1 Demand and Revenue Management Anton J. Kleywegt April 2, 2008.

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Demand and Revenue Management

Anton J. Kleywegt

April 2, 2008

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Revenue Management

What is Revenue Management Why do Revenue Management Pricing Optimization Demand Modeling and Forecasting

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What is Revenue Management

Management of inventory, distribution channels and prices to maximize profit over the long run

Selling the right product to the right customer at the right time at the right price

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Revenue Management involves the following activities Demand data collection Demand modeling Demand forecasting Pricing optimization System implementation and

distribution

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Airline industry How many seats to make available at each of the listed

fares, depending on the OD pair, time of year, time of week, remaining seats available, remaining time until departure

What contracts and prices to provide to corporations How many seats to make available to consolidators and

travel agents (if at all), and at what prices How much capacity to make available to cargo shippers

and freight forwarders, and at what prices

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Hotel industry How much to charge for a room depending on

the location, type of room, time of year, time of week, duration of stay

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Ocean cargo industry Which types of contracts to enter into with

shippers How much capacity to commit to each shipper Which contract prices to have for each shipper How to vary prices as a function of direction of

trade, commodity, and time of year

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Car rental industry How much to charge for a rental car depending

on the class of car, time of year, time of week, duration of rent

Restaurant industry How much to charge for lunch vs dinner

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What is Revenue Management Manufacturing industry

Make-to-stock: dynamic pricing of inventory Make-to-order: dynamic pricing of orders, how

much discount to give for orders in advance Make-to-stock and make-to-order: prices of

advance orders vs prices of inventory

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What is Revenue Management Retail industry Example: fashion apparel industry

Products in fashion for a single season Retailer wants to sell available inventory for

maximum profit Prices higher at start of season Retailer has to decide when to mark prices

down, and by how much

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What is Revenue Management Entertainment ticket pricing Example: opera houses let their ticket prices depend on

The performance The reviews received so far Location of seat in opera house Day of the week of the performance Time of the day of the performance Time of performance in the season Remaining time until the performance Number of remaining seats available

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What is Revenue Management Golf courses

Variable pricing: Choose prices to vary by time of day day of week season of year

Round duration control control tee-time interval control uncertainty in arrival time control uncertainty in duration

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Hospital Contract Case Study

Major customers of hospitals Insurance companies Medicare Medicaid Individuals

Hospital contracts with major customers Discount-off-listed-charges contracts Per-diem contracts Case-rate contracts Capitation contracts

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Example of setting per-diem rates

ICU Patient Length of Stay

0%2%4%6%8%10%12%14%16%

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Number of Days

% o

f P

ati

en

ts

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Example of setting per-diem rates Observe that most patients stay for only a few

days, although a few patients make the average length of stay quite high

Stratified per-diem rates Charge more per day to patients who stay for only a

few days Results

Higher average revenue Lower standard deviation of revenue

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Higher average revenue clearly beneficial to the hospital

Lower standard deviation of revenue Beneficial to the hospital?

Yes. More predictable revenue Beneficial to the insurance company?

Yes. More predictable costs

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Overbooking may be part of revenue management Overbooking important practice in many

industries that use reservations, and where cancellations or no-shows may occur airlines hotels car rental cruise lines restaurants contractors (construction etc)

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Overbooking Important trade-off between opportunity cost of unused

resources if cancellations or no-shows cause resources to be wasted, and cost of oversales

In 1960’s, Simon and Vickrey proposed the use of auctions to allocate airline seats in case of oversales

Airlines rejected idea for many years Nowadays, reverse Dutch auctions are widely used to

allocate airline seats in case of oversales, and seem to be widely accepted

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Dynamic pricing and the bullwhip effect Dynamic pricing can increase demand

variability The case of Campbell Soup

Wild swings in demand and in shipments of chicken noodle soup from the manufacturer to distributors and retail stores

Increase in production, storage and logistics costs Frequent stockouts resulting in lost sales

The culprit: Trade promotions!

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Dynamic pricing and the bullwhip effect Dynamic pricing can be used to decrease demand

variability Peak load pricing: lower prices during off-peak times,

higher prices during peak times Airlines Hotels Golf courses Electricity wholesale market Oil/gasoline?

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Revenue Management may involve price discrimination, but it does not have to

P=130-QUnit cost = 10Firm’s profits under single price:(130-Q-10)QP

qMC=10

130

130

60

70

Consumer surplus=1800

Deadweight loss=1800

Firm profits=3600

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Price Discrimination (continued)P=130-QUnit cost = 10What if the firmcould segmentthe market and charge two different prices?

P

q

MC=10

130

130

80

90

Consumer surplus=1600

Deadweight loss=800

Firm profits=4800

50

40

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Price Discrimination (continued)

P

q

MC=10

130

130

80

110 Consumer surplus=1000

Deadweight loss=200

Firm profits=6000

90

40

70

50

30

20 60 100

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Price Discrimination (continued)

Perfect pricediscrimination

P

q

MC=10

130

130

Consumer surplus=0Deadweight loss=0Firm profits=7200

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What is Revenue Management The same product sold at different times for different

prices is not necessarily price discrimination, because at different times...

the production or distribution costs may be different inventory costs were incurred to keep the product in stock until a

later time the product value may change over time, such as perishable or

maturing or seasonal products, fashion goods, antiques. the remaining inventory may be different interest is earned if product is sold at an earlier time consumers value products differently at different points in time locking sales in early reduces uncertainty

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It is not spam

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Fairness and Legal Issues

Depending on the industry, there may be legal obstacles to revenue management

Examples Regulated prices of utilities (this is changing) Prices in airline industry were regulated until 1978 -

price and quantity changes had to be approved by CAB Pricing in ocean cargo industry was regulated until

1999 - carriers had to provide all shippers with the same essential contract terms

Spot market pricing in ocean cargo industry is still regulated - 30 days notice required for price increases

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Golf course examples Kimes and Wirtz survey results (1 = extremely

fair, 7 = extremely unfair) Time-of-day pricing: 3.41 Varying price (for example, as function of bookings

on hand): 6.16 Two-for-one coupons for off-peak use: 1.80 Time-of-booking pricing: 5.12 Reservation fee/Charge for no-shows: 3.19 Tee-time interval pricing: 3.95

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Amazon.com example Fall 2000, Amazon conducted experiment to try to

determine price sensitivity of demand for DVDs Discounts between 20% and 40% offered randomly Customers who visited amazon.com multiple times

noticed changing prices Furious response by customers and press, suspecting

Amazon varied price by demographics Why are varying airline prices accepted by most, and

not varying DVD prices?

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Why do Revenue Management

Success stories American Airlines increased annual revenue with $500

million through revenue management Delta Airlines increased annual revenue with $300 million

through revenue management Marriott hotels increased annual revenue with $100 million

through revenue management National Car Rental was saved from liquidation with

revenue management Canadian Broadcasting Corporation increased revenue with

$1 million per week

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Why do Revenue Management

Increasing competition Fewer restriction on international trade More efficient international transportation Low cost foreign competitors Competitors use revenue management Use revenue management to stay on top

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Demand Forecasting

The first law of forecasting: The forecast is always wrong

Sources of forecast error: Modeling error Parameter error Measurement error

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It is very important to understand and model customer behavior accurately

Incorrect models of customer behavior can lead not only to suboptimal prices, but can lead to the systematic deterioration of models, prices, and profits over time – the spiral-down effect

Demand Modeling

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Spiral-down effect in airline revenue management For many years, airlines have used following simple

model of customer behavior Some time before departure, customer requests a ticket in a

particular fare class Airline accepts or rejects the request

Above model describes the way airline reservations systems work

However, it does not accurately describe the way customers behave

Demand Modeling

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Spiral-down effect in airline revenue management Low fare tickets and high fare tickets Airlines set aside chosen number of seats for

high fare tickets Airlines use observed sales to estimate the

supposed “demand for high fare tickets”

Demand Modeling

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Spiral-down effect in airline revenue management Spiral-down effect:

Airline allows some low fare sales Some flexible customers (not modeled by the airlines) willing to

buy high fare if that is the only option, now buy low fare tickets Airlines observe more low fare sales and less high fare sales –

decrease their estimate of “high fare demand” Airlines set aside fewer seats for high fare tickets, and allow

more low fare sales More customers buy low fare tickets, and the spiral down

continues Spiral-down effect is the consequence of an incorrect

model of customer behavior

Demand Modeling

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Forecasting methods Judgmental methods Statistical forecasting methods

Demand Forecasting

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Judgmental forecasting methods “Expert” opinion Questionable: See the articles

Armstrong, J.S., “How Expert Are the Experts?”, Inc, pp.15-16, 1981

Armstrong, J.S., “The Seer-Sucker Theory: The Value of Experts in Forecasting”, Technology Review, pp.16-24, 1980

Consensus methods, such as Delphi technique

Demand Forecasting

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Statistical forecasting methods Non-causal methods

Exponential smoothing Time series methods

Causal methods Linear regression Nonlinear regression Discrete choice models (logit, probit, etc)

Whatever the method, the basic approach is to find systematic behavior in data that one has reason to believe will continue in the future

Demand Forecasting

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Forecasting software surveys: Yurkiewicz, J., “Forecasting: Predicting Your Needs”, OR/MS

Today, volume 31, number 6, pp. 44-52, December 2004, <http://lionhrtpub.com/orms/surveys/FSS/fss-fr.html>.

Swain, J. J., “Desktop Statistics Software: Serious Tools for Decision Making”, OR/MS Today, volume 26, number 5, pp. 50-61, October 1999.

Swain, J. J., “Looking for Meaning in an Uncertain World”, OR/MS Today, volume 28, number 5, pp. 48-49, October 2001.

Swain, J. J., “2005 Statistical Software Products Survey: Essential Tools of the Trade”, OR/MS Today, volume 32, number 1, pp. 42-51, February 2005, <http://lionhrtpub.com/orms/surveys/sa/sa-survey.html>.

Demand Forecasting

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Questions?

1 Demand and Revenue Management Anton J. Kleywegt April 2, 2008.

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