Sports Obermeyer Case Study

Running head: SPORT OBERMEYER CASE

STUDY 1

Sport Obermeyer Case Study

Name:

Institution Affiliation

Date

SPORT OBERMEYER CASE STUDY 2

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 ten 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.

As stated that we ignore the differences in the styles prices, we use the wholesale selling

price mentioned for Rococo in the textbook which is $112.5 (Hammond, 1994).

To determine the production quantities speculated, we need to identify the value of k, which

makes the production quantity to be at least 10,000 units.

When k = 1, we have the following table.

STYLE

Wholesale Selling Price

Average

Forecast

2 * Standard

Deviation

First Period

Production Quantity

Max (0, µ-k)

Gail

$ 112.50

1,017

388

629

Isis

$ 112.50

1,042

646

396

Entice

$ 112.50

1,348

496

862

Assault

$ 112.50

2,525

680

1,845

Teri

$ 112.50

1,100

762

338

Electra

$ 112.50

2,150

807

1,343

Stephanie

$ 112.50

1,113

1,048

Seduced

$ 112.50

4,017

1,113

2,904

Anita

$ 112.50

3,296

2,094

1,202

Daphne

$ 112.50

2,383

1,349

989

19,991

9383

10,573

In this table, the total production quantity is at 10,583, a figure that is slightly higher than the

committed production of 10,000 units.

To determine the actual value of k, using the formula Max (0, µ-k) (Kibble, 1961), we take the

Average total forecast (µ) and subtract the total standard deviation * k.

∑

µ −

𝑖=1

∑

𝑘𝜎

𝑖=1

=10,000

19,991 – 9,383k = 10,000

9,383k = 9,991

SPORT OBERMEYER CASE STUDY 3

k = 1.0648

The units per style are therefore as shown below:

STYLE

Wholesale Selling

Price

Average

Forecast

2 * Standard

Deviation

First Period

Production Quantity

Max(0, µ-k)

Gail

$ 112.50

1,017

388

605

Isis

$ 112.50

1,042

646

357

Entice

$ 112.50

1,348

496

832

Assault

$ 112.50

2,525

680

1,804

Teri

$ 112.50

1,100

762

292

Electra

$ 112.50

2,150

807

1,294

Stephanie

$ 112.50

1,113

1,048

Seduced

$ 112.50

4,017

1,113

2,836

Anita

$ 112.50

3,296

2,094

1,075

Daphne

$ 112.50

2,383

1,349

904

19,991

9383

10,000

Assuming that the styles are done in Hong Kong whose least ordering amount stands at 600

units; we keep the orders of styles with more 600 units, but those styles with less we change to

600 units.

Check the table below:

Max(0, µ-k)

Order Quantity in Hong Kong

605

357

600

832

1,804

292

600

1,294

600

2,836

1,075

904

10,000

11,150

SPORT OBERMEYER CASE STUDY 4

2. Can you come up a measure of risk associated with your ordering policy? This measure

should be quantifiable.

Weber and Shafir,( 2004) advocate use of the coefficient of variation to measure risk and apply it

to a meta-analysis of data.

Coefficient of Variation = Standard Deviation / Average Forecast

STYLE

Standard Deviation

Average forecast

Coefficient of Variation

Gail

194

1,017

0.19

Isis

323

1,042

0.31

Entice

248

1,348

0.18

Assault

340

2,525

0.13

Teri

381

1,100

0.35

Electra

404

2,150

0.19

Stephanie

524

1,113

0.47

Seduced

556

4,017

0.14

Anita

1,047

3,296

0.32

Daphne

697

2,383

0.29

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?

China’s least order quantity stands at 1200 units (Hammond, 1994) and as such, orders with

more than 1200 units are kept while those with less are changed into 1200 units as in the table

below:

Initial Production

Order Quantity in China

605

1,200

357

1,200

832

1,200

1,804

292

1,200

1,294

1,200

2,836

1,075

1,200

904

1,200

10,000

14,334

SPORT OBERMEYER CASE STUDY 5

One of the most evident differences is the number of styles that needed to be sourced more than

the forecasted average. Using our sample, when ordering from China, Wally had to order seven

of the styles in excess and only three while ordering from Hong Kong. Though China offered

low labor costs, they were less flexible and exposed Wally to greater risk. Hong Kong offered

more reliable and high-quality products as compared to mainland China.

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

Operation efficiency in any organization impacts positively on performance and could

greatly reduce costs and increase productivity (Hosking, 2003). Wally needs to address a few

modes of operations. Firstly, there is need to decrease the number of production styles as well as

the stock keeping units as they have increased risk, complexity, inventory, and has made it

difficult to predict the customer demand for each style. Secondly, he needs to reduce the

production lead time, especially when dealing with raw materials. For instance, the lead time for

zippers from Japan needs to be minimized as it exceeds ninety days, a period considered to be

overdue. It could be reduced through such initiatives as giving incentives and sharing profits

with the suppliers. Thirdly, Wally should also focus on increasing the bargaining power of his

suppliers. It can be achieved through orders via a big supplier who can commit to set timelines.

Further, it is noted that some fabrics such as greige would be printed or dyed at a later date as

was deemed necessary. It prolonged their production process thus he should consider reducing

unnecessary postponement as this lowers his risks. Additionally, Wally should consider

employing promotional strategies that can persuade retailers and consumers to order such as

product giveaways, branded gifts as well as holding appreciation events for retailers and

customers. With a critical approach, Wally should make appropriate changes data systems,

SPORT OBERMEYER CASE STUDY 6

exploit historical data and speed up information analysis in his research for emerging market

trends, products, and customers’ demands.

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?

Givaudan (2016) states that responsible sourcing is based on certain general principles

that guide supply and service delivery. When procuring from China, seven of the styles needed

to be sourced more than the forecasted average to obtain the minimal production amounts. As

such, priority was given to low-risk items. However, Hong Kong was more flexible and

produced quality items thus recommended for risky products. Sourcing from China is

commendable for the long term while Hong Kong is best suited for the short term. Regarding

production, Hong Kong produced faster and more reliably as compared to China. To address

sourcing issues, Wally should use a weighted average rather just using an average of the specific

forecast from Laura and Tom. It is important for him to obtain the market feedback early enough

to enable him to convert production from a speculative to a reactive one. Improved sourcing

would mean decreased lead times both for the finished good and the raw materials. The business

should emphasize on a business strategy that focuses on dependability than cost.

SPORT OBERMEYER CASE STUDY 7

References

Elke U. Weber, S. S. (2004). Predicting Risk Sensitivity in Humans and Lower Animals: Risk as

Variance or Coefficient of Variation. Psychological Review, 430-445.

Givaudan. (2016). Sourcing Responsibly. Responsible Sourcing Policy, 3-7.

Hammond, J. H. (1994). In Sports Obermeyer, Ltd (pp. 64-75).

Hosking, J. (2003). Developing a Replacement Facility Strategy: Lessons from the Healthcare

Sector. Journal of Facilities Management, 214-28.

Kibble, T. (1961). Lorentz Invariance and the Gravitational Field. Journal of Mathematical

Physics, 212, Volume 2.

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