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Case study; sport obermeyer

Case study; sport obermeyer






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    Case study; sport obermeyer Case study; sport obermeyer Presentation Transcript

    • Case Study: Sport Obermeyer Prepared by: Shaheen Sardar SCM Lab. Department of Industrial and Management Engineering, Hanyang University, South Korea.
    • Company History: 1947: Klaus Obermeyer, a German immigrant began teaching at the Aspen (U.S.) Ski School “Skiing is a celebration of life” Klaus Obermeyer
    • 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 (Men, Women, Boys, Girls, Preschoolers) • Company segmented each gender market price, type of skier and fashion forwardness. different genders according • 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 to
    • 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 Produce, dye and print shell and lining fabrics, supply insulation, zippers, thread, logo patches and snaps. Apparel Manufacturers Subcontractors, receive production orders and materials from Obersport. Cut, sew and final assembly. Obersport Sport Obermeyer Retailers 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 products made in June and July were transported by ships Seattle Hong Kong Warehouse goods produced in August were air-shipped then transported by trucks Obermeyer’s Denver Warehouse Cost $5 per parka orders were finally shipped via small-package carriers such as UPS (United Parcel Service) at the end of August 1993 Retailers
    • Retailers Delivering products by early September Sport Obermeyer Specialty SkiRetail Stores Department Stores Direct Mail Retailers Most sales occur between September and January Consumers
    • 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
    • Planning and Production Cycle: Feb 92 Mar 92 May 92 Jul 92 Sep 92 Prototype, Sample Production Design Process begins Las Vegas Show Nov 92 Concept Finalise Mar 93 Sketches sent to Obersport Apr 93 - Jul 93 Designs Finalised Dec 93-Feb 94 Full scale production Place 1st Production Order with Obersport Las Vegas Show Additional orders received Replenishment orders received
    • 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 "NOW" Initial Forecast 9 months Feb … Oct 1992 … 1992 Design of 1993-94 Line. Las Vegas Revised Forecast 5 months Nov … Mar 1992 … 1993 5 months April … Aug 1993 … 1993 "Speculative" Production "Reactive" Production of 1993-94 Line of 1993-94 Line In Feb 1993, start design of 1994-95 line. “Speculative” Production 27 Months Sept 1993 Oct 1993 Nov 1993 8 months Dec Jan 1993 1994 Selling of Feb 1994 Mar 1994 1993-94 Line (peak selling in Dec & Jan) In Feb 1994, start design of 1995-96 line. “Reactive” Production Apr 1994
    • Production Process: Asia Fabric Producer 6 weeks Fabric Dyer Un-dyed greige goods Cut/Sew Factory 6 weeks Denver Warehouse Retailer 6 weeks Components Procurement lead time Greige Shell Fabric 45 – 90 days Finishing of Shell Fabric (Dying & Printing) 45 – 60 days Finished Lining Fabric 45 – 60 days Insulation 2 – 3 weeks Zippers Standard (HK) 60 days, Custom (JP) 90+ days Thread 30 days Logo Patches, Drawcords, Hang Tags, etc. 15 – 30 days Snaps (undyed) 1 – 2 months Dyeing of Snaps 15 – 30 days Consumer
    • Ordering and Shipment Process: 6 weeks Factories in Hong Kong Denver warehouse Seattle warehouse Order 80% in Mar 93 Order 20% in Apr-Jun 93 Forecasts Product Sketches Forecast Committee Retailers order in Apr-Jun 93 800 Ski Retailers
    • Sales and Replenishing Process: Aug 93 Sep 93 Oct 93 Nov 93 Dec 93 Feb 94 Sales Peak 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
    • ESTIMATED COST INFORMATION FOR ROCOCO PARKA (IF ASSEMBLED IN CHINA) 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
    • 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 20,000 20,000 20,000 20,000 20,000 20,000 Totals
    • 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
    • COMPARISON OF OPERATIONS IN HONG KONG AND CHINA 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 19 parkas 12 parkas Weekly (non-peak output/worker)
    • COMPARISON OF OPERATIONS IN HONG KONG AND CHINA Topic Hong Kong China Actual labour content per parka (incl repair work) Paid labour time per parka (incl repair work) Labour cost /garment Line configuration -2.35 hours -3.6 hours -2.53 hours/parka -4.88 hours/parka HK$75.6 RMB 4.45 10-12 people/line 40 people/line Training Cross-trained Min order quantity 600 units in same style Repair rate 1-2% Trained for single operation only 1200 units in same style -10% Challenges Wage Workforce rate, Workforce Low unemployment Younger worker prefer office job Less quality and cleanliness conscious Training requirements
    • 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 Opportunities: • Aggressive marketing campaign • Expanding sales to European/ South American markets • Sponsorship of major winter sports events 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 Threats: • Competition from valueoriented 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) DETERMINING SPECULATIVE PRODUCTION QUANTITIES k =0 <---Find value of k that makes last column sum to about 10,000 MEAN OF DEMAND STYLE Gail Isis Entice Assault Teri Electra Stephanie Seduced Anita Daphne Sum--->  1017 1042 1358 2525 1100 2150 1113 4017 3296 2383 20,001 STANDARD FIRST-PERIOD DEVIATION PRODUCTION QUANTITY OF DEMAND  Max (0,   k ) 388 646 496 680 762 807 1048 1113 2094 1394 1017 1042 1358 2525 1100 2150 1113 4017 3296 2383 20,001 Too much! <---Sum
    • 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 MEAN OF DEMAND STYLE Gail Isis Entice Assault Teri Electra Stephanie Seduced Anita Daphne Sum--->  1017 1042 1358 2525 1100 2150 1113 4017 3296 2383 20,001 STANDARD FIRST-PERIOD DEVIATION PRODUCTION QUANTITY OF DEMAND  Max (0,   k ) 388 646 496 680 762 807 1048 1113 2094 1394 Too little! 241 0 366 1165 0 536 0 1791 0 0 4,099 <---Sum
    • 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 MEAN OF DEMAND STYLE Gail Isis Entice Assault Teri Electra Stephanie Seduced Anita Daphne Sum--->  1017 1042 1358 2525 1100 2150 1113 4017 3296 2383 20,001 STANDARD FIRST-PERIOD DEVIATION PRODUCTION QUANTITY OF DEMAND  Max (0,   k ) 388 646 496 680 762 807 1048 1113 2094 1394 629 396 862 1845 338 1343 65 2904 1202 989 10,573 Too much! <---Sum
    • Solving Wally’s Sample Problem (with k=1.0608) DETERMINING SPECULATIVE PRODUCTION QUANTITIES k = 1.0608 MEAN OF DEMAND STYLE Gail Isis Entice Assault Teri Electra Stephanie Seduced Anita Daphne Sum--->  1017 1042 1358 2525 1100 2150 1113 4017 3296 2383 20,001 <---Find value of k that makes last column sum to about 10,000 STANDARD FIRST-PERIOD DEVIATION PRODUCTION QUANTITY OF DEMAND  Max (0,   k ) 388 646 496 680 762 807 1048 1113 2094 1394 Just right! 605 357 832 1804 292 1294 1 2836 1075 904 10,000 <---Sum
    • 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.
    • What’s the result if there is demand forecasting uncertainty? -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
    • Why does risk happen? Forecasts are always uncertain Standard deviation Standard deviation Demand Average
    • 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? “Risk –based production planning” - 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
    • 4. What operational changes would you recommend to Wally to improve performance?
    • KEY Problems: • 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
    • OPERATIONAL Changes: • 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.
    • Lead time reduction Asia Fabric Producer Fabric Dyer undyed greige goods Cut/Sew Factory Denver Warehouse Retailer Consumer Sport Obermeyer • 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
    • 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
    • OPERATIONAL Changes: 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
    • Original distribution process Seattle Hong Kong Establish Distribution Center in Seattle without through Denver
    • OPERATIONAL Changes: 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.
    • 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.
    • Recommendations to Wally (continued) 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) 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) RECOMMENDATION #5 (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).
    • Thank You