Your SlideShare is downloading. ×
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Presented by
Network planning drivers and mode...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Agenda
Airlines’ benchmark and best practices
...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Agenda
Key factors that drive Network Planning...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Passenger preference concept
What is QSI (Qual...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Methodology overview
Consumer choice models va...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Methods and tool overview
Inputs & Outputs
Mod...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Methods and tool overview
Example: LHR-JNB loc...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Methods and tool overview
Example: Local traff...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Agenda
Passenger preference concept
Main facto...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Main factors influencing local traffic capture...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Main factors influencing local traffic capture...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
+3
+2
+2
+3
+2
+2
0
2
4
6
8
10
12
14
16
2014 2...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Main factors influencing local traffic capture...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Main factors influencing local traffic capture...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Agenda
Passenger preference concept
Main facto...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Main factors influencing connecting traffic ca...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Main factors influencing connecting traffic ca...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Main factors influencing connecting traffic ca...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Main factors influencing connecting traffic ca...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Main factors influencing connecting traffic ca...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Agenda
Airlines’ benchmark and best practices
...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Agenda
Capacity/frequency model for local dema...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
By analysing network growth since
2008, it app...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Capacity/frequency model for local demand
Freq...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Capacity/frequency model for local demand
Freq...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Capacity/frequency model for local demand
Depa...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Capacity/frequency model for local demand
Wide...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Agenda
Capacity/frequency model for local dema...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Hub structure to connect passengers
How the Lu...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Hub structure to connect passengers
How the Lu...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Hub structure to connect passengers
Connecting...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Hub structure to connect passengers
Connecting...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Hub structure to connect passengers
Connecting...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Agenda
Capacity/frequency model for local dema...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Long-haul network profitability drivers
Schedu...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Long-haul network profitability drivers
Schedu...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Long-haul network profitability drivers
Balanc...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Long-haul network profitability drivers
Schedu...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Long-haul network profitability drivers
Connec...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Agenda
Airlines’ benchmark and best practices
...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Agenda
Schedule and hub impact on network
From...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Definition of a flight schedule
The commercial...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Definition of a flight schedule
The scheduler’...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Scheduling time windows
SIN-LHR structure with...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Scheduling time windows
SIN-LHR structure with...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Scheduling time windows
SIN-LHR structure with...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Scheduling time windows
SIN-LHR structure with...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Scheduling time windows
SIN-LHR structure with...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Agenda
Schedule and hub impact on network
From...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Offering more schedules
The point-to-point app...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Hub systems
• Hourglass
• Hinterland
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Hubbing or not hubbing
HUB
STRENGTHS
HUB
WEAKN...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
6 waves hub structure
DEPARTURES
ARRIVALS
Wave...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
4 waves hub structure
DEPARTURES
ARRIVALS
Airp...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
2 “semi-waves” hub structure
DEPARTURES
ARRIVA...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
1 wave hub structure
DEPARTURES
ARRIVALS
Conne...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Sometimes it’s difficult to see a wave…
DEPART...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Evolution of a hub
QR operations in DOH – 1999...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Main AF domestic airport: ORY
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Main AF long-haul hub: CDG
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Main AF regional hub: LYS
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Agenda
Schedule and hub impact on network
From...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Hinterland hub & spoke operations
Aircraft wai...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Case study
Balancing lower utilization with hi...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Case study
Balancing lower utilization with hi...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Case study
Balancing lower utilization with hi...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Case study
Balancing lower utilization with hi...
© AIRBUS S.A.S. All rights reserved. Confidential and proprietary document.
Conclusion
Understanding the market is key for...
Upcoming SlideShare
Loading in...5
×

Airbus Network Planning Models 2014

194

Published on

Published in: Business
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
194
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
0
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

Transcript of "Airbus Network Planning Models 2014"

  1. 1. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Presented by Network planning drivers and model How to optimise network and hub strengths? Olivier Cartault Fleet & Network Planning Manager
  2. 2. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Agenda Airlines’ benchmark and best practices Key factors that drive Network Planning Schedule and hub impact on network
  3. 3. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Agenda Key factors that drive Network Planning Passenger preference concept
  4. 4. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Passenger preference concept What is QSI (Quality Service Index)? A Quality of Service Index is a way of quantifying a concept that is qualitative (service quality). In the case of air travel, quality is measured from the passenger point of view: What aspects do the customer value when booking a trip? Based on the characteristics of different flight options, which ones are the customers more likely to choose? QSI attempts to forecast passenger behavior by quantifying the relative attractiveness of different flight options. Method of assessing the relative quality of different services
  5. 5. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Methodology overview Consumer choice models value each airline service offering Quantifying a qualitative product Associating coefficient to customer selection factors Measure passenger preference factors: Number of stops Flight frequency Time of day, day of week Travel elapsed time Fare Connecting time Aircraft type (Jet, turboprop) Aircraft size Airline preference …
  6. 6. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Methods and tool overview Inputs & Outputs Model inputs : what data is required Flight schedules (OAG, Innovata) O&D market size & average fares (Sabre MIDT) Default coefficients (airline benchmark, QSI tool provider) Model output : interpreting the results A QSI model will provide market share for local and connecting markets Combined with the data above, this can be used to calculate: - Flight load factor, revenue - Network load factor, revenue - Traffic spill - Impact on my other flights - Top O&D contributing to the traffic on a leg
  7. 7. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Methods and tool overview Example: LHR-JNB local market How to allocate local traffic to the capacity offered between JNB and LHR? 3 daily B747-400 2 daily A340-300 3 daily B777-300ER JNB-LHR local traffic = 658 daily passengers 8 daily flights offered by 3 main carriers
  8. 8. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Methods and tool overview Example: Local traffic allocation to capacity Simple process to determine airlines local market share per O&D BA flight SA flight EK flight Demand 433 209 16 Aircraft size (C1) Stop (C2) Frequency (C3) QSI (C1 * C2 * C3) Industry total (∑QSI) 57.4 Market share 65.9% 31.7% 2.4% 1.8 1.3 2.2 Direct Direct Non-direct3 Daily 2 Daily 3 Daily 1 1 0.03 21 14 21 37.8 18.2 1.4 658 daily pax B747-400 (310 seats) A340-300 (210 seats) B777-300ER (400 seats)
  9. 9. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Agenda Passenger preference concept Main factors influencing local traffic capture Key factors that drive Network Planning
  10. 10. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Main factors influencing local traffic capture Difference between objective and subjective factors Objective factors: the base of local traffic attractiveness Flying direct or flying with a stop Number of frequencies Number of seats allocated Subjective factors: the way to influence the passenger demand Fares Product Branding Aircraft type Frequent Flyer Program IFE …
  11. 11. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Main factors influencing local traffic capture Market and capacity share of services between Africa and Europe/USA/Middle East/Asia 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 Market share (Local traffic) Capacity share (seats) The capture of local traffic is directly related to the capacity offered
  12. 12. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. +3 +2 +2 +3 +2 +2 0 2 4 6 8 10 12 14 16 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Frequencies Main factors influencing local traffic capture Relationship of frequencies and market share on long-haul Frequencies share Market share (Local traffic) The relationship between frequencies and market share is linked to S-curve approach
  13. 13. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Main factors influencing local traffic capture Direct flights are more attractive than non-direct traffic The simplest way for a passenger to go between A and B is to fly direct. But there is always a significant part of the traffic to go via hubs (10% on average), mainly attracted by: Fares: lower prices or more fare flexibility Availabilities: be able to book a flight Schedules: better departure/arrival time, good airport connectivity, flying time Products: on-board product (cabin, services, IFE), Alliance attractiveness (FFP Mileage) The analysis of this part of the traffic will help to understand if a market is well served or not by a direct service. If there is more than 10% of the traffic not attracted by direct flights, and if direct flights experience high load factors, then it could represent a good opportunity of traffic to be recaptured It is also important to identify unserved market representing good potential for a new route opening
  14. 14. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Main factors influencing local traffic capture Share gap factors 35% 65% Observation Pax routing preference Other LHR-DXB-JNB =+15% =-15% “Share Gap” 50% Emirates attractiveness (price, service, product....) accounts for the “share gap” 630** PPDEW* 28 PPDEW* 50% 50% “Fair share” MODEL MODEL Pax routing preference Other LHR-DXB-JNB Market data 2011 2.4% 4.4% Local Market share Local Market share
  15. 15. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Agenda Passenger preference concept Main factors influencing local traffic capture Main factors influencing connecting traffic capture Key factors that drive Network Planning
  16. 16. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Main factors influencing connecting traffic capture Connecting time is key to define connectivity Elapsed Time Sensitivity is used to adjust QSI scores of connecting itineraries as a function of elapsed time of the itinerary relative to the average for the O&D. The function applies to single online connections only, since QSI scoring is already greatly reduced for other connections types (eg double and interline connections). A QSI multiplier is applied to the ratio of actual elapsed time–to–average elapsed time
  17. 17. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Main factors influencing connecting traffic capture Optimising connecting time, time window and feeding capacity 80% load factor on LO domestic flights, 4 North American flights within a 2 hours time window and 1:25 of average connecting time WAW Arrivals WAW Departures LO Weekly frequencies 6.00 4.00 2.00 0.00 2.00 4.00 6.00 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 00:00 YYZ ORD JFK EWR 8.00 Feeding Polish domestic flights DH4 aircraft 80% average load factor on domestic 01:25 average connecting time Weekly flights Distribution of all departures through a 2:00 time window
  18. 18. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Main factors influencing connecting traffic capture Optimising connecting time, time window and feeding capacity MUC Arrivals MUC Departures LH Weekly frequencies 6.00 4.00 2.00 0.00 2.00 4.00 6.00 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 00:00 YYZ ORD JFK EWR 8.00 Feeding flights from Polish market CR9, E95 aircraft 70% average load factor on Polish flights 00:55 average connecting time Daily flights Distribution of all departures through a 1:10 time window 70% load factor on LH Polish flights, 4 North American flights within a 1:10 hours time window and 0:55 of average connecting time
  19. 19. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Main factors influencing connecting traffic capture Taking into account interline and online Online connecting times (AA-AA) Minimum Domestic-International connecting time = 45 minutes Minimum International-International connecting time = 45 minutes Maximum connecting time without penalty = 5 hours Maximum connecting time with penalty = 7 hours No connections allowed after 7 hours Interline connecting times (AA-BB) Minimum Domestic-International connecting time = 55 minutes Minimum International-International connecting time = 55 minutes Codeshare preference factor Online connections have a base coefficient of 1 Interline connections have a base coefficient of 0.3 An Alliance member is more attractive, justifying a higher coefficient (0.5 to 0.7) Joint ventures relationship are very closed to online connections (0.9 to 1)
  20. 20. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Main factors influencing connecting traffic capture Benefiting from Alliance effect SFO SIN JNB NRTIAH FRA PEK Connection to an Alliance’s hub has an impact on capacity, by generating more traffic LH has allocated their biggest capacity (A380) to connect FRA hub to their partners. (64% of A380 routes are “Star Alliance” inter hubs connections) Connecting traffic to Star beyond those hubs has increased by 33% on average +40% +52% +35% +22% +42% +18%
  21. 21. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Agenda Airlines’ benchmark and best practices Key factors that drive Network Planning Schedule and hub impact on network
  22. 22. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Agenda Capacity/frequency model for local demand Airlines’ benchmark and best practices
  23. 23. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. By analysing network growth since 2008, it appears that 50% of this growth is driven by capacity growth, more than by the frequencies growth. Most of this capacity increase concerns oldest routes, whereas youngest routes are mainly growing by frequencies. Trunks routes with already multiple frequencies are ready for capacity increase Smaller routes need to grow in frequencies 50% 9% 6% 35% Capacity increase Constant Frequency & Capacity Increase Frequency & Capacity Increase Frequency Increase Capacity/frequency growth (2008-2013) (Source: OAG) Network development is mainly driven by capacity increase Capacity/frequency model for local demand Evolution of capacity/growth
  24. 24. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Capacity/frequency model for local demand Frequencies market trends on long-range (7,000 km) 89% of long-range routes are operated with 1 or less than 1 daily flight Just 1% of the long-range routes are operated beyond 2 daily 0 100 200 300 400 500 600 700 800 900 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 23 26 28 29 36 1996 2001 2006 2011 Number of flights Number of weekly frequencies
  25. 25. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Capacity/frequency model for local demand Frequencies market trends on medium-range (4,000 to 7,000 km) 0 100 200 300 400 500 600 700 800 900 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 24 26 27 28 29 32 33 34 35 40 41 42 46 47 48 49 62 1996 2001 2006 2011 Number of flights Number of weekly frequencies 82% of medium-range routes are operated with 1 or less than 1 daily flight Just 5% of the medium-range routes are operated beyond 2 daily
  26. 26. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Capacity/frequency model for local demand Departure time is key for local demand 0 100 200 300 400 500 600 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0 1 2 Southern Africa-Europe South America-North America Asia-Europe Frequencies (SEP09) Stronger demand for night long-haul flights Day flights for specific markets (Northern Asia) and 2nd daily flights Departure time
  27. 27. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Capacity/frequency model for local demand Widebodies capacity management to better match the demand Widebodies family allows capacity optimisation Less dynamic due to flight time and sector length Widebodies capacity management to match the demand. MON TUE WED THU FRI SAT SUN A340-300 (254 seats) A340-600 (342 seats) MAD SCL June 2014
  28. 28. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Agenda Capacity/frequency model for local demand Hub structure to connect passengers Airlines’ benchmark and best practices
  29. 29. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Hub structure to connect passengers How the Lufthansa’s FRA works (1) -30,000 -20,000 -10,000 0 10,000 20,000 30,000 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 10 10.5 11 11.5 12 12.5 13 13.5 14 14.5 15 15.5 16 16.5 17 17.5 18 18.5 19 19.5 20 20.5 21 21.5 22 22.5 23 23.5 DeparturesArrival WeeklySeatsOffered Local time in FRA Domestic & Regional Intercontinental 4hr 4hr 4hr Lufthansa’s medium-haul hub system has 4 waves, each with a 4-hr interval
  30. 30. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Hub structure to connect passengers How the Lufthansa’s FRA works (2) 4-8hr rotation 2-4hr rotation Airport bubble size is proportional to weekly seats offered Lufthansa’s hub wave design was based on its geographical environment
  31. 31. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Hub structure to connect passengers Connecting time is key to define connectivity 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 More than 300,000 transit passengers in 2010, accounting for 18% of all the traffic connecting in Seoul Japan is the major and contributor to ICN network
  32. 32. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Hub structure to connect passengers Connecting time is key to define connectivity 91 minutes as average connecting time between Japan and Europe AIRLINE FLIGHT TO DEPART. EQUIP. OZ 541 FRANKFURT 12:30 772 KE 907 LONDON 13:10 744 OZ 501 PARIS 13:15 772 KE 905 FRANKFURT 13:30 744 OZ 521 LONDON 13:30 772 KE 901 PARIS 14/00 744 AIRLINE FLIGHT FROM ARRIVAL EQUIP. KE 722 OSAKA 11:20 77W OZ 115 OSAKA 11:20 763 KE 752 NAGOYA 11:35 744 OZ 107 TOKYO 11:40 772 KE 706 TOKYO 11:50 744 KE 788 FUKUOKA 11:55 333
  33. 33. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Hub structure to connect passengers Connecting time is key to define connectivity 136 minutes as average connecting time between Japan and Europe AIRLINE FLIGHT TO DEPART. EQUIP. JL 405 PARIS 11:00 773 NH 205 PARIS 11:20 772 NH 209 FRANKFURT 11:25 772 NH 201 LONDON 11:35 772 JL 407 LONDON 12:00 773 JL 401 FRANKFURT 13:30 773 AIRLINE FLIGHT FROM ARRIVAL EQUIP. JL 3052 FUKUOKA 08:45 734 NH 338 NAGOYA 08:55 320 NH 2176 OSAKA 09:10 773 NH 2152 SAPPORO 09:25 320 JL 3002 OSAKA 09:40 773 NH 2142 FUKUOKA 09:45 735 JL 8405 NAGOYA 09:55 773 JL 500 SAPPORO 09:55 73H
  34. 34. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Agenda Capacity/frequency model for local demand Hub structure to connect passengers Long-haul network profitability drivers Airlines’ benchmark and best practices
  35. 35. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Long-haul network profitability drivers Scheduling is key to attract high yield passengers First Business Premium Eco Economy P F J C D I Z O W S A Y B M U K H L Q T E N R V X G AF183 10:20 17:10 247 seats Mon Tue Wed Thu Fri Sat Sun AF185 23:05 05:45+1 300 seats Mon Tue Wed Thu Fri Sat Sun Full availability (9 seats and over) Limited availability (1-6 seats) No availability Booking class not offered HKG-CDG Premium passengers have a strong preference for night flights, and as demand is higher, Airlines could generate higher revenue
  36. 36. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Long-haul network profitability drivers Scheduling is key to capture more connecting passengers Turkish Airlines has a ‘‘semi-hub’’ model based on morning and evening waves Turkish Airlines hub system in IST (August 2008) ArrivalsDepartures Long-haul Medium-haul
  37. 37. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Long-haul network profitability drivers Balancing lower utilization with higher revenues TK has rescheduled its Seoul flight in Feb 2009 to increase connections However turn-around time in Seoul has increased by 6h15 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 TK in IST (Aug 2008) ArrivalsDepartures Long-haul Medium-haul 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 TK in IST (Aug 2009) ArrivalsDepartures TK90 (19h15) TK91 (19h15) TK91 (05h50) TK90 (23h45) Turn-around time of TK90/91 in ICN = 1h50 Turn-around time of TK90/91 in ICN = 8h05
  38. 38. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Long-haul network profitability drivers Scheduling is key to capture more connecting passengers The new Istanbul-Seoul schedules have tripled connecting traffic , leading to higher capacities and frequencies MonthlyTKtrafficonICN-IST(one-way) Connecting traffic(+200%) Local traffic New flight schedules Frequency 2/7 or 3/7 (A340-300) Frequency 4/7 then 5/7 (A340-300 and 777-300ER)
  39. 39. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Long-haul network profitability drivers Connecting is key to generate higher revenue at network level Revenue Cash Operating Cost Profit (COC) Ownership Cost Network Contribution Profit (DOC) Profit + Network Contribution 1 2 3 Opening a new long-haul route will generate revenue at the network level
  40. 40. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Agenda Airlines’ benchmark and best practices Key factors that drive Network Planning Schedule and hub impact on network
  41. 41. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Agenda Schedule and hub impact on network From network planning to scheduling
  42. 42. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Definition of a flight schedule The commercial view A flight schedule is a direct or non-direct service between two airports Two flight numbers can exist in case of connections Day of the week, departure and arrival times must be convenient Total journey time must be minimal
  43. 43. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Definition of a flight schedule The scheduler’s view A flight schedule is made of a pair of Flight Numbers flown by one aircraft tail number, usually between the aircraft base and a destination airport More than 2 legs can exist in case of tag ends Block times are a function of leg distance, aircraft cruise speed and en-route winds Turn-Around Times (TAT) are a key input to build the schedule, and can be airport dependent SIN LHR SIN SQ318 (A380 – 13h25) SQ321 (A380 – 12h50) 13h25 19h10 22h05 17h55 TAT: 2h55
  44. 44. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Scheduling time windows SIN-LHR structure with SQ (Day-Night structure) Most Passengers avoid the night period to depart from and arrive at airports Middle-East and India remain exceptions, due to their geographic positioning Long-haul morning flights cannot leave before 8h00 Local passengers need to comply with minimum check-in times of at least 1hr (immigration, security) 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 SIN LHR D A A D TAT: 3h00
  45. 45. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Scheduling time windows SIN-LHR structure with SQ (Day-Night structure) 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 SIN LHR D A A D TAT: 3h00 Most Passengers avoid the night period to depart from and arrive at airports Middle-East and India remain exceptions, due to their geographic positioning Long-haul morning flights cannot leave before 8h00 Local passengers need to comply with minimum check-in times of at least 1hr (immigration, security) Time windows can be defined for flights between two airports Like the schedule, they depend on the aircraft cruise speed and its minimum TAT
  46. 46. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Scheduling time windows SIN-LHR structure with SQ (Night-Night structure) 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 SIN LHR D A A D A night flight can be found on the SIN-LHR sector Night flights on westbound sectors usually imply narrow time windows TAT: 3h00
  47. 47. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Scheduling time windows SIN-LHR structure with SQ (Night-Night structure) 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 SIN LHR D A A D A night flight can be found on the SIN-LHR sector Night flights on westbound sectors usually imply narrow time windows The return time schedule constraint means a significant increase of TAT TAT: 6h00
  48. 48. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Scheduling time windows SIN-LHR structure with SQ (Night-Night structure) 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 SIN LHR D A A D TAT: 6h00 TAT: 3h00TAT: 3h00 Geography constraints scheduling
  49. 49. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Agenda Schedule and hub impact on network From network planning to scheduling Hubing or not hubing
  50. 50. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Offering more schedules The point-to-point approach The hub-and-spoke system
  51. 51. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Hub systems • Hourglass • Hinterland
  52. 52. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Hubbing or not hubbing HUB STRENGTHS HUB WEAKNESSES HUB OPPORTUNITIES HUB THREATS • Provide more destinations & frequencies • One base (maintenance) • Improves market share • Improves revenues & LF • Capacity constraints (slots) • Environmental considerations (night curfews) • Deregulation of air transport (additional entry points) • Sensitive to disruptions (weather, security,…) • High staff & infrastructure utilization (peaks) • Lower aircraft utilization • Deregulation of air transport (6th freedom rights) PREREQUISITES FOR BUILDING A HUB: Geographical position - Air freedoms - Available airport capacity - Strong local traffic
  53. 53. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. 6 waves hub structure DEPARTURES ARRIVALS Waves of arrival flights are connected to wave of departure flights Minimise connecting time to increase connecting traffic opportunities HUB IN CDG Long-haul arrivals Medium-haul arrivals Medium-haul departures Long-haul departures
  54. 54. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. 4 waves hub structure DEPARTURES ARRIVALS Airports slot constraints impact frequencies and connecting bands Wider connecting waves limiting their number HUB IN FRA Long-haul arrivals Medium-haul arrivals Medium-haul departures Long-haul departures
  55. 55. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. 2 “semi-waves” hub structure DEPARTURES ARRIVALS Long-haul arrivals Medium-haul arrivals Medium-haul departures Long-haul departures “Regional” hub connecting Africa to the world Taking advantage of the geography of ADD HUB IN ADD 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0 1 2
  56. 56. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. 1 wave hub structure DEPARTURES ARRIVALS Connecting Europe to Far-east Asia Taking advantage of geography with polar routes HUB IN HEL Long-haul arrivals Medium-haul arrivals Medium-haul departures Long-haul departures
  57. 57. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Sometimes it’s difficult to see a wave… DEPARTURES ARRIVALS Extreme airport constraints are limiting the development of waves HUB IN LHR Long-haul arrivals Medium-haul arrivals Medium-haul departures Long-haul departures
  58. 58. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Evolution of a hub QR operations in DOH – 1999 to 2013 The geography around Qatar drove the positioning of the waves, since the beginning -100 -75 -50 -25 0 25 50 75 100 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 10 10.5 11 11.5 12 12.5 13 13.5 14 14.5 15 15.5 16 16.5 17 17.5 18 18.5 19 19.5 20 20.5 21 21.5 22 22.5 23 23.5 0 0.5 1 1.5 2 2.5
  59. 59. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Main AF domestic airport: ORY
  60. 60. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Main AF long-haul hub: CDG
  61. 61. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Main AF regional hub: LYS
  62. 62. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Agenda Schedule and hub impact on network From network planning to scheduling Hubing or not hubing Turnaround time is impacted by hubs structure
  63. 63. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Hinterland hub & spoke operations Aircraft wait at outstations to efficiently connect at the hub TRN CDG in Paris (CDG) Return 3 banks later Return 2 banks later AF 1102 CDG 7h35 - TRN 9h00 AF 1103 TRN 10h35 - CDG 12h00 (turnaround time of 1h35 vs 30 min optimum) 3h 3h 3h 3h 3h AF flight frequency distribution vs. range Return3bankslater(2,700km) Return2bankslater(1,500km)
  64. 64. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Case study Balancing lower utilization with higher revenues CDG-JNB Route 1 daily flight (Night-Day) 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 CDG JNB Typical day-night structure
  65. 65. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Case study Balancing lower utilization with higher revenues 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 CDG JNB Typical night-night structure CDG-JNB Route 1 daily flight (Night-Day) 1 daily flight (Night-Night)
  66. 66. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Case study Balancing lower utilization with higher revenues Availability request made 6 months before flight departure Carrier Flight From Depart To Arrive A/C Availability AF 994 CDG 10:15 JNB 21:40 77W P8 F4 R0 A1 J9 C9 D9 I9 Z9 E0 Y9 B9 K9 H9 W9 T9 V9 L9 Q0 N0 AF 990 CDG 23:15 JNB 10:40 +1 77W P8 F4 R0 A1 J9 C9 D0 I0 Z0 E0 Y9 B9 K9 H9 W9 T9 V0 L0 Q0 N0 Lowest “L” fare: 1,041 USD Lowest “V” fare: 1,193 USD Lowest “T” fare: 1,302 USD CDG-JNB Route 1 daily flight (Night-Day) 9h50 on the ground in JNB ! How does AF price this layover ? AF raised lowest prices by 261USD in Economy on the night flight…
  67. 67. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Case study Balancing lower utilization with higher revenues Availability request made 6 months before flight departure Carrier Flight From Depart To Arrive A/C Availability AF 994 CDG 10:15 JNB 21:40 77W P8 F4 R0 A1 J9 C9 D9 I9 Z9 E0 Y9 B9 K9 H9 W9 T9 V9 L9 Q0 N0 AF 990 CDG 23:15 JNB 10:40 +1 77W P8 F4 R0 A1 J9 C9 D0 I0 Z0 E0 Y9 B9 K9 H9 W9 T9 V0 L0 Q0 N0 Lowest “L” fare: 1,041 USD Lowest “V” fare: 1,193 USD Lowest “T” fare: 1,302 USD AF raised lowest prices by 261USD in Economy on the night flight… and put the A380 on the CDG-JNB route CDG-JNB Route 1 daily flight (Night-Day) 9h50 on the ground in JNB ! How does AF price this layover ?
  68. 68. © AIRBUS S.A.S. All rights reserved. Confidential and proprietary document. Conclusion Understanding the market is key for route evaluation: - New network opportunities - Competition - Traffic dynamics/characteristics Allocating the traffic to any capacity, schedule and network changes can be done with: - QSI: easy to understand - Logit: statistical approach Scheduling is important to airlines, as it is their key product. There are scheduling patterns which will bring higher revenues. Hubs are also designed to bring higher revenues. Scheduling and hubbing have an impact on aircraft utilization

×