Route Development - it is task of airlines that done by airports, as most of airports in world try to convince airlines to operate and used their airports, the issue, is not the huge facility and or service, but it is a business, if airline does not get a business, then it is no need to operate to that destination.
This presentation introduces readers to airline industry's two most common networks. It also compares the features of the two and highlights scenarios when one may be more profitable than the other.
Airlines are concerned for route development, but if there is no business for certain routes/city, there will be no operation to that city/airport. While airports acts as facilitators for airlines to encourage them to operates for new routes or increase their frequencies. also airports offered a good service at a most convenient cost for airlines. That is why each airport in the world is always concerned about the route development, they are publishing the airlines traffic/statistics on monthly bases, exploring the future business potential of existing/operating routes.
airBaltic forecasting 2013, based on period of 2009-2012.
many scenarios are addressed, as best , trend, worse, and Final, the accuracy of these models are measure by developing Forecasting Accuracy Matrix.
Route Development - it is task of airlines that done by airports, as most of airports in world try to convince airlines to operate and used their airports, the issue, is not the huge facility and or service, but it is a business, if airline does not get a business, then it is no need to operate to that destination.
This presentation introduces readers to airline industry's two most common networks. It also compares the features of the two and highlights scenarios when one may be more profitable than the other.
Airlines are concerned for route development, but if there is no business for certain routes/city, there will be no operation to that city/airport. While airports acts as facilitators for airlines to encourage them to operates for new routes or increase their frequencies. also airports offered a good service at a most convenient cost for airlines. That is why each airport in the world is always concerned about the route development, they are publishing the airlines traffic/statistics on monthly bases, exploring the future business potential of existing/operating routes.
airBaltic forecasting 2013, based on period of 2009-2012.
many scenarios are addressed, as best , trend, worse, and Final, the accuracy of these models are measure by developing Forecasting Accuracy Matrix.
Air cargo forecasting for major airports in the world for 2014, about eight airports are study and accuracy forecasting matrix is developed, the study explore a fair results, based on the input of data, the forecast is developed, some of them are good and others are not, and depends on the analyses’ decision.
Keeping the Same Rule
Forecasting is not an easy task; we have to agree in what path we have to move ahead,
There is one trail forecasting approach, but if we try get the same answer for all our business units, that’s will be great, I know it is a tough way, but it can be achieved in these days.
We force all the three seasonality models results to follow the trend one
Yes we keep the same rule but in one step ahead – it is in the FUTURE
Predicting Aviation Industry Performance (L/F) - 2019Mohammed Awad
Developing targets is one of the major issues in the aviation industry. In the recent time, many aviation sources predict different figures, based on their own analysis, and sight for the global aviation market. The dilemma, that, there is no basic rules for the predictors, especially aircrafts manufacture companies.
This presentation is a comparison between by a planned system and classical system, in terms of controlling seasonality and annual forecasting, the final accuracy is measured by S. D.
United Kingdom (U.K.) Airports:
A Short term forecast by setting a new rules for defining targets
Annually Forecast (LHR): The best way to set up annual target and minimize the data discrepancy is to address the data by two trend models using the concept of 12 rolling months. We implement two trend models by using Add a trend line in XLS sheet
Setting KPIs level for measuring Airports Performance,
this addressing the traffic flow for airports, and how to set the a KPIs scale to define the performance of airport
Route development is always governed by two main factors, Supply and Demand, Supply in terms of capacity offered i.e Seats, Demand in terms of Traffic Demand i.e Passengers.
So Airlines are concerned for route development, but if there is no business for certain routes/city, there will be no operation to that city/airport. While airports acts as facilitators for airlines to encourage them to operates for new routes or increase their frequencies. also airports offered a good service at a most convenient cost for airlines. That why each airport in the world is always concerned about the route development, they are publishing the airlines traffic/statistics on monthly bases, exploring the future business potential of existing/operating routes.
Predicting Air Transport Industry - 2018 Mohammed Awad
Predicting Air Transport Industry based two input parameters - RPKs and ASKs, then using their forecasted results to predicted the Air Transport Industry Performance i.e Load Factor which is simply RPKs/ASKs
“Plans are nothing; planning is everything” One of the main factors for successes is good planning, especially when we plan for futures as to design objectives and set targets, but the issue when we plan for targets from some raw data, that may have concurrent results or figures as the case of Amsterdam airport. Really to set concurrent figures to get the same target is a hard task, So how to solve this dilemma!!!
Recently Airberlin reduce their capacity, by concentrating on a more profitable routes, Logically if we are squeezing the capacity (ASK)- SUPPLY , the other part – DEMAND will force to pump out i.e (RPK), then how we can get the complete picture, for 2016, definitely the load Factor should be increase in normal cases, … for this issue , there are two scenarios or results, first if the load factor increase significantly the Airberlin absorb the pressure of shifting their markets by increase the frequencies on their specific route which also aircrafts assist in this process by accepting more passengers than the usual figure in previous periods. But if the load factor is stable it means that a part of airberlin market spill to other competitors, and they are losing their markets ,yes the only benefits from this is the revenue or more specifically the YIELD, i.e is Yield is high enough to implement this reduction if so then they are in a safe side. While the cost will comes down due to the reduction in operation, means reduction in the variable cost.
the concept of this article, is to evaluate the results of previous models that I used them. One of the amazing results is the Model of, All Australian Airports, article :" The Job Almost Done" yes the model and parameters are still valid even for the period 2010-2012.
Air Cargo Forecast 2023 for Aviation IndustryMohammed Awad
Air Cargo Forecast addresses the trends in terms of figures based on the IATA air cargo newsletter. It looks that Air Cargo is the only business unit in aviation that has not been impacted by Covid 19
BCG Matrix Analysis for Airlines for period Dec 2019Mohammed Awad
The BCG Matrix provides a visual representation that aids decision-makers in understanding the relative position of each business unit within the overall portfolio. It helps in resource allocation, strategic planning, and identifying areas that require attention or investment. Remember that the implementation may vary based on the specific dynamics and challenges each airline faces.
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Similar to Airport forecasting issue 45 tls 2020 - Toulouse Airport
Air cargo forecasting for major airports in the world for 2014, about eight airports are study and accuracy forecasting matrix is developed, the study explore a fair results, based on the input of data, the forecast is developed, some of them are good and others are not, and depends on the analyses’ decision.
Keeping the Same Rule
Forecasting is not an easy task; we have to agree in what path we have to move ahead,
There is one trail forecasting approach, but if we try get the same answer for all our business units, that’s will be great, I know it is a tough way, but it can be achieved in these days.
We force all the three seasonality models results to follow the trend one
Yes we keep the same rule but in one step ahead – it is in the FUTURE
Predicting Aviation Industry Performance (L/F) - 2019Mohammed Awad
Developing targets is one of the major issues in the aviation industry. In the recent time, many aviation sources predict different figures, based on their own analysis, and sight for the global aviation market. The dilemma, that, there is no basic rules for the predictors, especially aircrafts manufacture companies.
This presentation is a comparison between by a planned system and classical system, in terms of controlling seasonality and annual forecasting, the final accuracy is measured by S. D.
United Kingdom (U.K.) Airports:
A Short term forecast by setting a new rules for defining targets
Annually Forecast (LHR): The best way to set up annual target and minimize the data discrepancy is to address the data by two trend models using the concept of 12 rolling months. We implement two trend models by using Add a trend line in XLS sheet
Setting KPIs level for measuring Airports Performance,
this addressing the traffic flow for airports, and how to set the a KPIs scale to define the performance of airport
Route development is always governed by two main factors, Supply and Demand, Supply in terms of capacity offered i.e Seats, Demand in terms of Traffic Demand i.e Passengers.
So Airlines are concerned for route development, but if there is no business for certain routes/city, there will be no operation to that city/airport. While airports acts as facilitators for airlines to encourage them to operates for new routes or increase their frequencies. also airports offered a good service at a most convenient cost for airlines. That why each airport in the world is always concerned about the route development, they are publishing the airlines traffic/statistics on monthly bases, exploring the future business potential of existing/operating routes.
Predicting Air Transport Industry - 2018 Mohammed Awad
Predicting Air Transport Industry based two input parameters - RPKs and ASKs, then using their forecasted results to predicted the Air Transport Industry Performance i.e Load Factor which is simply RPKs/ASKs
“Plans are nothing; planning is everything” One of the main factors for successes is good planning, especially when we plan for futures as to design objectives and set targets, but the issue when we plan for targets from some raw data, that may have concurrent results or figures as the case of Amsterdam airport. Really to set concurrent figures to get the same target is a hard task, So how to solve this dilemma!!!
Recently Airberlin reduce their capacity, by concentrating on a more profitable routes, Logically if we are squeezing the capacity (ASK)- SUPPLY , the other part – DEMAND will force to pump out i.e (RPK), then how we can get the complete picture, for 2016, definitely the load Factor should be increase in normal cases, … for this issue , there are two scenarios or results, first if the load factor increase significantly the Airberlin absorb the pressure of shifting their markets by increase the frequencies on their specific route which also aircrafts assist in this process by accepting more passengers than the usual figure in previous periods. But if the load factor is stable it means that a part of airberlin market spill to other competitors, and they are losing their markets ,yes the only benefits from this is the revenue or more specifically the YIELD, i.e is Yield is high enough to implement this reduction if so then they are in a safe side. While the cost will comes down due to the reduction in operation, means reduction in the variable cost.
the concept of this article, is to evaluate the results of previous models that I used them. One of the amazing results is the Model of, All Australian Airports, article :" The Job Almost Done" yes the model and parameters are still valid even for the period 2010-2012.
Air Cargo Forecast 2023 for Aviation IndustryMohammed Awad
Air Cargo Forecast addresses the trends in terms of figures based on the IATA air cargo newsletter. It looks that Air Cargo is the only business unit in aviation that has not been impacted by Covid 19
BCG Matrix Analysis for Airlines for period Dec 2019Mohammed Awad
The BCG Matrix provides a visual representation that aids decision-makers in understanding the relative position of each business unit within the overall portfolio. It helps in resource allocation, strategic planning, and identifying areas that require attention or investment. Remember that the implementation may vary based on the specific dynamics and challenges each airline faces.
Forecasting is an important tool for planning, so without planning, there will be a disaster that may happen, i.e what will happen in case of Force Major
For study new destinations, Gravity Model frequently use, which is a tough approach that may not work sometime due to many economic factors in the world and war crises.
Since we use small size of data, the model is not fit properly , but the approach is clearly defined.
Marsa Alam Airport should be supported by Airport Hotel,
Marsa Alam Tourism team, Egypt Air, and Egyptian Civil Aviation Authorities should talk the same language to setup an effective tourist package that will attractive the tourist.
Rush Hour Analysis,
Every city has its own pattern of traffic congestion that may reflects by a rush hour. Here we use leveling approach, that define by two factors - Rotational and Displacement. the idea is to define the right repeated cycle with minimum errors, and define the Rush Hour !
Has Airline Forecasting changed forever?Mohammed Awad
it is concern forecasting in Aviation,
two case studies are addressded, i.e global world, and Delta Airline, which shows the impact of Covid19, and its recovery in the future.
Back To Norms,
study about defining the seasonality patterned of Dubai Airport
Using Forecasting for both short term and long term - keeping the out come results.
The Organisation for Economic Co-operation and Development (OECD) is an international organisation that works to build better policies for better lives. their goal is to shape policies that foster prosperity, equality, opportunity and well-being for all. they draw on 60 years of experience and insights to better prepare the world of tomorrow.
Back to norms, is an article that address the event of Black Swan, which is a very hard situation for airline industry, but it shows that there is some light at the end of the tunnel. that may recover soon.
Fare Mapping Analysis,
It is the best way to establish a foundation for Fare, It gives a complete picture for the condition of the flight for sector SHJ-AMM using the input of G9 airline (Al Arabia). in terms of CASK, Aircraft capacity and Fares.
Back To Norms,
It is addressing the impact of Covid19, and when to recover, both IATA are used Pax and Cargo, then we used Dlephi method to reflect the judgment of expert people to reflect their opinion in real life.
This research is up todate - we used IATA information
Is Low Cost Carrier Profitable, this time we hold differents senarios by varing load factors and fares, the network is huge and large 128 sectors. hope to enjoy
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Implicitly or explicitly all competing businesses employ a strategy to select a mix
of marketing resources. Formulating such competitive strategies fundamentally
involves recognizing relationships between elements of the marketing mix (e.g.,
price and product quality), as well as assessing competitive and market conditions
(i.e., industry structure in the language of economics).
1. Airport Forecasting - 2020
(Issue No. 45)
Toulouse Airport (TLS)
There is no means to forecast, if we do not hold it in the right time.
Long time ago as we were in the schools we learnt that – 80% value of R – square was accepted level
for best fitting for the Data. Today, in practice and real life, the margin of fitting is too tight, and the
change in values of R- square has a significant meaning on final results. Therefore, we are exploring
all the possible option of the outcomes – that put the top management on a solid ground to stand and
get a clear picture for the future.
Annual Passengers Forecast:
There are three possible outputs for forecasting, positive growth, leveling (Zero Growth) and negative
trend, and the best way to set up annual target and minimize the data discrepancy is to address the
data by two trend models using the concept of 12 rolling months.
First – General Trend Model using the concept of Straight Line equation – defining general trend.
Second – Most Recent Data Trend Model Using a Polynomial Model – Second-degree equation.
This reflects the impact of most recent data on the path of general trend. The mid-point is the most
convenient forecast annual result at Dec 2020. So as long as the gap between two models is small, the
more accurate approaching value for setting annual target otherwise we have to select the half way
distance between two extreme targets of these two models provided that Dec 2020 > Dec 2019.
Scenario 1: Preset Annual Target = Passengers = 9,673,392 Pax.
At annual growth 1.2 % and R- square = 95.01 % and boundary error range -5.18 to +6.57 %, we
select preset value for Dec 2019 = 9,673,392 as Dec 2019 > Dec 2020 for first scenario. –
(Recommend)
Scenario 2: Optimum Solution. = Passengers = 9,969,622 Pax.
This is an optimum solution without any pre-set targets or constrains that governed the analysis, the
outcome results = Pax 2020 = 9,969,622, at annual growth 2.42 %, R- square = 95.56 % and
boundary error range -3.01 to +5.57 %.
(below : how to read the Graph)
By: Mohammed Salem Awad
Aviation Consultant
Data Source:
https://ec.europa.eu/eurostat/data/database