Future Performance
Reading In The Future (4)Case Study
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Mohammed Salem AwadhAviation Consultant
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
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Outline 1/2
• Airline Market Segmentation• Key Performance Indicators For Airlines• Errors Vs KPIs• Forecasting – Basic concept of forecasting Model– Forecasting – Trend vs. Seasonality– Model Constrains– Max.& Min Signal Tracking Analysis
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Outline 2/2
• Case Study : ( Air Canada ) • Basic Data Base ( Three years data )• Forecasting
– Traffic 2014– Capacity 2014– Evaluation - Actual vs Forecast– Traffic 2015 – Capacity 2015– Expected Load Factor 2015
• Analysis• Summary
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Business Units of Icelandair Group
- Five business Units that Icelandair addressing in their reports , Mainly 1- International Flights, 2- Regional And Greenland Flights, 3- Charter Flights, 4- Cargo, 5- Hotels,- Four are analyzed while Charter Flights is not (as no seasonality patterned ). - The analysis is concentrated on the main KPIs as PAX, ASKs, L/F,. ATKs, FTKs, and Room Utilizations.
- 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
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K.P.I For Airlines
• Key Performance Figures• Capacity = ASM( available seat miles )
• Traffic = RPM ( revenue passenger miles )
• Load Factor ( LF ) = RPM/ASM
Traffic
Capacity
Targets & KPIs
Load Factor
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K.P.I For Airlines• K. P. I for Lufthansa Group:
Each Airline has its own KPIs policy, ASK , PAX & L/F are main measuring
KPIs for Icelandair
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Errors Vs KPIs
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FORECASTING
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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 , RPM ,ASM , 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 we are applied.
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Basic concept of forecasting Model
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Basic concept of forecasting Model
Directional Displacement
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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
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Max.& Min Signal Tracking AnalysisMaximum & 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
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Accuracy Forecasting MatrixBy 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.
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Case Study :
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Basic Data Base (Three years data: 2012-2014)
36 months data
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INTERNATIONAL Segment
2015
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Passengers Forecasting 2015International Pax (International Flights)
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Available Seat Kilometers - ASKs Forecasting - 2015 (International Flights)
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Load Factor % Forecasting - 2015 (International Flights)
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REGIONAL AND GREENLAND
Segment 2015
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Passengers Forecasting 2015REGIONAL AND GREENLAND PASSENGERS
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Available Seat Kilometers – 2015 ForecastREGIONAL AND GREENLAND PASSENGERS
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Load Factor % 2015 - ForecastREGIONAL AND GREENLAND PASSENGERS
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GARGOSegment
2015
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CARGO Forecasting 2015Available Tone Kilometers * 1000
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CARGO Forecasting 2015Freight Tone Kilometers * 1000Available
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HOTELS RoomSegment
2015
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HOTELS Room Forecasting 2015Available Hotel Room Nights
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HOTELS Room Forecasting 2015Sold Hotel Room Nights
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Utilization of Hotel Rooms % 2015 - Forecast
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Accuracy Forecasting Matrix
- The outcomes of Accuracy Forecasting Matrix are :- FTK ( Fair )- L/F R&G ( Poor )- Remaining are in
(Mislead) but they are almost Fair as R is High and S.T. lay on both sides of trend line but they are greater than ±4 so they lay on the actual data.
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Analysis – Four Segments are addressed in the analysis, three are shows a positive
trend, while one is not. Which is regional and Greenland segment.– 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.– Hotels Utilization :- it is the outcome of (Sold Rooms)/(Available Rooms).– The period of 2015 is forecasted for the propose of setting targets . – The study shows, that Iceland air work in a business chains i.e travelers,
tourism and cargo in a feeding loop system.– The outcomes are fairs with very high Coefficient of Correlations.
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Results
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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.
• The data is fairly fitted, with a minimum errors.• The results shows that there will be slight increase in international Passengers and
international ASKs for 2015, While the load factor will be a stable. • The expected L/F for Int. Pax. 2015 = 78 %• The expected L/F for Reg. & Greenland Pax. 2015 = 72 %• The expected Utilization for Hotels in 2015 = 74 %
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Welcome In The Club
Thanks !
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Contact
• Mohammed Salem Awad • Chairman Adviser – Yemenia • Tel: 00967 735222692• Email: [email protected] [email protected]
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