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Supply Chain Management Module

    Managing the Supply Chain » Key to matching demand with supply » Cost and Benefits of inventory Economies of Scale »

Palu Gear:

Inventory management of a retailer: EOQ + ROP » Levers for improvement Safety Stock » Hedging against uncertainty » Role of leadtime Improving Performance » Centralization & Pooling efficiencies » Postponement » Optimal Service Level Lin/Operations/Supply Chain Mgt 1

What is a Supply Chain?

1. Procurement or supply system

Raw Material supply points Movement/ Transport

2. Operating System 3. Distribution System

Raw Material Storage Movement/ Transport Manufacturing PLANT 1 Movement/ Transport

4. Sales or demand system

Finished Goods Storage Movement/ Transport A PLANT 2 PLANT 3  What makes for a “good” SC?

Lin/Operations/Supply Chain Mgt B WAREHOUSES (DCs) C MARKETS 2

US Vehicle Inventory

Lin/Operations/Supply Chain Mgt 3

Corporate Finance

Current Assets

Cash & Equivalents Short-term Investments AR Inventories Deferred income taxes other Total current assets Investments PPE other

Total assets Cisco

7/30/95 204,846 234,681 384,242 71,160 75,297 25,743 995,969 576,958 136,653 47747 1,757,327 21% 7%

Solectron

8/25/95 89,959 58,643 254,898 298,809 100% 24,049 726,358 203,609 10,888 940,855 12% 41% 100%  Inventories represent about 34% of current assets for a typical US company; 90% of working capital.

 For each dollar of GNP in the trade and manufacturing sector, about 40% worth of inventory was held.

 Average logistics cost = 21¢/sales dollar = 10.5% of GDP Lin/Operations/Supply Chain Mgt 4

Costs of not Matching Supply and Demand

 Cost of overstocking – liquidation, obsolescence, holding  Cost of under-stocking – lost sales and resulting lost margin Lin/Operations/Supply Chain Mgt 5

We never Talk anymore!

Magazine sales at newsstands as % of copies shipped to newsstands In Style People Vanity Fair Vogue The New Yorker GQ New York Esquire Rolling Stone Us Talk 64.7% 54.5% 45.6% 42.1% 39.9% 39.4% 35.1% 31.0% 28.0% 23.9% 18.0% Data for Oct. 1999 – Oct. 2000 Lin/Operations/Supply Chain Mgt 6

The Current Environment:

The Grocery Industry 1985-1992

Number of products in average supermarket 1985 1990 11,036 16,486 1992 2004 20,000 ??

20,000 2,000 1975 Lin/Operations/Supply Chain Mgt 1992 2002 7

A Key to Matching Supply and Demand

When would you rather place your bet?

A B A: B: C: D: Lin/Operations/Supply Chain Mgt A month before start of Derby The Monday before start of Derby The morning of start of Derby The winner is an inch from the finish line C D 8

Where is the Flow Time?

Buffer

Lin/Operations/Supply Chain Mgt

Waiting

Operation

Processing

9

Operational Flows

Lin/Operations/Supply Chain Mgt

Throughput R Inventory I FLOW TIME T

I = R T

Flow time

T

= Inventory

I

/ Throughput

R

10

Why do Buffers Build?

Why hold Inventory?

 Economies of scale – Fixed costs associated with batches – Quantity discounts – Trade Promotions  Uncertainty – Information Uncertainty – Supply/demand uncertainty  Seasonal Variability  Strategic – Flooding, availability Lin/Operations/Supply Chain Mgt

Cycle/Batch

stock

Safety

stock

Seasonal

stock

Strategic

stock 11

Palü Gear

: Retail Inventory Management & Economies of Scale  Annual jacket revenues at a

Palü Gear

retail store are roughly $1M.

Palü

jackets sell at an average retail price of $325, which represents a mark-up of 30% above what

Palü Gear

paid its manufacturer. Being a profit center, each store made its own inventory decisions and was supplied directly from the manufacturer by truck. A shipment up to a full truck load, which was about 3000 jackets, was charged a flat fee of $2,200. Typically, stores placed roughly two orders per year, each of about 1500 jackets. (

Palü

’s cost of capital is approximately 20%.) What order size would you recommend for a

Palü

network?

store in current supply manufacturer retailer Lin/Operations/Supply Chain Mgt 12

Economies of Scale: Inventory Build-Up Diagram

R

: Annual demand

rate

,

Q

: Number of jackets per replenishment order Inventory

Inventory Profile

: # of wind breakers in inventory over time.

 Number of orders per year =

R

/

Q.

Q R =

Demand rate  Average number of jackets in inventory =

Q

/2 .

Time

t

Lin/Operations/Supply Chain Mgt 13

Palü Gear

: evaluation of current policy of ordering

Q

= 1500 units each time

1.

What is average inventory

I

?

  

I = Q/2 =

Annual cost to hold one unit

H

= Annual cost to hold

I = Holding cost × Inventory

2.

How often do we order?

   Annual throughput

R

= # of orders per year =

Throughput / Batch size

Annual order cost =

Order cost × # of orders

3.

What is total cost?

 TC =

Annual holding cost + Annual order cost

= 4.

What happens if order size changes?

Lin/Operations/Supply Chain Mgt 14

Find most economical order quantity: Spreadsheet for a Palü Gear retailer

Number of units Number of per order/batch Batches per

Q

Year:

R/Q

50 100 62 31 150 200 21 15 250 300 350 400 450 500 510 520 530 540 550 600 12 10 9 8 7 6 6 6 6 6 6 5 650 700 750 800 850 900 1000 5 4 4 4 4 3 3

Annual Annual Setup Cost Holding Cost

$ 135,385 $ 67,692 $ $ 1,250 2,500 $ 45,128 $ 33,846 $ 3,750 $ 5,000 $ 27,077 $ 22,564 $ 19,341 $ 16,923 $ 15,043 $ 13,538 $ $ $ $ $ $ 6,250 7,500 8,750 10,000 11,250 12,500 $ 13,273 $ 13,018 $ 12,772 $ 12,536 $ 12,308 $ 11,282 $ 10,414 $ 9,670 $ 9,026 $ 8,462 $ 7,964 $ 7,521 $ 6,769 $ 12,750 $ 13,000 $ 13,250 $ 13,500 $ $ 13,750 15,000 $ 16,250 $ 17,500 $ 18,750 $ 20,000 $ $ $ 21,250 22,500 25,000

Annual Total Cost

$ 136,635 $ 70,192 $ 48,878 $ 38,846 $ 33,327 $ 30,064 $ 28,091 $ 26,923 $ 26,293 $ 26,038 $ 26,023 $ 26,018 $ 26,022 $ 26,036 $ 26,058 $ 26,282 $ 26,664 $ 27,170 $ 27,776 $ 28,462 $ 29,214 $ 30,021 $ 31,769 $160,000 $140,000 $120,000 $100,000 $80,000 $60,000 $40,000 $20,000 $ 0 Setup Cost Holding Cost Total Cost 100 200 300 400 500 600 700 800 900 1000 Order (batch) size Q Lin/Operations/Supply Chain Mgt 15

Economies of Scale: Economic Order Quantity

EOQ

R S H Q

: : : : Demand per year, Setup or Order Cost ($/setup; $/order), Marginal annual holding cost ($ per unit per year), Order quantity.

Q EOQ

 2

SR H C r

: Cost per unit ($/unit), : Cost of capital (%/yr),

H

=

r C .

2

SRH

Total annual costs

H Q/2:

Annual holding cost Lin/Operations/Supply Chain Mgt EOQ

S R /Q:

Annual setup cost Batch Size

Q

16

Optimal Economies of Scale: For a Palü Gear retailer

R = 3077 units/ year r = 0.20/year  Unit annual holding cost = H = C = $ 250 / unit S = $ 2,200 / order  Optimal order quantity = Q EOQ =  Number of orders per year = R/Q =  Time between orders = Q/R =  Annual order cost = (R/Q)S = $13,008.87/yr  Average inventory I = Q/2 =  Annual holding cost = (Q/2)H =$13,008.87/yr  Average flow time T = Lin/Operations/Supply Chain Mgt 17

Role of Leadtime

L

:

Palü Gear

cont.

 The lead time from when a

Palü Gear

retailer places an order to when the order is received is two weeks. If demand is stable as before, when should the retailer place an order?

 I-Diagram:  The two key decisions in inventory management are: – How much to order?

– When to order?

Lin/Operations/Supply Chain Mgt 18

Learning Objectives: Batching & Economies of Scale

 Increasing batch size of production (or purchase) increases average inventories (and thus cycle times).

 Average inventory for a batch size of Q is Q/2.

 The optimal batch size trades off setup cost and holding cost.

 To reduce batch size, one has to reduce setup cost (time).

 Square-root relationship between Q and (R, S): – If demand increases by a factor of 4, it is optimal to increase batch size by a factor of 2 and produce (order) twice as often.

– If demand increases by a factor of 4, the flow time decreases by a factor of 2.

 An inventory policy must specify when to order (the ROP) and how much to order (the batch size).

Lin/Operations/Supply Chain Mgt 19

Demand uncertainty and forecasting

Year

1992 1993 1994 1995 1995 1997 1998 1999 2000 2001

Demand

194 251 320 267 233 223 266 252 251 331 Lin/Operations/Supply Chain Mgt 20

Demand uncertainty and forecasting

 Forecasts depend on (a) historical data and (b) “market intelligence.”  Forecasts are usually (always?) wrong.

 A good forecast has at least 2 numbers (includes a measure of forecast error, e.g., standard deviation).

 The forecast horizon must at least be as large as the lead time. The longer the forecast horizon, the less accurate the forecast.

 Aggregate forecasts tend to be more accurate.

Lin/Operations/Supply Chain Mgt 21

 

Palü Gear

: Service levels & inventory management

In reality, a

Palü Gear

store’s demand fluctuates from week to week. In fact, weekly demand at each store had a standard deviation of about 30 jackets  assume roughly normally distributed. Recall that average weekly demand was about 59 jackets; the order lead time is two weeks; fixed order costs are $2,200/order and it costs $50 to hold one jacket in inventory during one year.

Questions: 1.

If the retailer uses the ordering policy discussed before, what will the probability of running out of stock in a given cycle be?

2.

The

Palü

retailer would like the stock-out probability to be smaller. How can she accomplish this?

3.

Specifically, how does it get the service level up to 95%?

Lin/Operations/Supply Chain Mgt 22

How find

s

of lead time demand?

s

R

s

R

… s

R

Sum of

N independent

random variables, each with identical standard deviation s

R

, has standard deviation =  Applications: – Demand over the leadtime

L

has standard deviation = s R  

L

– Pooled demand over

N

regions or products has standard deviation = s R  

N

Lin/Operations/Supply Chain Mgt 23

Example: say we increase ROP to 140 (and keep order size at Q = 520)

1.

2.

On average, what is the stock level when the replenishment arrives? On average, what is the

inventory profile

?

500 3.

400 300 200 100 0 What is the probability that we run out of stock?

4.

How do we get that stock-out probability down to 5%?

Lin/Operations/Supply Chain Mgt 24

Safety Stocks

Inventory on hand

I

(

t

)

ROP I s

0

order

Q

order

Q L

order

L R

mean demand during supply lead time: m

= R L

safety stock

I s L

Time

t

Lin/Operations/Supply Chain Mgt 25

Safety Stocks & Service Levels: The relationship

Cycle Service Level (CSL) Stock-out probability

F(z)

I s

= z

s mean ROP demand during supply lead time  Raise ROP until we reach appropriate SL  To do numbers, we need:  Mean and stdev s of demand during lead time  Either Excel or tables with z - value such that CSL =

F(z)

Lin/Operations/Supply Chain Mgt 26

1. How to find service level (given ROP)?

2. How to find re-order point (given SL)?

   1.

2.

L

= Supply lead time,

D =N

(

R

, s

R

) = Demand per unit time is normally distributed with mean

R

and standard deviation s

R D L =N

( m

L

, s

L

) where m

L

=

RL

= Demand during the lead time and s

L

 s R 

L

, Given ROP, find SL = Cycle service level =

P

(no stock out) =

P

(demand during lead time <

ROP

) =

F

(

z*=

(

ROP-

m

L

)/ s

L

)

=

NORMDIST (

ROP

, m

L

, s

L

, True) Given SL, find ROP = m

L + I

s

=

m

L + z *

s

L

= NORMINV (SL, m

L

, s

L

) [use table] [or Excel] [use table to get [or Excel]

z *

] Safety stock

I s

=

z *

s

L

Reorder point

ROP =

m

L + I

s

Lin/Operations/Supply Chain Mgt 27

The standard normal distribution

F(z)

• Transform

X = N(

m,s

)

to

z = N(0,1) z =

(

X

m ) / s .

F

(

z

) = Prob(

N

(0,1) <

z

)

F(z)

0

z

• Transform back, knowing

z*

:

X*

= m

+ z*

s .

z

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

2.6

2.7

2.8

2.9

3.0

3.1

3.2

3.3

1.5

1.6

1.7

1.8

1.9

2.0

2.1

2.2

2.3

2.4

2.5

0.9772

0.9821

0.9861

0.9893

0.9918

0.9938

0.9953

0.9965

0.9974

0.9981

0.9987

0.9990

0.9993

0.9995

0.00

0.5000

0.5398

0.5793

0.6179

0.6554

0.6915

0.7257

0.7580

0.7881

0.8159

0.8413

0.8643

0.8849

0.9032

0.9192

0.9332

0.9452

0.9554

0.9641

0.9713

0.9778

0.9826

0.9864

0.9896

0.9920

0.9940

0.9955

0.9966

0.9975

0.9982

0.9987

0.9991

0.9993

0.9995

0.01

0.5040

0.5438

0.5832

0.6217

0.6591

0.6950

0.7291

0.7611

0.7910

0.8186

0.8438

0.8665

0.8869

0.9049

0.9207

0.9345

0.9463

0.9564

0.9649

0.9719

0.9783

0.9830

0.9868

0.9898

0.9922

0.9941

0.9956

0.9967

0.9976

0.9982

0.9987

0.9991

0.9994

0.9995

0.02

0.5080

0.5478

0.5871

0.6255

0.6628

0.6985

0.7324

0.7642

0.7939

0.8212

0.8461

0.8686

0.8888

0.9066

0.9222

0.9357

0.9474

0.9573

0.9656

0.9726

0.9788

0.9834

0.9871

0.9901

0.9925

0.9943

0.9957

0.9968

0.9977

0.9983

0.9988

0.9991

0.9994

0.9996

0.03

0.5120

0.5517

0.5910

0.6293

0.6664

0.7019

0.7357

0.7673

0.7967

0.8238

0.8485

0.8708

0.8907

0.9082

0.9236

0.9370

0.9484

0.9582

0.9664

0.9732

0.9793

0.9838

0.9875

0.9904

0.9927

0.9945

0.9959

0.9969

0.9977

0.9984

0.9988

0.9992

0.9994

0.9996

0.04

0.5160

0.5557

0.5948

0.6331

0.6700

0.7054

0.7389

0.7704

0.7995

0.8264

0.8508

0.8729

0.8925

0.9099

0.9251

0.9382

0.9495

0.9591

0.9671

0.9738

0.9798

0.9842

0.9878

0.9906

0.9929

0.9946

0.9960

0.9970

0.9978

0.9984

0.9989

0.9992

0.9994

0.9996

0.05

0.5199

0.5596

0.5987

0.6368

0.6736

0.7088

0.7422

0.7734

0.8023

0.8289

0.8531

0.8749

0.8944

0.9115

0.9265

0.9394

0.9505

0.9599

0.9678

0.9744

0.9803

0.9846

0.9881

0.9909

0.9931

0.9948

0.9961

0.9971

0.9979

0.9985

0.9989

0.9992

0.9994

0.9996

0.06

0.5239

0.5636

0.6026

0.6406

0.6772

0.7123

0.7454

0.7764

0.8051

0.8315

0.8554

0.8770

0.8962

0.9131

0.9279

0.9406

0.9515

0.9608

0.9686

0.9750

0.9808

0.9850

0.9884

0.9911

0.9932

0.9949

0.9962

0.9972

0.9979

0.9985

0.9989

0.9992

0.9995

0.9996

0.07

0.5279

0.5675

0.6064

0.6443

0.6808

0.7157

0.7486

0.7794

0.8078

0.8340

0.8577

0.8790

0.8980

0.9147

0.9292

0.9418

0.9525

0.9616

0.9693

0.9756

0.9812

0.9854

0.9887

0.9913

0.9934

0.9951

0.9963

0.9973

0.9980

0.9986

0.9990

0.9993

0.9995

0.9996

0.08

0.5319

0.5714

0.6103

0.6480

0.6844

0.7190

0.7517

0.7823

0.8106

0.8365

0.8599

0.8810

0.8997

0.9162

0.9306

0.9429

0.9535

0.9625

0.9699

0.9761

0.9817

0.9857

0.9890

0.9916

0.9936

0.9952

0.9964

0.9974

0.9981

0.9986

0.9990

0.9993

0.9995

0.9997

0.09

0.5359

0.5753

0.6141

0.6517

0.6879

0.7224

0.7549

0.7852

0.8133

0.8389

0.8621

0.8830

0.9015

0.9177

0.9319

0.9441

0.9545

0.9633

0.9706

0.9767

Lin/Operations/Supply Chain Mgt 28

Palü Gear

: Determining the required Safety Stock for 95% service

DATA:

R

= 59 jackets/ week

H

= $50 / jacket, year

S

= $ 2,200 / order s

R

= 30 jackets/ week

L

= 2 weeks

QUESTION:

What should safety stock be to insure a desired cycle service level of 95%?

ANSWER: 1.

Required # of standard deviations z* for SL of 95% =

2.

Determine s lead time demand =

3.

Answer: Safety stock

I s

= Lin/Operations/Supply Chain Mgt 29

Comprehensive Financial Evaluation: Inventory Costs of

Palü Gear

Cycle Stock (Economies of Scale) 1.1

Optimal order quantity

1.2

# of orders/year

1.3

Annual ordering cost per store

1.4

Annual cycle stock holding cost.

= 520 = 5.9

= $13,009 = $13,009

2. Safety Stock (Uncertainty hedge)

2.1 Safety stock per store

2.2

Annual safety stock holding cost = 70 = $3,500 .

3. Total Costs for 5 stores

Lin/Operations/Supply Chain Mgt

= 5 (13

,009 + 13,009 + 3,500) = 5 x $29,500 = $147.5K

.

30

Learning Objectives safety stocks

I s

z

* s

R L Safety stock

increases (decreases) with an increase (decrease) in:  demand variability or forecast error,  delivery lead time for the same level of service,  delivery lead time variability for the same level of service. Lin/Operations/Supply Chain Mgt 31

Improving Supply Chain Performance: 1. The Effect of Pooling/Centralization

Decentralized Distribution Centralization Distribution I s =100 I s =100 I s =100 I s =100

Lin/Operations/Supply Chain Mgt 32

Palü Gear’s

Internet restructuring: Centralized inventory management

 Weekly demand per store with standard deviation

H

= $ 50 / jacket, year

S

= $ 2,200 / order = 59 jackets/ week = 30 / week Supply lead time

L

= 2 weeks Desired cycle service level F(z*) = 95%.

Palü Gear

now is considering restructuring to an Internet store.

R

s

R

– =

5

Assuming Internet store is sum of the five stores and demands are independent.

59 = 295 jackets/week

average total demand over lead time

m = 

5

 s

L L

= 2

295 = 590.

30 = 67.1

STD of total demand over lead time =

2

67.1 = 94.9.

Lin/Operations/Supply Chain Mgt 33

Palü Gear’s

Internet restructuring: comprehensive financial inventory evaluation

1. Cycle Stock (Economies of Scale) 1.1

Optimal order quantity

1.2

# of orders/year

1.3

Annual ordering cost of e-store

1.4

Annual cycle stock holding cost = 5 = 

5

x 520 = 1163 x 5.9 = 13 = $29,089 = $29,089

2. Safety Stock (Uncertainty hedge)

2.1 Safety stock for e-store

2.2

Annual safety stock holding cost

3. Total Costs for consolidated e-store

Lin/Operations/Supply Chain Mgt = = 156 $7,800

Note: This is

5

3500 - cost of safety inventory at one store.

=

29,089 + 29,089 + 7,800 =

$65,980 = 147.5/

5

34

Learning Objectives: centralization/pooling

 Different methods to achieve pooling efficiencies: – Physical centralization – Information centralization – Specialization – Raw material commonality (postponement/late customization)  Cost savings are sqrt(# of locations pooled).

Lin/Operations/Supply Chain Mgt 35

Improving Supply Chain Performance:

2. Postponement & Commonality (HP Laserjet) Generic Power Production Process I: Unique Power Supply Unique Power Production Transportation Europe N. America Process II: Universal Power Supply Europe N. America Make-to-Stock Lin/Operations/Supply Chain Mgt Push-Pull Boundary Make-to-Order 36

Variety and Marketing/Operations: Be smart with product differentiation

High Low

Consumer Hierarchy Score

Low High • Braking system • Transmission • Electrical design • Chassis design • Exterior body panels • Engine block • Front & rear seats • Floor mats • Airbags & antilock system • Rear-view mirrors • Dashboard layout • Headlights • Cup holders • Remote keyless entry Source: Mohan Sawhney Lin/Operations/Supply Chain Mgt 37

Learning Objectives: Supply Chain Performance

 Pooling of stock reduces the amount of inventory – physical – information – specialization – substitution – commonality/postponement Single product Multi product  Tailored response (e.g., partial postponement) can be used to better match supply and demand  The entire supply chain must plan to customer demand Lin/Operations/Supply Chain Mgt 38

Finding the optimal service level: The newsvendor problem

Optimal Service Level

when you can order only once:

Palü Gear

 

Palü Gear’s

is planning to offer a special line of winter jackets, especially designed as gifts for the Christmas season. Each Christmas-jacket costs the company $250 and sells for $450. Any stock left over after Christmas would be disposed of at a deep discount of $195. Marketing had forecasted a demand of 2000 Christmas-jackets with a forecast error (standard deviation) of 500 How many jackets should

Palü Gear’s

order?

Demand Forecast for Christmas jackets

18% 16% 15.9% 14.6% 14.6% 14% 12% 10% 11.6% 11.6% 7.8% 7.8% 8% 6% 4.5% 4% 2.2% 2% 0.5% 0% 600 Lin/Operations/Supply Chain Mgt 0.9% 800 1000 1200 1400 1600 1800 2000 2200 4.5% 2.2% 0.9% 0.5% 2400 2600 2800 3000 3200 3400 40

In reality, you do not know demand for sure…

Impact of uncertainty if you order the expected

Q =

2000 IF: THEN:

Demand Order/Stock Q = Probability of Demand

600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 3200 3400 0.5% 0.9% 2.2% 4.5% 7.8% 11.6% 14.6% 15.9% 14.6% 11.6% 7.8% 4.5% 2.2% 0.9% 0.5% Expected values: 2000

units sold

units overstock

600 800 1000 1200 1400 1600 1800 2000 2000 2000 2000 2000 2000 2000 2000 1802 1400 1200 1000 800 600 400 200 0 0 0 0 0 0 0 0 198

units understock

0 0 0 0 0 0 0 0 200 400 600 800 1000 1200 1400 198

Profit ($000)

$ 43 $ 94 $ 145 $ 196 $ 247 $ 298 $ 349 $ 400 $ 400 $ 400 $ 400 $ 400 $ 400 $ 400 $ 400 $ 350 Lin/Operations/Supply Chain Mgt 41

What happens if you change your order level to hedge against uncertainty?

Performance for all possible

Q

using Excel:

Order size Q

600 800 1000 1200 1400 1600 1800 2000 2200

2400

2600 2800 3000 3200 3400

Probability Demand = Q

0.5% 0.9% 2.2% 4.5% 7.8% 11.6% 14.6% 15.9% 14.6%

11.6%

7.8% 4.5% 2.2% 0.9% 0.5% Expected

units sold

600 799 996 1189 1373 1541 1686 1802 1886

1941

1973 1989 1996 1999 2000 Expected

units overstock

0 1 4 11 27 59 114 198 314

459

627 811 1004 1201 1400 Expected Profit Expected

units understock

1400 1201 1004 811 627 459 314 198 114

59

27 11 4 1 0

Expected

Profit

$ 120 $ 160 $ 199 $ 237 $ 273 $ 305 $ 331 $ 350 $ 360

$ 363

$ 360 $ 353 $ 344 $ 334 $ 323 $400 $360 $320 $280 $240

- C

o

= - 55

$200 $160 $120 600

+ 200 = C

u

800 1000 1200 1400 1600 1800 2000 2200 2400 2600

Order/Stock Quantity Q

2800 3000 3200 3400

Towards the newsboy model S

uppose you placed an order of 2000 units but you are not sure if you should order more.

What happens if I order one more unit (on top of

Q =

2000)?

Sell the extra unit with probability … Do not sell the extra unit with probability … Lin/Operations/Supply Chain Mgt DP = …..

DP = Expected profit from additional unit E( DP ) = …..

So? ... Order more?

43

The Value-maximizing Service Level

The newsvendor formula

In general: raise service level (i.e., order an additional unit)

if and only if

E(

DP

) =

(1-

SL

) 

C u

SL

C o

> 0 Sell Do not sell  Thus, optimal service level

SL

*

C u C

u C o p p

1  1 

c p

2 (= Newsvendor formula) • Example: use formula for Palu-Gear Christmas order 1.

2.

 SL * = So how much should Palu order then?

How does this compare to forecasted demand of 2000?

Lin/Operations/Supply Chain Mgt

Demand

1,000 1,200 1,400 1,600 1,800 2,000 2,200 2,400 2,600 2,800 3,000 3,200

Prob. Cum. Prob.

1% 1% 3% 6% 10% 13% 16% 16% 13% 10% 6% 3% 1% 1% 2% 5% 12% 21% 34% 50% 66% 79% 88% 95% 98% 99% 44

Accurate response: Find optimal

Q

from newsboy model

 Cost of overstocking by one unit =

C

o – the out-of-pocket cost per unit stocked but not demanded – “Say demand is one unit below my stock level. How much did the one unit overstocking cost me?” E.g.: purchase price - salvage price.

 Cost of understocking by one unit =

C u

– The opportunity cost per unit demanded in excess of the stock level provided – “Say demand is one unit above my stock level. How much could I have saved (or gained) if I had stocked one unit more?” E.g.: retail price - purchase price.

Given an order quantity

Q

, increase it by one unit if and only if the expected benefit of being able to sell it exceeds the expected cost of having that unit left over.

Marginal Analysis: Order more as long as

F

(

Q

) <

C u

/ (

C

o +

C

u )  = smallest

Q

such that service level

F

(

Q

) > critical fractile

C u

/ (

C

o +

C

u ) Lin/Operations/Supply Chain Mgt 45

Where else do you find newsvendors?

 Deciding on economic service level  Benefits: Flexible Spending Account decision  Capacity Mgt Lin/Operations/Supply Chain Mgt 46

Whistler Blackcomb Ski & Snowboard School

 Has over 1,200 instructors (including part timers).

– Organized into 36 pods.

 Manager of a pod must determine today the number of instructors to call in for tomorrow’s lessons.

– A master schedule is generated on a monthly basis but adjusted daily.

 Skiers can pre-book (i.e., reserve) a lesson or can walk in.

– Total demand depends on a number of factors: Day of the week, point in the season, US/Canadian exchange rate etc.

Lin/Operations/Supply Chain Mgt 47

Whistler Blackcomb Economics of Individual Lessons

Today 8:00am 12:00pm 3:00pm 5:00pm 9:00pm Tomorrow 8:00am Begin morning lessons (demand realized) Afternoon lessons begin Finish lessons for day Determine forecast demand and instructor requirements for tomorrow Call instructors to fill in or to call off Pre-bookings made for today  If unable to staff a lesson, lose $320 in revenue.

 Instructors are paid $40 per hour for lessons.

– An instructor who gives a lesson is paid for three hours.

– An instructor on stand by who does not give lesson is paid for two hours.

Lin/Operations/Supply Chain Mgt 48

Whistler Blackcomb Staffing Decision

 A forecasting model predicts that demand for individual lessons tomorrow is 56.

– Error in forecast (i.e., standard deviation) is 3.12.

 If demand is normally distributed, how many instructors should be called in?

– Assume each instructors teaches just one individual lesson.

Lin/Operations/Supply Chain Mgt 49

Whistler Blackcomb Analysis

 If one too many instructors, must pay for two hours.

– C o = 2 × 40 = $80.

 If one too few instructors, lose margin on a lesson.

– C u = 320 – (3 × 40 ) = 320 – 120 = $200.

 Critical fractile = C u /(C o +C u )=200/(200+80) = 71.4%.

 z 71.4

= Normsinv(0.714) = 0.5659.

 Optimal decision for normal distribution:

Q = μ + z 71.4

× σ = 56 + 0.5659 × 3.12 = 57.7 ≈ 58

Lin/Operations/Supply Chain Mgt 50

Goal of a Supply Chain

Match Demand with Supply It is hard … Why?

Hard to Anticipate Demand Forecasts are wrong… why?

There is lead time… why there is lead time?

Lead time (flow time) = Activity time+ Waiting Time Because there is waiting time..

Why there is waiting time? There is inventory in the SC (

Little’s Law)

Why there is Inventory?

Economies of Scale

There are fixed costs of ordering/production Q*= 2

SR H

Implications:

How fast cycle inventory grows if demand grows.

How much to invest in fixed cost reduction to reduce batch size.

Uncertainty

Forecast Error

Safety Stock Is

= z s R

L

Implications:

Is z (service level appropriate) Reduce Lead time Reduce s R

Seasonality

Implications:

Is z (service level appropriate) Reduce Lead time Reduce s R Where does s R come from?

Balance overstocking and understocking Newsboy Problem …

Critical Fractile = 1- P(stockout)

Customer Demand Uncertainty

Normal Variations… How do we deal with it?

Aggregation

•Physical •Information •Specialization •Component Commonality •Postponement

Bullwhip Effect

Causes

•Demand Signaling •Rationing •Batching •Promotions

How do we deal with it?

•Make the SC more visible •Align Incentives