribution for each style as a normal random variable With mean equal to average of committee forecasts Standard deviation twice of committee forecasts
  • 33.
    COMMITTEE FORECAST- 10STYLES OF WOMEN’S PARKA – Individual Forecast Style Price Laura Carolyn Greg Wendy Tom Wally Gail $110 900 1,000 900 1,300 800 1,200 Isis $99 800 700 1,000 1,600 950 1,200 Entice $80 1,200 1,600 1,500 1,550 950 1,350 Assault $90 2,500 1,900 2,700 2,450 2,800 2,800 Teri $123 800 900 1,000 1,100 950 1,850 Electra $173 2,500 1,900 1,900 2,800 1,800 2,000 Stephanie $133 600 900 1,000 1,100 950 2,125 Seduced $73 4,600 4,300 3,900 4,000 4,300 3,000 Anita $93 4,400 3,300 3,500 1,500 4,200 2,875 Daphne $148 1,700 3,500 2,600 2,600 2,300 1,600 Totals 20,000 20,000 20,000 20,000 20,000 20,000
  • 34.
    COMMITTEE FORECAST- 10STYLES OF WOMEN’S PARKA – Individual Forecast Style Average Forecast Standard deviation 2 x Standard Deviation Gail 1,017 194 388 Isis 1,042 323 646 Entice 1,358 248 496 Assault 2,525 340 680 Teri 1,100 381 762 Electra 2,150 404 807 Stephanie 1,113 524 1,048 Seduced 4,017 556 1,113 Anita 3,296 1,047 2,094 Daphne 2,383 697 1,349 Totals 20,000
  • 35.
    Parkas • Wally alsohad to decide the location for production for each style ( Hong Kong or China) • It was planned this year to produce 50% of products in China • There was risk of managing production and inventory in longer term • The larger minimum order size of China limits the capacity of company’s ability to increase the range of products • China trade relationship with USA - Risky
  • 36.
    Topic Hong KongChina Hourly wage HK$30 RMB 0.91 Exchange rate HK$7.8 = US$1 RMB (Renminbi) 5.7 = US$1 Working hours 8 hours/day, 6 days/week 9 hours/day, 6.5 days/week Total = 48 hours/week Total = 58.5 hours/week Maximum overtime allowed = 200 hours/years During peak production periods, workers work 13 hours/day, 6.5 days/week Weekly (non-peak output/worker) 19 parkas 12 parkas COMPARISON OF OPERATIONS IN HONG KONG AND CHINA
  • 37.
    Topic Hong KongChina Actual labour content per parka (incl repair work) -2.35 hours -3.6 hours Paid labour time per parka (incl repair work) -2.53 hours/parka -4.88 hours/parka Labour cost /garment HK$75.6 RMB 4.45 Line configuration 10-12 people/line 40 people/line Training Cross-trained Trained for single operation only Min order quantity 600 units in same style 1200 units in same style Repair rate 1-2% -10% Challenges Wage rate, Workforce Low unemployment Younger worker prefer office job Workforce Less quality and cleanliness conscious Training requirements COMPARISON OF OPERATIONS IN HONG KONG AND CHINA
  • 38.
    Sport Obermeyer’s Relationshipwith Obersport • 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).
  • 39.
    Sport Obermeyer’s Relationshipwith Obersport (Continued) • 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.
  • 40.
    SWOT Analysis Strengths: • Historyof product innovation • Buying committee forecasts balance expectations • Experienced leadership and focused management team • Deliver products to retailers early in the selling season • Variety of SKUs, with color/size product diversity • Use of greige fabric delays product differentiation Weaknesses: • Excessively long lead times, though this is the nature of the industry • Minimum order quantity at Chinese manufacturers • Leftover unpopular merchandise at end of selling period. • Stock outs on most popular items during peak selling Opportunities: • Aggressive marketing campaign • Expanding sales to European/ South American markets • Sponsorship of major winter sports events Threats: • Competition from value- oriented sellers like Columbia. • Regulatory limits of goods that can be imported into US.
  • 41.
    Case Discussion Questions 1.Using the sample data given in Table 2-20, make a recommendation for how many units of each style Wally should make during the initial phase of production. Assume that all of the 10 styles in the sample problem are made in Hong Kong and that Wally’s initial production commitment must be at least 10,000 units. Ignore price differences among styles in your initial analysis. 2. Can you come up with a measure of risk associated with your ordering policy? This measure should be quantifiable.
  • 42.
    Case Discussion Questions 3.Repeat your methodology and assume now that all 10 styles are made in China. What is the difference (if any) between the two initial production commitments? 4. What operational changes would you recommend to Wally to improve performance? 5. How should Wally think (both short-term and long-term) about sourcing in Hong Kong versus China? What kind of sourcing policy do you recommend?
  • 43.
    Solving Wally’s SampleProblem (with k=0) 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   ),0(  kMax 
  • 44.
    Solving Wally’s SampleProblem (with k=2) 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   ),0(  kMax  Too little!
  • 45.
    Solving Wally’s SampleProblem (with k=1) 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   ),0(  kMax  Too much!
  • 46.
    Solving Wally’s SampleProblem (with k=1.0608) 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   ),0(  kMax  Just right!
  • 47.
    Question 1. and3. Comparison units of each style when produced in HK and China
  • 48.
    Differences between productionin HK and China • Inventory • Total Cost • Operation Time • Quality (% Repair)
  • 49.
    Question 1. and3. The differences between production in HK and China
  • 50.
    Question 1 (Alternativeapproach) • We have three types of products: -Low risk: risk % between 0 and 40 -Medium risk: risk % between 41 and 59 -High risk: risk % above 60 • To minimize the risk, we decided to order the following quantity: -Low risk items: 75% of the average forecast -Medium risk items: 50% of the average forecast -High risk items: 25% of the average forecast
  • 51.
  • 52.
    2. Can youcome up a measure of risk associated with an your ordering policy? This measure should be quantifiable.
  • 53.
    -Stock outs (-24% whole sale price) -Market downs( -8% of wholesale price) -(Old) designs -High inventory holding cost -Unable to fully profit from hit products What’s the result if there is demand forecasting uncertainty?
  • 54.
    Forecasts are alwaysuncertain Why does risk happen? Demand Average Standard deviation Standard deviation
  • 55.
    How we assess forecastcertainty? 1 . Based on historical data - Past forecast error - Variability of demand
  • 56.
    2. Rather thanproducing one joint forecast, each member of the purchasing committee produces his/her own forecast . Obermeyer’s Buying committee
  • 57.
    3. The deviationin views (of Buying committee) is good estimator of forecast reliability Table of standard deviation vs. Coefficient of variation C.V. = Standard Deviation / Mean
  • 58.
    4. How isthis information helpful? - Using Early production Capacity (Speculative capacity) for Assault and Seduced - Reserve later production Capacity (reactive capacity) for Daphne and Anita as demand become more apparent “Risk –based production planning”
  • 59.
    4. What operationalchanges would you recommend to Wally to improve performance?
  • 60.
    • Ski Clothesis fashionable product, Its life cycle is short • Long time of planning and production activities • Uncertain forecasting due to customer demand • Fashion taker >> No R&D KEY Problems:
  • 61.
    • Reducing numberof styles handled and to predict customer demand for individual style. • To create promotion strategy to persuade retailers to order. OPERATIONAL Changes:
  • 62.
    PRODUCTION SYSTEM •Increasing productionQuality of China to be closed to Hong Kong. • To reduce lead time of production especially the preparation of raw materials. OPERATIONAL Changes:
  • 63.
    Lead time reduction •Fabric dyer lead time of several months • Dyer has long lead time on greige goods and needed to keep their capacity utilized year round but can change colors overnight • Obermeyer can predict total annual sales and sales of basic colors, but can’t predict fashion colors Fabric Producer Fabric Dyer Cut/Sew Factory Denver Warehouse Retailer undyed greige goods Sport Obermeyer Asia Consumer
  • 64.
    Solution: • Offer dyerone year commitment on greige goods and capacity • Dye basic colors early in year and fashion colors late in season on few days notice
  • 65.
    SUPPLY CHAIN SYSTEM •Increase bargaining power with suppliers by ordering via big supplier that can commit on timeline • Collect stock raw materials which is base on Ski cloth production OPERATIONAL Changes:
  • 66.
    •Increase distribution channelto a country that have different period of product usage •Increase services level requirements •Establish DC in Seattle to reduce lead time and cost from inland transportation from Seattle to Denver OPERATIONAL Changes:
  • 67.
    Hong Kong Seattle Original distributionprocess Establish Distribution Center in Seattle without through Denver
  • 68.
    INFORMATION SYSTEM • Collectthe data backward and analyze the demand of the show in Vegas and compare with actual purchase. • Speedup data/information analysis and utilize historical data / Committee forecasting / Research and Trend & Market Movement. OPERATIONAL Changes:
  • 69.
    5. How shouldWally think (both short term and long term) about sourcing in Hong Kong versus China? What kind of sourcing policy do you recommend?
  • 70.
    Production Options • HongKong – Faster – More flexible – High / Reliable Quality – Better for higher risk designs • Concern – Smaller lot sizes – Higher labor cost • China (Guangdong, Lo Village) – Lower labor cost – Larger lot sizes – Better for lower risk designs • Concern – Quality & Reliability – Slower – Less flexible
  • 71.
    Where is better? Shortterm Long term Hong Kong China
  • 72.
    Recommendations to Wally RECOMMENDATION#1. Improve the demand forecasts made internally by the Buying Committee in November (1992) just before Speculative Production. Instead of using just a simple average of the individual forecasts made by Laura, Carolyn, Greg, Wendy, Tom and Wally use a weighted average, with the weights reflecting past accuracy.
  • 73.
    Recommendations to Wally (continued) 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.
  • 74.
    Recommendations to Wally (continued) 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. •Speed up orders through information sharing with suppliers. •Speed up shipments using faster (but more expensive) shippers. •Establish some local (but more expensive) production capacity for “last minute” production.
  • 75.
    RECOMMENDATION #3 (continued) Otherways 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? Recommendations to Wally (continued)
  • 76.
    Recommendations to Wally (continued) 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.
  • 77.
    Recommendations to Wally (continued) 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”.
  • 78.
    Recommendations to Wally (continued) SportObermeyer 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). RECOMMENDATION #5 (continued)
  • 79.