3. Case-Sports Obermeyer

1

How to deal with products having highly uncertain

demand pattern and short product life cycle?

2

Functional vs Innovative Products ?

3

Cost of lost sale

Risk of obsolescence

Forecast accuracy

Product variety

Product life cycle

High

Low

Low

Low

High

High

High

Low

ShortLong

Functional Innovative

Products differ

4

And supply strategies differ

Factory focus

Inventory Strategy

Lead-time focus

Supplier selection

Product-design strategy

Low cost preferred over short lead-time

High utilization

High turns

Low cost

Maintain buffer capacity

Significant buffer stocks of components and FGs

Speed & flexibility

Aggressively shorten lead-time

Modular to enable postponed differentiation

Integral for max performance at min cost

Physically efficient

Market responsive

5

match

matchmismatch

mismatch

Life cycle > 2 yearsGross Margin < 35%Low Product Variety

Functional Products

Life cycle < 1 yearGross Margin > 35%High Product Variety

Innovative ProductsR

esp

on

sive

S

up

ply

Ch

ain

Eff

icie

nt

Su

pp

ly C

hai

n

Supply predictable demand efficiently at lowest cost

Respond quickly to unpredictable demand to minimize stockouts, markdowns, and obsolete inventory

Need to match supply strategy with product type

6

So as to minimize total of two types of costs

• Physical Production/Distribution Costs

– Production Costs

– Transportation Costs

– Facility Utilization rates

– Inventory carrying cost on pipeline and cycle stocks

• Supply/Demand Mismatch Costs

– Lost revenue and profit margin when supply is less than demand

– Product and parts scrapped or sold at a loss when supply exceeds demand

– Inventory carrying cost on safety stocks

7

Sport ObermeyerA classis example of innovative product with highly uncertain demand and short product life cycle. Also highlights the importance of:

• Shorter lead times

• Smaller minimum order requirements

• Increased reactive capacity

• Improved market information

• Reducing the expected costs of stock outs and markdowns

8

A page from Sport

Obermeyer’s product catalog

9

Next year’s catalog

10

Obermeyer’s styles are fashion-forward and change every year

11

Factories in China and Hong Kong

DC in Denver

800 Ski Retailers

The Obermeyer supply chain stretches from Asia to Aspen

12

Obermeyer’s planning calendar (For

targeted season of Sept, 09-Jan, 10)

• Designing starts in February, 08 and Finalizes in September, 08

• Production starts in November 07, about six months ahead of Las Vegas Show

• Las Vegas Fashion Show: March every year (March, 09)

• Bulk receiving of orders from retailers after Las Vegas in March-April, 09

• Shipping of finished products from China / Hong Kong: August-September, 09

• Normal Sales Season: Sept-Oct-Nov 09

• Peak Sales Season: December, -09 and January, 10

• Replenishment: In February, 10 by Obermeyer at discounted rates and simultaneously markdowns by the retailers

13

Problems at Obermeyer• Long Product Development Cycle

• Inaccurate Forecasts

• High Stock outs as well as high mark downs

• Hong Kong vs. China

14

Cost of Under and Over Production

Rococo Parka

Wholesale Price: $112.50 Profit Margin: (24% of wholesale price)= $27

Expected loss on each unsold parka: (8% of wholesale price)= $9

15

Which parka family sold best?

Black Voodoo sold 4000

Sold 4

16

Initial forecasts are highly inaccurate …

but improve dramatically with just a little sales data

17

Sample buying committee projections: Which product is more predictable?

Gail

Isis

Laura Carolyn

Greg Wendy Tom Wally Average

Std. Dev.

900

800

1000 900 1300 800 1200 1017 194

700 1000 1600 950 1200 1042 323

18

How to think about supply chain improvementProduct

Availability

Responsive Supply Chain

Inventory

Accurate Forecasts

How does product availability drive revenue?

Optimize cost of lost margin, carrying and obsolescence

Track & improve the accuracy of forecasts that drive decisions e.g. parts lead time demand

Create a framework for inventory efficiency e.g. common parts, short lead times, efficient small lot production

19

• How should Wally think about how much of each style he should order in November– Production Planning– How do we do production planning? (OM)

• What can be done to mitigate the risk?

• What are the issues of global supply chains?– Choosing between Hong Kong & China

???

20

What is the solution?

21

Risk-based production sequencing • It refers to using speculative production capacity to

make low-risk products

• Postpone the production of higher-risk products until additional market information reduces their demand uncertainty

• Define the risk of producing a unit to be the expected cost of mismatched supply and demand for that unit

• As additional market information is available, the uncertainty about the sale of a product is reduced

• Generate probabilistic forecasts based on the subjective forecasts of a set of individuals

22

Early write

• Bring 25 (out of 800) largest retailers to Aspen in February. Accounts for 20% of sales.

• Put them up at the Ritz Carlton• They interact with Klaus Obermeyer, an

industry icon and founder of the company• They get an advance preview of the line• They order early

23

Lead time reduction

• Fabric dyer lead time of several months was a problem for Obermeyer

• 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

Fabric Producer

Fabric Dyer

Cut/Sew Factory

Denver Warehouse

Retailer

undyed goodsSport Obermeyer

Asia

Consumer

24

Revised planning calendar

25

Desk top tool run by user

Factories in China

DC in Denver

800 Ski Retailers

Product Sketches

Forecast Committee

Forecasts

Order 50% in November (For

Dec, Jan)

Order 50% in April (For Sept,

Oct, Nov)

Retailers order in

Feb & April

26

Elements of the Obermeyer process

• Early orders are highly predictive

• Early write: bring 25 largest retailers to Aspen to order early

• Cut lead times on expensive, long lead time component – dyed fabric

• Use committee forecast process to forecast forecasting errors

• Risk based production sequencing– Replace point forecast by probability distribution– Make predictable volume early.– Set production volumes based on likely forecast

accuracy and cost of over and under production.

27

Observations from past years’ Demand and Forecast

• Distribution show bell shaped normal distribution curve

• Standard Deviation of the demand for a style is approximately twice the SD of the buying committee’s forecast for that style

28

FACTORS AFFECTING UNPREDICTABILITY

• Short Life Time of Products (shrinking PLC)• SKU proliferation

RESULT : Markdowns as high as 30% and also some lost sale (How much?)

29

Risk based production

• What is risk?– How to quantify risk?

• How to predict what people will buy?

30

How to quantify risk? • Standard Deviation and Co-efficient of

Variation• Expected profit value

– 0.24 P *pi +0.08 P* (1-pi)

31

Similarity with “Newspaper boy problem”?

32

Production Planning for Short Life Cycle Products

It’s undesirable to make things that do not sell & also not to make things that sell….– Find Probability of Sale

• How to find µ and σ?

• How much to produce & When– Cannot postpone till demand is known– What should be the strategy?

• Production Capacity– Speculative & Reactive– How to use Speculative?

µ

33

How to solve?• Can the entire production happen

after Las Vegas??

• Speculative and reactive production capacity– How much?

• How to allocate?

34

How to solve?

• How to allocate?– Product price– Demand uncertainty– Expected Demand

• How to rank the parkas based on risk– Risk based production sequencing

• Make low risk products and postpone the production of high risk products until additional market information is available

• Grade parkas based on risk

• Do it for each variant

35

Buying Committee Forecasts

Style Price Avg. Forecast (µ)

2 × SD (σ) or SD of actual demand

CV

Gail 110 1017 388 0.3815

Isis 99 1042 646 0.6200

Entice 80 1358 496 0.3650

Assault 90 2525 680 0.2693

Teri 123 1100 762 0.6927

Electra 173 2150 807 0.3753

Stephanie 133 1113 1048 0.9416

Seduced 73 4017 1113 0.2770

Anita 93 3296 2094 0.6353

Daphne 148 2383 1394 0.5850

20000

36

How to find production numbers for 10,000 units?

Can it be Σ (µ -σ)

or

Σi µi -k σi = Speculative Capacity?

How to find the value of k?

k = 1.0607 (to make the speculative capacity equal to 10,000)

37

Equally risky recommended quantities Style Equally Risky

quantity (µi –kσi) = Speculative Capacity

Avg. Forecast (µ)

2 × SD (σ) CV

Gail 606 1017 388 0.3815

Isis 357 1042 646 0.6200

Entice 832 1358 496 0.3650

Assault 1804 2525 680 0.2693

Teri 292 1100 762 0.6927

Electra 1295 2150 807 0.3753

Stephanie 02 1113 1048 0.9416

Seduced 2837 4017 1113 0.2770

Anita 1075 3296 2094 0.6353

Daphne 905 2383 1394 0.5850

10,005 20000

38

But there are minimum order quantity also?

• Find a safety factor for each style• Higher the safety factor safer to make it

early

39

Creating a safety factor (Ref. Articles by Fisher et al., 1994)

Safety Factor = Max (µ-2m, m-µ, 0)/ σ

Categorize styles into three types1. Expected Demand is more than twice the minimum

order quantity (m), SAFEST

2. Expected Demand is less than the minimum order quantity, MODERATE RISK

3. Expected Demand is less than twice m but more than m. RISKIEST

40

Safety Factors for m=600

Style µ σ Equal Risk Q

Safety Factors

Seduced 4017 1113 2837 2.530997

Assault 2525 680 1804 1.948529

Electra 2150 807 1295 1.1772

Anita 3296 2094 1075 1.000955

Daphne 2383 1394 905 0.848637

Entice 1358 496 832 0.318548

Gail 1017 388 606 0

Isis 1042 646 357 0

Teri 1100 762 292 0

Stephanie 1113 1048 2 0

41

Calculation of production qty.• Starting with the safest style, compute the

order quantity using the following formula: Order Qty. = Max [(600, µ-600-(Min SF × σ)]

• For example, if we produce only Seduce then Min. SF would be 2.531

• If we produce Seduce, Assault and Electra then Min. SF would be 1.177

• Total the aggregate quantity, if it has not reached 10,000 then add one more style

• Repeat this till we get an aggregate total of 10,000 parkas

42

Iteration I Style µ σ SF Min. SF Q Total

Quantity

Seduced 4,017 1,113 2.53 2.53 601 601

43

Iteration II Style µ σ SF Min. SF Q Total

Quantity

Seduced 4,017 1,113 2.53 1,247

Assault 2,525 680 1.95 1.95 600 1,847

44

Iteration III Style µ σ SF Min. SF Q Total

Quantity

Seduced 4,017 1,113 2.53 2104

Assault 2,525 680 1.95 1123

Electra 2150 807 1.18 1.18 600 3827

45

Iteration IV Style µ σ SF Min. SF Q Total

Quantity

Seduced 4,017 1,113 2.53 2304

Assault 2,525 680 1.95 1245

Electra 2,150 807 1.18 743

Anita 3,296 2,094 1.00 1.00 602 4894

46

Iteration V Style µ σ SF Min. SF Q Total

Quantity

Seduced 4,017 1,113 2.53 2472

Assault 2,525 680 1.95 1348

Electra 2,150 807 1.18 865

Anita 3,296 2,094 1.00 919

Daphne 2383 1394 0.8487 0.8487 600 6204

47

Iteration VI Style µ σ SF Min. SF Q Total

Quantity

Seduced 4,017 1,113 2.53 3063

Assault 2,525 680 1.95 1709

Electra 2,150 807 1.18 1293

Anita 3,296 2,094 1.00 2030

Daphne 2383 1394 0.8487 1340

Entice 1358 496 0.318 0.318 600 10,035

48But How to REDUCE?

Minimum Production Lot size Constraint

• How will the markdowns & stock out vary with production lot

Minimum order Quantity

Sto

ck o

ut

as a

per

cen

tage

of

sale

s

49

Reducing Minimum Lot size by

– Postponement– Flexible manufacturing systems

• GT, CELL DESIGNS etc.

– Investment in Technology (sewing technology)– Examine why HK min order qty is less than

China?

50But How to AUGMENT?

Augmenting Reactive Production Capacity

• How will the markdowns & stock out vary with reactive capacity?

Reactive Capacity (as a percentage of sales)

Mar

kd

own

/ Sto

ck o

ut

as a

per

cen

tage

of

sale

s

51

Augmenting Reactive Capacity

• Increasing reactive capacity only– Flexible work force, overtime, layoffs– Risky in Hong Kong (why?)– Subcontractors : Good option?

• Total Capacity Augmentation– Increase year round capacity– What is the problem?– Complimentary products

52

Augmenting Reactive Capacity

• Decrease Raw Material and Manufacturing Lead Times– Risk Pooling : Greige Fabric– Store fabric that is used by many products– Store accessories like zippers– Redesign the Product (to minimise varieties)

53

SCM Co-ordination• How should Obermeyer management think –short

term & long term- about sourcing from Hong Kong vs China?

• What is the role of Sports Obermeyer & OberSports– Manufacturer?– Marketer?– Designer– Co-ordinator?

• Supply chains work well with lesser intermediaries. So is it necessary to have Obersports?

54

Obersport :The Value proposition• How should we decide on disinter mediation

& re-intermediation in a supply chain

• What is the value of an intermediary– Aggregation– Economies– Place, Time utility– Transaction Cost Analysis

•

55

Role of Obersport

• Is there any value addition by Obersport?

• How should Obermeyer change its strategies if it is planning to source more from China?

56

Hongkong Vs China

• Wage rate– Productivity & Line fill rate

• Worker ability• Rejects & quality• Minimum order size• Throughput Time

• Surge Capacity

• WHAT IS THE IDEAL STRATEGY?