Transcript Distribution history

IT integration
in airline business process
ITAB 2007
Grach Muradyan
General principle
Information Technologies allow airline
…but only in case IT is properly integrated
in airline business process…
© 2007 Amadeus IT Group SA
 To be aware of…
 To understand…
 To describe…
 In order to control !!!
General principle
 Airline industry operates in a dynamic environment
 Variety of external and internal factors:
 Changes in demand
 Competitors actions
 Fuel cost, etc…
 Maximum info for planning
 Maximum info for ongoing situation / status
 Maximum flexibility and best tools to react
on the ongoing situation
 Minimum time for decision delivery to the market
© 2007 Amadeus IT Group SA
 Impossible to predict all the variations
 IT complex should provide airline
General principle
IT complex should be organized
as a system with feedback (“autopilot scheme”)
Competitors
Optimization
Implementation
Control
Regulation
MARKET
Other factors
Data analysis
Data collection
Airline commercial department
© 2007 Amadeus IT Group SA
Objectives &
planning
Airline IT modules
 Objectives and Planning
 Revenues and costs planning
 Network planning
 Schedule generation & optimization
(max fleet & crew utilization with given restrictions)
 Prognosis, based on the historical data
 Availability and overbooking level recommendations
 Reporting
© 2007 Amadeus IT Group SA
 Optimization: Revenue Management
Airline IT modules
 Implementation
 Schedule publication
 Connections (ongoing) optimization
 Operation and disruptions management
 Inventory control
 Nesting
 Availability
 Levels per class
 Rules / limitations
 Taxes
© 2007 Amadeus IT Group SA
 Fares
Airline IT modules
 Control
 Revenue Integrity: increasing load factor and
efficiency of RM utilization
 Time limits
 Fake names (“test”, etc..)
 Unreal bookings
 Unproductive bookings
 Married Segment Control
 Long Haul availability
 Dynamic Availability
 Journey Data
© 2007 Amadeus IT Group SA
 Distribution (in GDSs)
Airline IT modules
 Data collection (major airline data streams)
 Billing Information (BIDT / ABI): bookings on own
airline
 Marketing information (MIDT): bookings on own +
other airlines
 Global
 Ticketing Data (ATD)
 IATA Reporting / Hand Off Tape format files
 ET Flight Coupons (LIFT files)
© 2007 Amadeus IT Group SA
 Regional
 Express
 Custom, etc…
Airline IT modules
 Major Data analysis tasks
 Commercial analysis
 Demand for the airline services
 Bookings / cancellations distribution (per markets, flights, cabin /
classes, departure dates, etc…)
 TAs making passive, test, fake and other unproductive bookings
 Revenue / ticketing info
 Cashflow / stock control
 Interlining
 Source for Revenue Accounting systems
 Sales effectiveness (e.g. TK, UN,… levels)
 Billing / accounting purposes
 Understanding billing of IT service providers
 Supporting airline claims
© 2007 Amadeus IT Group SA
 Technological analysis
Data analysis examples
© 2007 Amadeus IT Group SA
distribution per month of departure
Market and seasonality dependence (RU / Jan)
Data analysis examples
© 2007 Amadeus IT Group SA
distribution per month of departure
Market and seasonality dependence (DE / Jan)
Data analysis examples
© 2007 Amadeus IT Group SA
distribution per month of departure
Market and seasonality dependence (DE / May)
Data analysis approach
From global to local
 Being aware something is going not the way
it was expected (e.g. irregularity)…
 Understanding what exactly is happening ?
(e.g. bookings jumping in low season)
 Deciding how to resolve the issue ?
(technological and commercial actions)
 Analyzing how to prevent this happening again ?
(e.g. changing airline policy)
© 2007 Amadeus IT Group SA
 Finding who exactly and why is doing this ?
(POS: country->TA office ID)
Data analysis example
Regularity in long-term observation
( peaks in Jan and Sep net bookings )
70 000
60 000
50 000
add
40 000
cancel
net
30 000
10 000
Se
p
O
ct
No
v
De
c
Ja
n
Fe
b
De
c
Ja
n
Fe
b
M
ar
Ap
r
M
ay
Ju
n
Ju
l
Au
g
Se
p
O
ct
No
v
Ja
n
Fe
b
M
ar
Ap
r
M
ay
Ju
n
Ju
l
Au
g
0
© 2007 Amadeus IT Group SA
20 000
Data analysis example
© 2007 Amadeus IT Group SA
TA activity split by country & office
Data analysis example
© 2007 Amadeus IT Group SA
TA activity split by office
Data analysis example
Distribution per month of departure:
Jan bookings made by one TA office (“seats freezing”)
Departure month ->
Jan Feb Mar
Added
60
99
10
Canceled
14
20
2
Net
46
79
8
% of Total
0,8% 1,4% 0,1%
Canceled %
30,4% 25,3% 25,0%
Booking period (days) 14
9
3
Apr
May
Jun
Jul
Aug
Sep
Oct
846
728
779
824
740
915
921
10
8
25
10
0
31
43
836
720
754
814
740
884
878
14,5% 12,5% 13,1% 14,1% 12,8% 15,3% 15,2%
1,2% 1,1%
3,3%
1,2%
0,0%
3,5%
4,9%
5 4 (13-16) 4(13-16) 5(13-17) 4(14-17) 4 (14-17) 3(15-17)
Total
5922
163
5759
100,0%
2,8%
18,0%
16,0%
14,0%
12,0%
© 2007 Amadeus IT Group SA
10,0%
8,0%
6,0%
4,0%
2,0%
0,0%
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Data analysis example
© 2007 Amadeus IT Group SA
Passive bookings made by an office
within just one day…
Last but not least…
Need for IT policy coordination
on top management level
 Internal competition (trend) between departments
within airline: IT being a TOOL for commerce
 Permanent control on IT activity: info processing
 Regularity
 Frequency
 Completeness
© 2007 Amadeus IT Group SA
 Commerce dictates what
 IT decides how (the best)
 IT proposes new tools / approaches
© 2007 Amadeus IT Group SA
Thank you !