aviation case study ppt_2

7/31/2019 Aviation Case Study Ppt_2

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Demand and Revenue Management


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Flow of Presentation Revenuw

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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 atthe right time at the right price


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What is Revenue Management Revenue Management involves the

following activities

Demand data collection

Demand modeling

Demand forecasting

Pricing optimization System implementation and distribution


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What is Revenue Management Airline industry

How many seats to make available at each of the listed

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

departure

What contracts and prices to provide to corporations

How many seats to make available to consolidators andtravel 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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What is Revenue Management Hotel industry

How much to charge for a room depending on

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


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What is Revenue Management 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 oftrade, commodity, and time of year


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What is Revenue Management 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, howmuch 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 pricesdepend 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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Hospital Contract Case Study 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

fP

atients


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Hospital Contract Case Study Example of setting per-diem rates

Observe that most patients stay for only a few

days, although a few patients make the averagelength 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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Hospital Contract Case Study 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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What is Revenue Management Overbooking may be part of revenue management

Overbooking important practice in many

industries that use reservations, and wherecancellations or no-shows may occur airlines

hotels

car rental cruise lines

restaurants

contractors (construction etc)


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What is Revenue Management Overbooking

Important trade-off between opportunity cost of unused

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

In 1960s, 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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What is Revenue Management 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 chickennoodle 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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What is Revenue Management 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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Price Discrimination Revenue Management may involve price

discrimination, but it does not have to

P=130-QUnit cost = 10Firms profitsunder single price:

(130-Q-10)QP

q

MC=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 firm

could segmentthe market andcharge twodifferent 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=0

Deadweight loss=0

Firm 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 atdifferent 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 ormaturing 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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What is Revenue Management 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 until1999 - carriers had to provide all shippers with thesame essential contract terms

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


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Fairness and Legal Issues 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 bookingson 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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Fairness and Legal Issues Amazon.com example

Fall 2000, Amazon conducted experiment to try todetermine price sensitivity of demand for DVDs

Discounts between 20% and 40% offered randomly

Customers who visited amazon.com multiple timesnoticed 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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Why do Revenue Management

At many companies, little cost-cutting juice can easily beextracted from operations. Pricing is therefore one of the fewuntapped levers to boost earnings, and companies that startnow will be in a good position to profit fully from the next

upturn. McKinsey Quarterly, 2003


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Revenue Management Optimization Control Methods

Resource Bucket Control Methods

Bid Price Control Methods

Dynamic Programming

Software


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Revenue Management Optimization Control Methods/Optimization Methods

Static Dynamic

Deterministic

StochasticLeg Based

OD based


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Revenue Management Optimization Resource Bucket Control Methods

If supply of different products are related, for exampleif different products use shared resources or capacity,

then revenue management should not be doneseparately for the different products

Also if demand for products are related, for examplecomplementary goods or substitutes

Examples Airlines: Itineraries with different origin-destination

pairs share the same flight legs (resource)

Hotels and rental cars: Multiple day bookings sharecapacity


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Revenue Management Optimization Bid price methods

Simple single-stage deterministic LP model

Input: Lines of flight (LOF)

The flights (legs/segments) each LOF traverses (flight-LOFincidence matrix A)

Fares f1,f2,,fkfor each LOF

Demand Dj for each LOF-fare combination j (not well-definednotion)

Capacity Qi of each flight (leg/segment) i

Primal decision variables: xj = number of seats allocated to LOF-fare combination j


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Revenue Management Optimization Dynamic programming

State of process: current bookings/seats available for each flight,competitor information

Transitions: take place through bookings and cancellations

Decisions: which prices/fares are quoted when booking requestsare received

Policy: decision for each state x and time t

Objective: determine optimal policy

Value function: expected value V(x,t) as function of state x and

time t Solving problem involves computing optimal value function

V*(x,t)

Another benefit: Optimal policy very simple:

accept booking request if fare > V*(x,t) - V*(x-1,t)


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Revenue Management Optimization Optimization Software Surveys

Fourer, R., Linear Programming, OR/MS Today, volume 32,number 3, pp. 46-55, June 2005,.

Nash, S. G., Nonlinear Programming, OR/MS Today, volume 25,number 3, pp. 36-45, June 1998,.

Grossman, T.A., Spreadsheet Add-Ins for OR/MS, OR/MSToday, volume 29, number 4, pp. 46-51, August 2002,.


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Revenue Management Optimization Decision Support Software Surveys

Aksoy, Y. and Derbez, A., Software Survey: Supply Chain Management, OR/MSToday, volume 30, number 3, pp. 34-41, June 2003,.

Buede, D., Decision Analysis Software Survey: Aiding Insight IV, OR/MS Today,

volume 25, number 4, pp. 56-64, August 1998.

Hall, R., Vehicle Routing Software Survey: On the Road to Recovery, OR/MSToday, volume 31, number 3, pp. 40-49, June 2004,.

Maxwell, D.T., Decision Analysis: Aiding Insight VII, OR/MS Today, volume 31,number 5, pp. 44-55, October 2004, .

Swain, J. J., 'Gaming' Reality: Biennial survey of discrete-event simulationsoftware tools, OR/MS Today, volume 32, number 6, pp. 44-55, December 2005,.

Swain, J. J., Power Tools for Visualization and Decision-Making, OR/MS Today,volume 28, number 1, pp. 52-53, February 2001.


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Demand Forecasting The first law of forecasting: The

forecast is always wrong

Sources of forecast error: Modeling error

Parameter error


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Demand Forecasting Modeling error

The basic form of the demand model is wrong

Example Suppose we want to forecast demand d as a function of

price p

The true demand function is d = exp(3-2p) / (1 + exp(3-2p))

We try to estimate a linear demand model d = a bp,with parameters a and b that are estimated with data

No matter what values we estimate for a and b, theestimated model is wrong modeling error


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Demand Forecasting Parameter error

The basic form of the demand model is correct,but we do not know the correct values of the

parameters Example

The true demand function is d = exp(3-2p) / (1 + exp(3-2p))

We try to estimate a demand model d = exp(a-bp) / (1+ exp(a-bp)), with parameters a and b that areestimated with data

If we estimate a=3 and b=2 (for example, with gooddata and a good statistical technique), then theestimated model is correct


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It is very important to understand and model

customer behavior accurately

Incorrect models of customer behavior canlead not only to suboptimal prices, but can

lead to the systematic deterioration of

models, prices, and profits over timethespiral-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 thesupposed 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) willingto buy high fare if that is the only option, now buy low faretickets

Airlines observe more low fare sales and less high fare salesdecrease their estimate of high fare demand

Airlines set aside fewer seats for high fare tickets, and allowmore low fare sales

More customers buy low fare tickets, and the spiral downcontinues

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 tobelieve will continue in the future

Demand Forecasting


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Revenue Management Implementation Business case: assessment of

Revenue opportunity

Development and support personnel needs

Development cost

Maintenance cost

Hardware

Software DBMS

Forecasting

Optimization

Interfaces


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Revenue Management Implementation Distribution system

Communication network hardware

Interfaces with revenue managers Interfaces with customers

Management of customer awareness

and customer perceptions Management of organizational change


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aviation case study ppt_2

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