Really this presentation address the performance of airline - how to forecast and know the LOAD FACTOR. in trems of ASK and RPK. case study is LH group. hope to enjoy !!!!!

1. Reading
In The
FUTURE
By:
Mohammed S. Awad
Chairman Adviser
Yemenia

2. Reading In The Future
“Excellence is never an
accident. It is always the
result of high intention,
sincere effort, and
intelligent execution; it
represents the wise choice
of many alternatives -
choice, not chance,
determines your destiny.”
― Aristotle

3. Outline 1/2
• Introduction
• Key Performance Indicators For Airlines
• Forecasting
– Basic concept of forecasting Model
– Forecasting – Trend vs. Seasonality
– Model Constrains
– Max.& Min Signal Tracking Analysis
– Accuracy Forecasting Matrix

4. Outline 2/2
• Case Study : ( Lufthansa Group )
• Basic Data Base ( Three years data )
• Forecasting
– Lufthansa Group - Passengers
– Lufthansa Group – Flights
– Lufthansa Group – ASK
– Lufthansa Group – RPK
– Expected Load Factor
• Forecasting Accuracy Matrix (Lufthansa Group)
• SUMMARY

5. Introduction – Clear Objectives
Most of airlines in the world working on
a clear objectives and that’s come with
clear targets which lead us to set a clear
picture of forecasting process.
Based on that, our objective is to
develop a clear massage for top
managements for the key performance
figures of the airline, not just to
compare month by month approach
but to develop the right path ( time
series ) in the future to set the right
targets which consequently develop
K.P. I for the airlines

6. K.P.I For Airlines ( Lufthansa Group )
• Key Performance Figures ( June 2014 )

7. K.P.I For Airlines
• K. P. I for Lufthansa Group:

8. FORECASTING

9. Basic concept of forecasting Model

10. Basic concept of forecasting Model
Directional Displacement

11. Basic concept of forecasting Model
Evaluation Forecasting

12. Forecasting – Trend vs. Seasonality
Trend Forecasting
Tell us in which direction (Growth) of the
historical data, and usually is a long term
forecast.
Seasonal Forecasting
Tell us the Seasonal, Cyclic shocks, we
used it to define the forecasting Pattern
Trend vs Seasonal Forecasting
Forecasted Year of TREND
= Sum of 12 forecasted Seasonal Months
for same year,

13. Model Constrains
 Two Main Constrains to get a fair model:
R2 > 80%
AND
-4 < T.S.< 4
R2 = Coef. Of Determination T. S. = Tracking Signal

14. Max.& Min Signal Tracking Analysis

15. Accuracy Forecasting Matrix
• Case Study : ( Lufthansa Group )

16. Case Study : ( Lufthansa Group )
The Lufthansa Group is an
aviation group with global
operations and a total of almost
500 subsidiaries and associated
companies. It consists of five
business segments, which encompass the areas of
passenger transportation and airfreight, as well as
downstream services: Passenger Airline Group, Logistics,
MRO, Catering and IT Services. All the segments are
market leaders in their respective areas.

17. Basic Data Base ( Three years data )
• 36 months data files

18. Forecasting
• Forecasting
– Lufthansa Group - Passengers
– Lufthansa Group – Flights
– Lufthansa Group – ASK
– Lufthansa Group – RPK
– Expected Load Factor

19. Lufthansa Group - Passengers

20. Lufthansa Group - Flights

21. Lufthansa Group – ASK

22. Lufthansa Group - RPK

23. Expected Load Factor -2014

24. Reading In the Future
• Analysis:
– Passengers: – there will be slight reduction in Passengers
– Flights: - due to the presence of A380 there will be a
significance reduction in 2014, due to large capacity of A380
– ASK:- also ASK will tend to be less
– RPK: - this factor will be stable, as LH will keep to serve their
markets
– Expected Load Factor ( L/F ) : Since RPK stable and ASK will
slightly decrease. This will lead to increase the expected
load factor.

25. Forecasting Accuracy Matrix
• Forecasting Accuracy :
– RPK is fair as it is satisfies
the constrains of the
forecasting.
– Passengers is also fair as
the mislead is denied by
Max/Min T. S. Analysis
( errors are distributed on
both sides of the trend line).
– ASK is also fair as the
mislead is denied by
Max/Min T. S. Analysis.
– Flights is also fair as the
mislead is denied by
Max/Min T. S. Analysis.

26. Summary
• Most of Investors in Airline Industry are concerned for the
performance factors that’s Passengers, RPK ,ASK , and Load
Factor. They evaluate them by comparing their values in past
according to month by month approach.
• This presentation tilling us the future patterns for these
factors, which consequently we can develop and forecast the
expected Load Factor.
• This also will help the airline to set their targets, and
developed the right KPI policy for measuring airline
performance.
• The data is fairly fitted, with a minimum errors.
• The results shows that there will be slight decrease in ASK,
with stability for RPK, THIS WILL LEAD TO INCREASE IN
EXPECTED LOAD FACTOR IN THE FUTURE (2014).

27. Welcome In The Club
Thanks !

28. Contact
• Mohammed Salem Awad
• Chairman Adviser – Yemenia
• Tel: 00967 736255814
• Email: mohammed.hadi@yemenia.com