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Pricing and Customer Value Phil Kaminsky [email protected] David Simchi-Levi Philip Kaminsky Edith Simchi-Levi

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Page 1: Ch.10PricingValue

Pricing and Customer Value

Phil [email protected]

David Simchi-LeviPhilip Kaminsky

Edith Simchi-Levi

Page 2: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Outline

Customer Value The Fundamentals of Pricing Strategies

– Revenue Management & Customized Pricing Mail-in-Rebate strategies Dynamic Pricing in SCM

– Delayed Pricing vs. Delayed Production

Page 3: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Customer Value How should a company measure the value of its products or services? The emphasis has moved from internal measures such as quality to

customer satisfaction measures. The supply chain has a huge impact on perceived customer value:

– Prices vs. service?– Delivery speed vs. price?– Specialization or one-stop shopping?

Recall that responding to customer requirements is a basic part of supply chain management.

Customer value drives changes in the supply chain, and is a critical input in determining the type of supply chain for a particular product– Large inventories– High level of customization

Page 4: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

The Dimensions of Customer Value

Conformance to requirements– Offer what the customer wants– Demand impacts the supply chain

Product Selection– A proliferation of options makes the supply chain difficult to manage– Three trends

Specialty stores (Starbucks, Subway) Megastores (Wal-Mart, Target) Specialized Megastores (Home Depot, OfficeMax)

– Dealing with the proliferation: Build-to-order Centralized inventories A fixed set of options

Page 5: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

The Dimensions of Customer Value

Price and Brand– Pricing is a key part of the customer experience

The correct supply chain supports the correct price Wal-mart

– Brand works hand in hand with price As the number of salespeople decreases, the value of brand increases This is particularly true on the internet

Value Added Services– It is hard to compete on price alone– Value added services are on the rise due to

Commoditization of products The need to get closer to the customer Improving information technology

Relationships and Experiences– An increased connection between the firm and its customers

Dell manages the PC’s of large customers 3PL The Sony store

Page 6: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Smart Pricing? Dell:

– Same product is sold at a different price to different consumers (private/small or large business/government/academia/health care)

– Price of the same product for the same industry varies Amazon

– Books.com had a lower price than Amazon 99% of the time, yet Amazon had 80% of the market in 2000 while Books.com only 2%

Nikon, Sharp…– Mail-In-Rebate

Boise Cascade office– Prices of 12,000 items sold on-line may change as often as daily

Page 7: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue Management Example:

– A cruise ship with C=400 identical cabins– The Price-Quantity relationship

Page 8: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue Management

Price

No. seats

2000

1000

P=2000-2Q

Page 9: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue Management Example:

– A cruise ship with C=400 identical cabins– The Price-Quantity relationship

What is the price that the company should charge to maximize revenue?

Page 10: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue ManagementPrice

No. seats

P0=1200

C=400

Revenue=480,000

Page 11: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue ManagementPrice

No. seats

P0=1200

C=400

Money on the Table=160,000

Page 12: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue ManagementPrice

No. seats

P2=1600

Q2=200

Page 13: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue ManagementPrice

No. seatsC=400

P1=1200

Page 14: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue ManagementPrice

No. seatsQ1 =400

P1=1200

Q2=200

P2=1600

Revenue=1600(200) + 1200(400-200)=560,000

Page 15: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue Management Can we increase revenue more?

Page 16: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue ManagementPrice

No. seatsQ1 =400

P1=1200

Q2=200

P2=1600

P3=1800

Q3=100

Revenue=1800(100) + 1600(200-100) + 1200(400-200)=580,000

Page 17: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

How can the firm prevent customers from moving from one class to another?

Leisure

Travelers

Business

TravelersNo

Offer

NoDemand

Sensitivity to Price

Sensitivity to DurationSensitivity to Flexibility

High Low

Low

High

Page 18: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue Management “Allocating the right type of capacity to the right

kind of customer at the right price so as to maximize revenue or yield”

Traditional Industries: – Airlines– Hotels– Rental Car Agencies– Retail Industry

Page 19: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Traditional Requirements Perishable inventory Limited capacity Ability to segment markets

– early-bird booking– over the weekend

Product sold in advance Fluctuating demand

Page 20: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Airline Revenue Management

Two components of airline revenue maximization:– Customized Pricing:

Various “fare products” offered at different prices for travel in the same O-D market

– Yield Management (YM): Determines the number of seats available to each

“fare class” on a flight, by setting booking limits on low fare seats

Page 21: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue Management:Yield Management

There are only two price classes– Leisure: (f2) $100 per ticket

– Business: (f1) $250 per ticket Total available capacity= 80 seats Distribution of demand for business class is

known

Page 22: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Business Class: Demand Distribution

Probability

0

0.05

0.1

0.15

0.2

0.25

0.3

0 5 10 15 20 25 30

Demand for Business Class

Page 23: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue Management:Capacity Allocation

There are only two price classes– Leisure: (f2) $100 per ticket

– Business: (f1) $250 per ticket Total available capacity= 80 seats Distribution of demand for business class is

known Enough demand for the leisure class

Page 24: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue Management:Capacity Allocation

Objective: How many seats to allocate to the business class to maximize expected revenue

Page 25: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Expected Revenue

Expected Revenue

7500

8000

8500

9000

9500

10000

0 5 10 15 20 25 30 35

Business Class

Page 26: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Expected Revenue

Expected Revenue

7500

8000

8500

9000

9500

10000

0 5 10 15 20 25 30 35

Business Class

Page 27: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Revenue Management:Capacity Allocation

Optimality Condition: Choose the number of seats for the business class such that marginal revenue from each class is the same

Page 28: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Optimality Condition

Margina Revenue Business

0

50

100

150

200

250

300

0 5 10 15 20 25 30 35

Page 29: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Optimality Condition

Margina Revenue Business

0

50

100

150

200

250

300

0 5 10 15 20 25 30 35

Marginal Revenue Leisure

Page 30: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Optimality Condition

Margina Revenue Business

0

50

100

150

200

250

300

0 5 10 15 20 25 30 35

Marginal Revenue Leisure

Page 31: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Benefits of Revenue Management in the Airline Industry

Evidence of airline revenue increases of 4 to 6 percent:– With effectively no increase in flight operating costs

RM allows for tactical matching of demand vs. supply:– Booking limits can help channel low-fare demand to

empty flights– Protect seats for highest fare passengers on forecast

full flights

Page 32: Ch.10PricingValue
Page 33: Ch.10PricingValue
Page 34: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Mail-in-Rebate What is the manufacturer trying to achieve

with the rebate?– Why the manufacturer and not the retailer?

Should the manufacturer reduce the wholesale price instead of the rebate?

Are there other strategies that can be used to achieve the same effect?

Page 35: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Mail-in-Rebate A Retailer and a manufacturer.

– Retailer faces customer demand.– Retailer orders from manufacturer.

Selling Price=?

Wholesale Price=$900

Retailer Manufacturer

Variable Production Cost=$200

Page 36: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Demand-Price Relationship

Demand

Price

10000

2000

P=2000-0.2Q

Page 37: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Retailer Expected Profit (No Rebate)

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

500 1,000 1,500 2,000 2,500 3,000 3,500 3,654 4,110 4,567 4,547

Order

Reta

iler E

xpec

ted

Prof

it

Page 38: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Retailer Expected Profit (No Rebate)

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

500 1,000 1,500 2,000 2,500 3,000 3,500 3,654 4,110 4,567 4,547

Order

Reta

iler E

xpec

ted

Prof

it

$1,370,096

Page 39: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Manufacturer Profit (No Rebate)

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

500

1,000

1,500

2,000

2,500

3,000

3,500

3,654

4,110

4,567

4,547

4,961

5,374

5,788

6,201

6,614

7,028

7,441

7,855

Order

Man

ufac

ture

r Pr

ofit

Page 40: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Manufacturer Profit (No Rebate)

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

500

1,000

1,500

2,000

2,500

3,000

3,500

3,654

4,110

4,567

4,547

4,961

5,374

5,788

6,201

6,614

7,028

7,441

7,855

Order

Man

ufac

ture

r Pr

ofit

$1,750,000

Page 41: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Retailer Expected Profit ($100 Rebate)

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,110 4,567 4,547 4,961

Order

Ret

aile

r Exp

ecte

d Pr

ofit

Page 42: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Retailer Expected Profit ($100 Rebate)

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,110 4,567 4,547 4,961

Order

Ret

aile

r Exp

ecte

d Pr

ofit

$1,644,115

Page 43: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Manufacturer Profit ($100 Rebate)

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,110

4,567

4,547

4,961

5,374

5,788

6,201

6,614

7,028

7,441

7,855

8,268

Order

Man

ufac

ture

r Pr

ofit

Page 44: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Manufacturer Profit ($100 Rebate)

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,110

4,567

4,547

4,961

5,374

5,788

6,201

6,614

7,028

7,441

7,855

8,268

Order

Man

ufac

ture

r Pr

ofit

$1,810,392

Page 45: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Retailer Expected Profit (Reduced Wholesale Price $100 )

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,110 4,567 5,024

Order

Ret

aile

r E

xpec

ted

Pro

fit

Page 46: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Retailer Expected Profit (Reduced Wholesale Price $100 )

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,110 4,567 5,024

Order

Ret

aile

r E

xpec

ted

Pro

fit

$1,654,508

Page 47: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Manufacturer Profit (Reduced Wholesale Price $100)

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

3,500,000

4,000,000

4,500,000

5,000,000

500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,110 4,567 5,024 4,961 5,374 5,788 6,201 6,614 7,028 7,441 7,855

Order

Man

ufac

ture

r Pro

fit

Page 48: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Manufacturer Profit (Reduced Wholesale Price $100)

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

3,500,000

4,000,000

4,500,000

5,000,000

500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,110 4,567 5,024 4,961 5,374 5,788 6,201 6,614 7,028 7,441 7,855

Order

Man

ufac

ture

r Pro

fit

$1,800,000

Page 49: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Mail-in-Rebate

Strategy Retailer Manufacturer TotalNo Rebate 1,370,096 1,750,000 3,120,096 With Rebate ($100) 1,644,115 1,810,392 3,454,507 Reduce Wholesale P ($100) 1,654,508 1,800,000 3,454,508

Page 50: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Mail-in-Rebate

Strategy Retailer Manufacturer TotalNo Rebate 1,370,096 1,750,000 3,120,096 With Rebate ($100) 1,644,115 1,810,392 3,454,507 Reduce Wholesale P ($100) 1,654,508 1,800,000 3,454,508 Global Optimization 3,929,189

Page 51: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Managerial Insights Mail in Rebate allows supply chain partners

to move away from sequential strategies toward global optimization– Provides retailers with upside incentive

Mail in Rebate outperforms wholesale price discount for manufacturer

Other advantages of rebates:– Not all customers will remember to mail them in– Gives manufacturer better control of pricing

Page 52: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Smart Pricing Customized Pricing

– Revenue Management Techniques Distinguish between customers according to their

price sensitivity– Influence retailer pricing strategies– Move supply chain partners toward global

optimization

Page 53: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

Smart Pricing Dynamic Pricing

– Changing prices over time without necessarily distinguishing between different customers

– Find the optimal trade-off between high price and low demand versus low price and high demand

Page 54: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

When does Dynamic Pricing Provide Significant Profit Benefit?

Limited Capacity Demand Variability Seasonality in Demand Pattern Short Planning Horizon

Page 55: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

The Internet makes Smart Pricing Possible

Low Menu Cost Low Buyer Search Cost Visibility

– To the back-end of the supply chain allows to coordinate pricing, production and distribution

Customer Segmentation– Difficult in conventional stores and easier on the Internet

Testing Capability

Page 56: Ch.10PricingValue

McGraw-Hill/Irwin © 2003 Simchi-Levi, Kaminsky, Simchi-Levi

A Word of Caution Amazon.com experimented with dynamic

pricing – customers responded negatively Coca-Cola distributors rebelled against a

seasonal pricing scheme Opaque fares (priceline.com, hotwire.com)

– Determining the correct mix of opaque and regular fares is difficult.