isye 4301: supply chain economics case study | sport...

ISYE 4301: Supply Chain Economics Case Study | Sport Obermeyer

Group 2:

Jordan Avery

Michael Gilkenson

Alina Cornejo

Fabio Romero

Farida Jariwala

Sara Rogovin

Eric Timm

ISYE 4301 Case Study | Sport Obermeyer

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Table of Contents

Page Title

2 Obermeyer Beginnings

7 Obermeyer Challenges

7 Challenges and Methods of Forecasting

8 Effective Inventory Management Policy

11 Sports Obermeyer ’92-’93 Initial Strategy

11 Our Solutions

12 Obermeyer’s Actual Response


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Obermeyer Beginnings

Everything started when Klaus Obermeyer emigrated from Germany to Aspen, Colorado

in 1947. He began teaching at the Aspen Ski School, and through his teaching, he found that

many of his students were poorly supplied to handle the cold weather. His response was to begin

producing functional, stylish ski clothing with his wife, Nome.

Obermeyer is credited for making the first goose-down vest and popularized the “ski

brake”. In 1961, the first Sport Obermeyer factory warehouse opened in Aspen, and the

innovations continued with “soft-shell” jackets, double lens goggles, and the first waterproof-

breathable fabrics. Customers of Sport Obermeyer are mostly retail stores in urban areas, near ski

resorts, some large department stores like Nordstrom, and mail retailers like REI.

All the items of the company are provided and produced in Asia. In China they have

independent subcontractors in Shenzhen and Lo Village. Other production locations are in Hong

Kong and Macau. Obermeyer products were divided into different “genders”: men’s, women’s,

boys’, girls’, and preschoolers’. Each gender was then further segmented by price, type of skier,

and how “fashionable” the market was. Unlike its competitors, Sport Obermeyer targeted the

middle to high end of the skiwear market and designed the majority of their products exclusively

for use while skiing, not to be worn on the street. Over the years, Sport Obermeyer developed into

a main competitor in the U.S. skiwear market and by 1992 Sport Obermeyer owned 45 percent of

the children’s skiwear market and 11 percent of the adult’s skiwear market.

In 1992, Sport Obermeyer’s gross profit margin was 24%. The changes Wally made in

the following years led to an increase in profits by 50%, and thus a 50% increase in profit margin

to 36%. By contrast, one of Sport Obermeyer’s biggest competitors, Columbia Sportswear, as a

high-volume, lower-quality manufacturer, has an average profit margin across all products of

4.15%. The skiwear market is $3.3 billion.


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Obermeyer Challenges

Some of the challenges that Sport Obermeyer faced were consequences of poor

forecasting. Each year Obermeyer had to decide on production quantities for each of its products

prior to knowing the product’s actual demand. Below is a graph of the forecasts and actual

demands throughout the production process. As production continues, the forecasts get more

accurate ending in almost a linear fashion after observing 80 percent of sales.


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It was necessary, however, to start production so retailers would receive products early

for customers to be exposed to its products for a decent amount of time. Obermeyer earned

approximately 24 percent of wholesale price prior to tax on each parka the company sold.

Leftover parkas were sold at a loss that averaged 8 percent of wholesale price. In addition, these

leftovers incurred high inventory holding costs. Obviously Obermeyer did not want to exceed

demand; Obermeyer also did not want to be short of demand because when it did not produce

enough to meet demand it was missing out on profit.

Greater product varieties made it harder to accurately predict demand. Wally, the vice

president, asked each member of the “Buying Committee” to forecast retailer demand for each

product. Forecasts varied greatly among the individuals as shown below.

Sample Buying Committee Forecasts for the different styles of Women’s Parkas

History showed that forecast was the most accurate when the consensus among the

members was the greatest. Wally also noticed that the standard deviation of demand for a

particular style was about twice the standard deviation of the Buying Committee’s forecasts for

that style. Thus, Wally created a forecast distribution for each style as a normal random variable

with the average of the committee’s forecast being the mean and the standard deviation being

twice that of the committee’s standard deviation.


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One of the main issues that Sport Obermeyer was faced with was their supply chain; they

were challenged with the decision of where to produce the bulk of their products. In Sport

Obermeyer’s supply chain system, they outsourced their products through Obersport, a joint

venture established by Klaus Obermeyer and Raymond Tse, to assist in the production of Sport

Obermeyer products in the Far East. Obersport supported two locations for manufacturing Sport

Obermeyer’s products: Tsuen Wan, Hong Kong and Guangdong, China. Obersport was

responsible for the fabric and component sourcing. They purchased the outer shell fabric from

vendors in the United States, Japan, Korea, Germany, Austria, Taiwan, and Switzerland. The

lining fabric was purchased primarily from Korea and Taiwan. Obersport outsourced other

components such as insulation materials, D-rings, buckles, snaps, buttons, zippers, pull-strings

with attached castings, and labels/tags from Germany, Japan.

The two factories for cutting and sewing were Tsuen Wan, Hong Kong and Guangdong,

China. The speed of this production depended majorly on the factory in which it was produced.

Workers in the Hong Kong factory worked about 50 percent faster than those in China. However,

the wage rates for China were much lower than in Hong Kong. Another disadvantage of China’s

production is that they required 40 workers compared to Hong Kong’s 10 workers. These longer

production lines in China led to pronounced instability in assembly. Additionally the Hong Kong

factory was able to initiate production much quicker than the Chinese workers. This quality


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joined with short production lines, allowed the Hong Kong factory to produce small orders

quicker and more efficiently. The table below shows a complete comparison between operations

in Hong Kong and China.

There are two questions that Obermeyer needed to answer. Firstly, which styles should be

produced in China and which in Hong Kong? During 1992 Obermeyer predicted that

approximately half of all of their products would be produced in China. However, long term this

may not be the best strategy for Obermeyer. Producing in China could constrain their ability to

produce quickly as well as manage production and inventory. If more products were produced in

Hong Kong, Sport Obermeyer would have the flexibility to produce smaller order quantities more

quickly, as well as a guaranteed higher quality of work. There are many factors to consider when

deciding where to produce. Hong Kong has benefits such as more rapid production, smaller work

numbers, and increased line stability; their only disadvantage was the high wage rates. On the

other hand, China had slower production and greater line imbalances due to the higher number of


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workers per line, in addition to import restrictions; their only advantage being considerably lower

wage rates.

The second question to be answered was whether or not it would be better for Obersport

to outsource to a smaller number of suppliers. For example, Obersport ordered greige shell fabric

from 7 different countries, insulation from 4 suppliers, and finished lining from 3 different

suppliers, not to mention the different companies that supplied zippers, logos, snaps, etc. Is this

the least costly approach to gather the components into one location? Suppose Obersport

decreased their supplier base. This in turn would decrease lead times and increase the speed of

production. However a smaller supplier base correlates with a greater risk. If they outsource shell

fabric, for example, from one supplier and the supplier goes out of business, then Obersport is left

in an extremely difficult position. They would lose money, completely stop production, and lose

clients.

The question of whether or not Obersport has too many suppliers leads to another

question. Does Obermeyer have too many parka shell designs? This can be argued both ways.

Sport Obermeyer prided itself in the fact that they offered such a broad range of parka styles. This

attracted many different types of consumers and raised profit and distinction. Obermeyer sold the

majority of its products to specialty ski retailers due to the fact that they produced specifically ski

equipment rather than everyday winter jackets and pants. Decreasing the types of shell designs

and styles could lower their customer base since they are well known for that particular reason.

However, with a decrease in shell designs the number of suppliers would be reduced, leading to

lower lead times, and faster, more even production.

Challenges and Methods of Forecasting

Devising an accurate forecast for demand of their array of products was another

challenge that Sport Obermeyer faced. The inability to accurately predict future demand led to


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problems up and down their supply chain. For example, they often could not meet demand for

popular items and had excess of less popular items that they were forced to sell at a loss.

Sport Obermeyer’s problems with forecasting are not unique. Forecasting is inexact and

most often incorrect. The company’s need to forecast many production cycles in advance

exacerbated their problems—as well as their need to predict fashion trends years into the future—

as the longer the forecast horizon is, the more likely it will be wrong.

One of Sport Obermeyer’s biggest problems in forecasting is predicting which styles of

coats will be most popular in a given season. Other companies cope with customer variability

through risk pooling, which utilizes a central distribution system that reduces aggregate demand

variability across all markets. Companies also utilize time-series methods in which they analyze

past behavior in order to predict future behavior. They might analyze behavior of specific types of

customers or of sales of specific types of items. These methods would be very beneficial for Sport

Obermeyer. Finally, companies also use causal methods that attempt to forecast future demand as

a function of data unrelated to sales (such as GNP, unemployment rate, or weather).

Effective Inventory Management Policy

Another challenge associated with devising an optimal inventory policy is the tradeoff

between service level and inventory level. The higher the service level, the higher the inventory

level. A company can determine a target service level across all products and then develop

optimization models that determine service levels for individual products and maximize profit.


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As service level increases, cost of inventory increases.

Sport Obermeyer must cope with variable lead times in their production cycle. Their full-

scale production begins in February and the first shipment of finished goods does not occur until

June. Some of the lead times on individual elements of their products are as much as 90 days.

This variability affects the company’s ability to maintain inventory levels capable of satisfying

demand but not wildly exceeding it.

Lead times of Various Materials


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The fact that their overall lead-time is four months means that they can only produce

once in a given season. If they were able reduce lead times across their entire supply chain, they

would be able to react to customer demand for specific products and reorder them, which would

maximize their profits.

Sport Obermeyer is currently operating under a single period model of inventory

management. That is, their product has a short lifecycle and they only order once a season. Thus,

their ability to accurately forecast is that much more important. Through more accurate

forecasting, they would be able to better predict the behavior of customer demand and determine

the order quantity Q that maximizes their profits.

Below is a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis for

Obermeyer. The goal of Obermeyer is to use their strengths and pursue opportunities to eliminate

weaknesses and threats.


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Sports Obermeyer ’92-’93 Initial Strategy

After much debate Sports Obermeyer decided to forecast their ‘92-‘93 demand by

creating a model based on a sample of their product line and extrapolating that data to the rest of

their product lines. Sports Obermeyer looked at the forecasting data for the ten women parka

designs, which represented about 10 percent of Sport Obermeyer’s total demand. To make this

plan more realistic he scaled the production capacity to 10 percent of actual capacity. From this

forecast he decided to commit half of his production in November, the 1st production period, and

the 2nd half in march once he had visited the Las Vegas fashion show and perfected his forecast,

in the 2nd production period. After this experiment Wally realized that the actual variation

between style demands was much lower where the buying committee had similar forecasts.

As mentioned, Obermeyer polled individual board members about their retailer demand

forecast for each Obermeyer product. Wally then used the individual forecasts to come up with an

appropriate estimation. The only issue with his forecast was that there was a large variation

between individual forecasts. As an extension to this original strategy, Wally could have used the

Delphi method to compile and summarize the individual’s forecasts and to let the individuals

change their forecasts after seeing the summary. After multiple iterations a more uniform

consensus should be achieved.

Our Solutions

The team’s first strategy is to implement an electronic inventory tracking system in the

winter months before peak season. The electronic database would supply Sport’s Obermeyer with

real time sales data that would allow them to spot trends early in the winter season. This strategy

is to maximize Sport’s Obermeyer’s profits by ensuring that there will be no stock-outs during the

peak season. In the case study, Wally mentions that if he is notified of demand early enough,

Hong Kong has the capability of producing and air delivering parkas with a 2 month lead time.

Although the profit margin will not be as high on these items, this method would ensure that there


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are no stock outs and the remaining profit margin is more than enough to offset the air

transportation and premium labor costs in Hong Kong ($47.42 profit per parka that wouldn’t have

been made otherwise).

The team’s second strategy is to expand into the South American Markets. This strategy’s

focus is to continue to maximize profits on Sport Obermeyer’s popular products and to prevent

downside risk on the North American overstocked products that would have normally been sold

at extreme discounts. Since the seasons are flopped the overstocked North American products are

in season in South America and can now be sold at wholesale value. By implementing this

strategy you would reduce the expected loss on unsold parkas, currently 8 percent less than

wholesale, and continue the production of the popular products, which sell on an average of 24

percent profit.

The team’s third strategy is to reduce time in the design phase. Currently, Sport’s

Obermeyer offers several preliminary samples for the next year’s product designs. If Sport’s

Obermeyer manufactured fewer samples and created digital samples with specs, Sport’s

Obermeyer could reduce the sample making process by 30-40 days, which would allow starting

production sooner and using China, the cost effective suppliers, to produce the initial product

supply. This suggestion would help Wally accomplish his goals of having 50 percent of

production through China and having an early start production date.

Obermeyer’s Actual Response

Obermeyer decided to install a computerized system to slash time for order processing,

pre-position raw materials, hold sneak preview of upcoming lines, and talked to designers to

encourage the use of the same types of raw materials and keep everything undifferentiated until

close to the end of production. The computerized system, pre-positioning of raw materials, and

the sneak preview of upcoming lines helped increase forecasting. The computerized systems

helped Obermeyer understand the popular trends. The pre-positioning of raw materials shortened


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lead-time to start production earlier. The sneak preview of the upcoming line brought in 20% of

orders rather than waiting until the March fashion show to get 80% of the orders. Using the same

raw materials and undifferentiating the designs cut down lead-time and decrease the number of

supplies.

The changes Wally made in the following years led to an increase in profits by 50% to a

profit margin of 36%. The company’s customer rating increased to number one. Over-

production decreased from 25,000 to 22,000 and under-production decreased from 7,500 to 800.

The methods helped predict popular products more easily than before, but the methods did not

help decrease over-production as well as they had hoped. Moving the market to South America

could help decrease the over-production significantly.

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