Seven Performance Factors that Turkish airline are addressing in their reports , Mainly , Number of Landing, Available Seat Km, Revenue Passenger Km, Passengers Load Factor (%) , Passenger Carried, Cargo And Mails, Km Flown. So most of airlines working on a clear objectives and that’s come with clear targets which lead us to set a clear picture of forecasting process. Most of the results are fairs except Load Factor, the outcome is poor

1. Future Performance
Reading In
The Future (5)
Case Study
83 %Prepared By
Mohammed Salem Awadh
Aviation Consultant

2. Future Performance
“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
Future Performance

3. Future Performance
Outline 1/2
• Key Performance
Indicators For Turkish
Airlines
• Errors Vs KPIs
• Forecasting (Model)
– Basic concept of forecasting
Model
– Model Constrains
– Max.& Min Signal Tracking
Analysis
– Accuracy Forecasting
Matrix
• Case Study : ( TK )
• Basic Data Base ( Three
years data )
• Forecasting ( Actual )
– Traffic Passengers 2015-2016
– RPK 2015 - 2016
– ASK 2015 – 2016
– Load Factor 2015 -2016
– Distance Km 2015-2016
– Cycles 2015-2016
– Traffic 2015 -2016
– Cargo and Mail 2015 -2016

4. Future Performance
Outline 2/2
• Forecasting Accuracy Matrix
• Analysis
• Results
• Summary
• Contact

5. Future Performance
Performance Factors
of Turkish Airline
- Seven Performance Factors that Turkish
airline are addressing in their reports , Mainly
1- Number of Landing,
2- Available Seat Km.
3- Revenue Passenger Km,
4- Passengers Load Factor (%) ,
5- Passenger Carried,
6- Cargo And Mails,
7- Km Flown.
- So most of airlines 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
000000

6. Future Performance
Performance Factors
of Turkish Airline

7. Future Performance
K.P.I For Airlines
• Key Performance Figures
• Capacity = ASK( available seat Kilometers )
• Traffic = RPK( revenue passenger Kilometers )
• Load Factor ( LF ) =
RPK/ASK

8. Future Performance
K.P.I For Airlines
• K. P. I for Lufthansa Group:
Each Airline has its own KPIs
policy, LANDING, ASK , RPK, PAX &
L/F are main measuring KPIs for
Turkish Airline

9. Future Performance
Errors Vs KPIs - RYANAIR

10. Future Performance
FORECASTING

11. Future Performance
FORECASTING
• Forecasting is a unique science, very useful in practice, and use widely in
many fields, especially Aviation.
• Today we are concerning on the application of Forecasting for Airlines, and
also Airports. Airlines can define their seasonality, and its impacts on
operations and maintenance programs, we have to define the right
demand for the right sector in the right segment.
• While most of Investors in Airline Industry are concerned for the
performance factors that’s Traffic and Capacity , RPK ,ASK , and Load
Factor. They evaluate them by comparing their values in past according to
month by month approach. here we look forward, to future to set targets.
• Forecasting is tilling us the future patterns for these factors, which
consequently, we can develop and forecast the expected Load Factor which
means also define the future performance for airlines.
• There are many methods of forecasting, but the approach of Max/Min
Signal Tracking, deliver the best scenario for the data that can be analyzed.
No grey region, just in a black and white / Good or Bad based on the
constrains that we are applied.

12. Future Performance
Basic concept of forecasting Model

13. Future Performance
Basic concept of forecasting Model
Directional Displacement

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

15. Future Performance
Max.& Min Signal Tracking Analysis
Maximum & Minimum Signal Tracking Analysis
- It is almost as Quality Control Chart, that bond
all values in the control limits, but by adjusting
the values of the two basic elements in the
forecasting model, (Displacement and Rotational
one) we try to satisfies the constrains i.e ± 4 –
Accepted Region , if not we have to match the
values of max & min as a final solution for best
value of R (Coeff. of correlation ).
- By implementing this approach, we can get the
best answer ( in black or white no grey answer).
R2 > 80%
AND
-4 < T.S.< 4

16. Future Performance
Accuracy Forecasting Matrix
By setting the constrains for Accuracy of
Forecasting, Four possible outcomes we can get :
Fair, Mislead, Unrelated and Poor
R2 > 80%
AND
-4 < T.S.< 4
Fair : All Constrains are satisfied.
Mislead: Even R is GOOD, while T.S.
is not, the possibility of Mislead is
there, due to displacement effect.
(almost Fair – need visual sight)
Unrelated : R is poor even T.S. is
GOOD. ( no relation )
Poor : Both ( R + T.S) are out of the
constrains region.

17. Future Performance
Case Study :

18. Future Performance
Basic Data Base
(Three years data: 2012-2014)
36 months data

19. Future Performance
Total Passengers
Segment
2015-2016

20. Future Performance
Total Passengers
Forecasting 2015-2016

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(RPKs)
Revenue Pax Kilometers
Forecasting - (2015-2016)

22. Future Performance
Revenue Passenger Kilometers - RPKs
Forecast 2015 - 2016

23. Future Performance
(ASKs)
Available Seat Kilometers
Forecasting - (2015-2016)

24. Future Performance
Available Seat Kilometers - ASKs
Forecasting - (2015-2016)

25. Future Performance
Load Factor %
Forecasting – (2015-2016)

26. Future Performance
Load Factor %
Forecasting – (2015-2016)

27. Future Performance
( Distance Flown )
Kilometers × 1000 - Km
Forecast 2015 - 2016

28. Future Performance
Kilometers × 1000 - Km
Forecasting 2015 - 2016

29. Future Performance
CYCLES - Total
Forecasting – (2015-2016)

30. Future Performance
Cycles – Total
Forecasting – (2015-2016)

31. Future Performance
GARGO Segment
CARGO and MAIL (tons)
Forecasting 2015-2016

32. Future Performance
CARGO and MAIL (tons)
Forecasting 2015-2016

33. Future Performance
Accuracy Forecasting Matrix
The outcomes of Accuracy
Forecasting Matrix are :
- PAX, RPK, ASK, Flights,
Cargo & Mails, and Km are
in (Mislead) but they are
almost Fair as R is High and
S.T. lay on both sides of
trend line i.e displacement
effect is Zero not on one
side, but they are greater
than ±4 so they lay on the
actual data.
- Load Factor is in Poor
region.

34. Future Performance
Analysis
– Seven parameters are addressed in the analysis, all shows a
positive trend.
– Many performance parameters are studied as
– Traffic : - in terms of Passengers ( Pax )
– Capacity :- in terms of Available Seat Kilometers (ASKs)
– Load Factor :- it is the outcome of RPK/ASK.
– Distance :- in terms of Kilometers.
– Cargo and Mail : in terms of tons.
– The period of 2015-2016 is forecasted for the propose of setting
targets .
– The study shows, that Turkish Air work in many business unit to
develop a business chains i.e travelers, tourism and cargo in a
feeding loop system.
– The outcomes are fairs with very high Coefficient of Correlations.

35. Future Performance
Results

36. Future Performance
Summary
• Most of Investors in Airline Industry are concerned for the
performance factors that’s Traffic and Capacity , RPM ,ASM ,
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.
• Most of the data are fairly fitted, with a minimum errors,
Except Load Factor comes with a poor forecast.
• The results shows that there will be a significant increase in Passengers, ASK,
RPK, CYCLES, Kilometers. While the forecasting results for load factor is not
accurate figure due to low coefficient of correlations and low value of signal
tracking.

37. Future Performance
Reading In The Future

38. Future Performance
Welcome In The Club
Thanks !

39. Future Performance
Contact
• Mohammed Salem Awad
• Chairman Adviser – Yemenia
• Tel: 00967 735222692
• Email: mohammed.hadi@yemenia.com
smartdecision2002@yahoo.com