1. Integration of Pricing and Revenue Management for a Future without Booking Classes
AGIFORS
Reservation and Yield Management Study Group Annual Meeting, Bangkok, May , 2001
Natascha Jung Senior Operations Research Specialist
Klaus Weber Senior Scientific Analyst

2. Presentation on behalf of my colleague Natascha
...
and her boss

3. Agenda Motivation Booking Classes Pricing & Revenue Management
Integrated Approach to Pricing & Revenue Management
Outlook / Conclusions

4. Motivation The Customer
Typical Travel Agency Situation?
I see, ...
Are you looking for
a last minute offer?
Do you have any
idea when and how you would like to fly?
I would like to book
a flight from
Bangkok to
Rio de Janeiro.
No, ...
Yes, I would prefer a
three leg itinerary via Frankfurt and
Madrid.
That’s not important! I just like to travel in M class ... I mean, from BKK to FRA in M, and then H class to MAD. But for transatlantic flights I prefer class Q!!
travel agent
customer

5. Motivation The Customer (cont.)
Typical Travel Agency Situation?
Do you have any idea when and how you would like to fly?
I understand. You need a comfortable seat with power supply for your laptop.
If you don’t mind the risk of thrombosis N I can offer you a discounted fare in Eco?
I would like to book a flight from Bangkok to Rio de Janeiro.
I am going to take part in the annual
meeting of Nobel
laureates which starts next month and will take 8 days.
Oh, no! I just like to sit and think about a new formula.
Great! I take it!
travel agent
customer

6. Motivation The Customer (cont.)
Resume
Customer does not care about booking classes!
Customer demand depends on
Travel day
Prices (offered at ticketing day)
Service
Restrictions (minimum stay, day application, ...)
fares
Demand is controlled by fares, i.e. customer needs!
Revenue management systems
Forecast is estimated on basis of historical demand
Booking histories are stored w.r.t. booking class!
!!! Contradiction !!!

7. Agenda Motivation Booking Classes Pricing & Revenue Management
Integrated Approach to Pricing & Revenue Management
Outlook / Conclusions

8. Booking Classes Historical Review
Historical Development of Revenue Management at Lufthansa
1955
Central Reservation
1965
Overbooking
1972
Currency Control
1977
Segment Pricing
1989
Fare Mix / Control
1994
Network Management / Bid Pricing
1972 Littlewood’s rule
1989 EMSRb
Booking classes
Currency Control: Lower availability for countries with weak currency.
Network Management: Availability concerning Routing and Point of booking. A passenger flying from A to B to C is maybe paying less than a passenger just flying from B to C.

9. Booking Classes Why Booking Classes?
Revenue management point of view
Booking classes reflect ‘somehow’ the customers’ will to pay
booking classes are the basis for demand forecast
Reservation systems use them to indicate availability
However, there are other means to
reflect customer will to pay (fares)
compute customer demand (customer choice model)
We do not truly need booking classes but we are used to use them.

10. Booking Classes Why Booking Classes? (cont.)
Pricing point of view
Booking classes are not important at all
Only fares are important!
Fares are richer in information than booking classes

11. Booking Classes Problems with Booking Classes
Booking classes are inaccurate, e.g.
Quite different fares in same booking class
Distortion of average revenue of booking class
Another indicator
Booking class harmonisation in airline alliances usually increases number of booking classes

12. Booking Classes Problems with Booking Classes (cont.)
RM systems forecast on historical data
!!! Meanwhile fares might have been changed !!!
Different demand
Different average values of corresponding booking classes

13. Booking Classes Booking Classes - pros and cons
Booking classes cons
History building for demand forecast
(generally possible for fares as well, however: too many fares)
Bid price control requires calculation of bid prices
Booking class protects not necessary
Booking classes only indirectly used for BP calculation
Booking class corresponds to class value (‘somehow’)
Booking class can be identified with restrictions (‘somehow’)
Inexactness of booking classes
restricts opportunity of additional revenue gain ... in 0.1 % range (which are millions of € or $)
‘approximation’
inexact, but works

14. Booking Classes Booking Classes - pros and cons (cont.)
Booking classes cons
‘customer pricing’ (priceline.com, tallyman.de) shows
Booking classes are not necessary
!!! Approach not generally applicable to airlines !!!
restrictions (not refundable) are necessary to avoid down selling
not possible to sell ‘open tickets’

15. Agenda Motivation Booking Classes Pricing & Revenue Management
Integrated Approach to Pricing & Revenue Management
Outlook / Conclusions

16. Price Elasticity Model
Pricing & Revenue Management Overview: Pricing System - Price Elasticity Model
Trigger
Fare
Change
Price Elasticity Model
Output
Demand
Shift
Fare
Analyser
Market Share
Model
Competitor
Reaction
Analyser
Traveller Preference Analyser
Market Stimulation Model

17. Pricing & Revenue Management Overview: Revenue Management System
O&D Forecast Engine
O&D Optimiser
Forecast Interface DB
Optimiser Interface DB
Inventory
GDS
...
Forecast Building
Demand Forecasts
Control
Parameters

18. Pricing & Revenue Management Comparison
Target level (What shall be controlled?)
Market - OD origin destination Fares given on this level.
ODIF POS origin destination itinerary fare class point of sale Booking values given on this level.
customer oriented
Value / revenue oriented
coarse level
fine level
Target quantities (Which quantities are focused on?)
Market size
Market share
Fares
ODIF POS demand
ODIF POS values
marginal seats revenues
bid prices

19. Pricing & Revenue Management Comparison (cont.)
Target quantities (Which quantities are focused on?)
Market size
Market share
Fares
ODIF POS demand
ODIF POS values
marginal seats revenues
bid prices
Linking both spheres means
replace booking classes in RM sphere by fares (properly)
integrate both spheres

20. Pricing & Revenue Management Requirements for Integration
Current Demand Forecast
Booking histories
Current booking level
Booking classes
Booking classes
PNR

21. Pricing & Revenue Management Requirements for Integration
Integrated Demand Forecast
Booking histories
Current booking level
Fare buckets
fares clustered with respect to
value / revenue
restrictions
Fare buckets
??? Source ???
fare
In the future?
... together with
other usefull,
quantities, e.g. bid prices
fare (inexact)
Why buckets?
Optimisation requires competition among customers for same seat
Why not take fares, i.e. one fare per bucket?
Too many buckets
Pricing DB
class info
restrictions etc.

22. Pricing & Revenue Management Requirements for Integration (cont.)
Bookings
Fare buckets
Example
Value
restriction sunday return
advanced purchase 14 days
...
av. value no. of bkgs.
For optimisation we need to forecast the number of bookings in each fare bucket.

23. Agenda Motivation Booking Classes Pricing & Revenue Management
Integrated Approach to Pricing & Revenue Management
Outlook / Conclusions

24. Integrated Approach Pricing & RM Price Elasticity Model
Forecast of demand for each fare bucket - step 1
Data sources
Utility
factors
Competitor
Reaction
Analyser
Market Share
Model
Market Stimulation Model
Price Elasticity Model
Traveller Preference Analyser
Alternative
Customer choice model
multinomial logit model
customer’s choice depends on
amount
minimum stay
advanced purchase
...
Internal fare data
ATPCO
MIDT
Separate for business and leisure passengers

25. Integrated Approach Pricing & RM Market Size Forecaster
Forecast of demand for each fare bucket - step 2
Data sources
MIDT
ATPCO
Internal fare data
Forecast basis
Demand forecast
Market Size Forecaster
Current bookings

26. Integrated Approach Pricing & RM Fare Buckets Forecast
Forecast of demand for each fare basket - step 3
Price Elasticity Model
Per ticketing/travel combination
Per departure date
...
av. value no. of bkgs.
Fare buckets
Market Size Forecaster

27. Integrated Approach Pricing & RM System Overview
O&D Optimiser
Forecast Interface DB
Optimiser Interface DB
Inventory
GDS
...
Market Shares
Demand Forecasts
Control
Parameters
Market Size Forecast
Price Elasticity Model
Market Size
Bookings with Fare Information

28. Integrated Approach Pricing & RM Demand Changes
Re-Optimisation
Previous è New
Forecast
Previous Forecast
Demand
Shift
Current Demand
Demand
Shift
Price Elasticity
Model
Learning
Fare
Change
Floating dcp
Snap shot

29. Agenda Motivation Booking Classes Pricing & Revenue Management
Integrated Approach to Pricing & Revenue Management
Outlook / Conclusions

30. Outlook / Conclusions Outlook - Mining PNRs
Business passengers behave different from leisure passengers
Separate customer choice models
Problem: Identification of passenger types
history data
current booking data ü
Fare information available (insufficient?) !!
PNR may not contain fare information!
Mine PNR data to decide to which type passenger belongs to
e.g.
pax travels single ... or with family
pax is frequent traveller
...
PNR

31. Outlook / Conclusions Summary
Booking classes
are inaccurate w.r.t. amount of fares contained
are not used directly in O&D bid price control
Booking class-based forecast
reflects historical customer choice only
does not concern current market changes
Booking class-oriented revenue management systems
are sophisticated (O&D control)
work well
may not exhaust the full potential of RM control!!!
There is need for strong integration of Pricing and RM

32. Outlook / Conclusions Summary
Gap between pricing and revenue management could be closed
by replacement of booking classes by fare buckets
by forecast concerning
market size
market shares
Integrated approach to pricing and revenue management
manages demand changes
Challenges
Inventory changes
Information provision
Good experience with
pricing NetLine/Price
pricing simulation NetLine/Price:PSM
pax demand forecast for scheduling NetLine/Plan
Interested airlines are kindly invited for proving the concept

33. Thank you for your attention! Any questions?1