Case Study Sport Obermeyer

1. Prepared by: Shaheen Sardar
SCM Lab. Department of Industrial and
Management Engineering, Hanyang
University, South Korea.
Case Study: Sport Obermeyer

2. 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

3. Company History:
1985: Obersport; a joint venture in Hong Kong, the company began
to increase productivity to meet their new demands.

4. Women’s Collection

6. Competitors
The Jacobs Corporation
founded by David L. Jacobs Biography

7. Competitors
The North Face, Inc.
: subsidiary of VF Corporation

8. Competitors
Burton Snowboards
founded by Jake Burton Carpenter
Innovative Burton
outerwear performance meets
leading Motorola Bluetooth ®
technology

9. 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)

10. 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

11. Manufacturing Structure:
Sport Obermeyer Ltd.
Obersport Ltd.
Alpine Ltd
• Hong Kong
• Macau
• China
Lo Village
Other subcontractors

12. COMPANY
NETWORK:
Recently, a number of
contractual ventures
were added and a new
complex in Lo Village
Guangdong China

13. Product and Segmentation:

14. Product Variety:

15. 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

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
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.

19. 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

20. 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

21. Production Options
• Hong Kong
– 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 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:

24. 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.

25. 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

26. 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:

27. 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:

28. 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)

29. 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

30. 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

31. 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)

32. 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

33. 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

34. 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

35. 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

36. 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

37. 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

38. 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).

39. 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.

40. 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.

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 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 

44. 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!

45. 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!

46. 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!

47. Question 1. and 3. Comparison units of each style
when produced in HK and China

48. Differences between production in HK and China
• Inventory
• Total Cost
• Operation Time
• Quality (% Repair)

49. Question 1. and 3. The differences between
production in HK and China

50. 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

51. Question 1 (Alternative approach)

52. 2. Can you come 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 always uncertain
Why does risk happen?
Demand Average
Standard
deviation
Standard
deviation

55. How we assess
forecast certainty?
1 . Based on historical data
- Past forecast error
- Variability of demand

56. 2. Rather than producing one joint
forecast, each member of the purchasing
committee produces his/her own forecast .
Obermeyer’s Buying committee

57. 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

58. 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”

59. 4. What operational changes would
you recommend to Wally to improve
performance?

60. • 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:

61. • Reducing number of 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 production Quality 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 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

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 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:

67. Hong Kong
Seattle
Original distribution process
Establish Distribution
Center in Seattle without
through Denver

68. 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:

69. 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?

70. 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

71. Where is better?
Short term 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)
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)

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)
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)

79. Thank You