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Sport Obermeyer, Ltd. was founded by Klaus Obermeyer to provide U.S. skiers with the same protective and stylish clothing and equipment available in Germany. With a history of innovative new products and leading styles, Sport Obermeyer developed into a prominent competitor in the U.S. skiwear market selling its products in U.S. department stores and specialty ski shops. Based out of its Aspen, Colorado headquarters, Obermeyer currently offers a broad line of fashion ski apparel, including parkas, vests, ski suits, shells, ski pants, sweaters, turtlenecks, and accessories.
Although Sport Obermeyer has a global supply network, most production is done in Hong Kong and China by its partner, Obersport Limited. Established in 1985 as a joint venture between Klaus Obermeyer and Raymond Tse, Obersport is responsible for fabric and component sourcing for Sport Obermeyer’s entire production in the Far East. The materials are then cut or sewn either in Raymond Tse’s own “Alpine” factories or by independent subcontractors. Sport Obermeyer’s orders represent about 80 percent of Alpine’s annual production volume.
Common factors used to make future sales forecasts include historical sales data, data from competitors of similar products, and estimation of future demand and economic conditions, and statistical averages and variations from this data collected. Forecasts are almost never 100% accurate, but supply chain managers must do their best to make as accurate projections as possible in order to be efficient with inventory, logistical costs, and production costs to ensure an overall profitable business endeavor for the company.
According to our textbook, forecasting can be defined in to four general categories: Judgment Methods, Market Research Methods, Time-Series Methods, and Casual Methods. The first category, Judgment Methods, directly applies to the first question in this case study. Judgment Method involves the collection of expert opinions in a systematic way to attempt to accurately forecast future sales. Figure 2-20 in the Obermeyer case study shows sales projections for 10 Obermeyer women’s parka’s by a six person projection committee.
Each committee member lists a sales estimate for each of the 10 different parka’s, with standard deviations listed to show an estimated variance of what the actual production will be from the estimated production. In order to make an accurate forecast, we will take the approach of minimizing risk as much as possible for Obermyer. Our projections are listed in the attached excel sheet. The method we used was to take the average demand from each of the six committee members for each product, subtract the standard deviation, and multiply in a variable (k) to get to the desired production level of 10,000 units. This strategy takes in to account demand uncertainty and expected demand.
This is calculated by dividing standard deviation by average demand. Standard deviation is defined as a measure of how much demand tends to vary around the average, and coefficient of variation is the ratio of standard deviation to average demand. Coefficient of variation measures variability relative to average demand. Our calculations of coefficient of variation can be seen in the attached excel spreadsheet. The various coefficients of variation listed illustrated the risk involved with each projection.
The first recommendation would be to 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, and Wally, it would be better to use a weighted average, with the weights reflecting past accuracy.
The second recommendation would be to obtain market feedback earlier than Las Vegas, thereby converting some Speculative Production to Reactive Production. Sport Obermeyer could invite selected retailers to come in January to Aspen for an all-expense paid “Early Order Weekend”, where there would be a “sneak preview” of the new line, some recreational skiing and socializing, and then the opportunity to place early orders at a discounted rate.
The third recommendation would be to 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 could be reduced by using several methods: computerize processes (collect and use POS data); choose suppliers of raw materials more on the basis of dependability rather than cost and do not commit initial production orders to an unproven factory; expedite orders through information sharing with suppliers; expedite shipments using faster (but more expensive) shippers or establish local (but more expensive) production capability with subcontracts who can deliver at a faster rate for “last minute” production needs. Additionally, for items with long lead times, Obermeyer could increase the amount of safety stock inventory for those items that are inexpensive (ex: buttons) and/or shared by many parkas (ex: black fabric). Finally, Obermeyer should simplify the parkas’ designs so that they can share as many components as possible (use standardized products).
The fourth recommendation would be to increase production capacity. This could be done several ways including using more subcontractors, using more overtime in China, and/or exploring an alliance with a swimwear manufacturer who could “supply” excess capacity when Sport Obermeyer needs it and “consume” capacity when Sport Obermeyer has excess capacity.
The final recommendation would be to 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 could come from improved process design and/or improved equipment (ex: more flexible cutting machines).
Hong Kong offers shorter production time, allows smaller orders which are better for initial forecast and is better for high risk designs. China, on the other hand, offers lower overall costs and is better for lower risk designs. For the long term, Hong Kong offers higher quality products, but their low unemployment levels means higher wage expense. For the long term, China’s unstable political environment is an important factor to keep in mind, as well as the import quotas, high minimum order quantity levels, and the effort that must be put in to increase worker efficiency and skill.
Our source policy recommendation would be for Sport Obermeyer to continue its relationship with Obersport and seek to improve the coordination between Sport Obermeyer’s demand side activities and Obersport’s supply side activities. Furthermore, Obersport should work with its Chinese facilities to attempt to make an agreement to allow reduced minimum orders and implement a program that will improve worker skills. This would solve two of the biggest issues with the Chinese suppliers – high minimum order quantities and low quality of work. Wally should continue to use the Hong Kong facilities for small order quantities and using the Chinese facilities for large-batch quantities.
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