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Winners and Losers

Winners and Losers



Three Articles are published

Three Articles are published
Cost of Delay, Winners Vs Losers, and Airport Forecasting all topic are related to airlines and aviation industry



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    Winners and Losers Winners and Losers Document Transcript

    • Civil Aviation & Meteorology Authority (Yemen) July - September 2012, issue 16 Winners vs. Losers Aday in Sheharah Airports Forecasting www.camamagazine.com The new Aviation Systems More Safety and Welfare for the Passenger
    • study 21 CAMA Magazine | issue 16 | September, 2012 Cost of Delay, Rescheduling and Cancellation In Airlines Introduction Usually Airlines are suffering from flights delay issues, but most of them control these problems and their causes, so the issue of flight delay may create a bad impression on the airline image and its brand name in the market, and consequently it is directly related to the concerned airline operation divisions and departments, from maintenance, flight operation, commercial and customer service, as they are interacted and integrated divisions that serve for one mission, so every division has its own rules and impacts on dispatch the flight on time, and any negligence may reflects on airline final performance, and cause the delay of the flight. In aviation industry the cost of delay is considerably high due the high gained revenue of the flights and high direct fixed operating cost for a certain type of aircraft hence we measure the activities of an airline by its performance which usually addressed by the performance report of Operation Control Committee OCC. Where the maintenance and material divisions are the main airline departments that support the operation, as they are responsible for aircraft technical readiness and fulfill the provision of spare parts of the aircraft, and tracking/ monitoring the technical operating performance by papering reliability report, which is similar as performance report, but its results are technical oriented, i.e defining technical problems and failure diagnostic before its happen and cause a delay or cancelation, which play a major rule in preventive maintenance program for the aircraft. Finally by referring to Boeing Company reports, the engineering and maintenance issues and problems for aircraft are represents 30-40% of total delay cost for the flight in airline industry.8 Prepared by: Mohammed Salem Awad Research Scholar – Aviation Management
    • STUDY22 OCC Operation Control Committee: The weekly report of this committee is one of the main sources of airline activity evaluation and it is an effective tool to explore and define deviations so a proper action may take on time and most of operating and serving departments represents in the committee, so this report rise the initial signals to predicate defect or trouble a certain failure in the airline activity for one week period. Delay Cost: It is too complicated to evaluate and calculate the delay cost in the airline industry and its impacts on the image and the brand of the airline. So we can refer to Boeing terms and definitions for delay cost that addressed in AGIFORS - Denver which are; 1- Passenger direct cost 2- Direct Operating Cost 3- Cost of unavailability of scheduling Aircraft 4- Cost of losing the image and the loyalty for the airline. In our case we will use only two factors in the analysis only: 1- Passenger direct cost 2- Direct Operating Cost the calculation of delay or cancellation cost will as the following: Direct Operating Cost + expected income revenue of the delay or cancelled flight. And according to the study of American Airlines – domestic routes, the results are: Delay from: 0 ~ 15 minute No Calculation of Cost 16 ~ 60 minute 0.25 % ticket/min/pax 1 ~ 2 Hours 0.5 % ticket /min/pax Approximately 1 out 8 passengers will probably not buy their next ticket on this airline. 2 ~ 5 Hours All passengers will probably not buy tickets on this airline again for at least a year. And in this stage the growth of delay cost increase exponentially until reach to 5 hours delay period (out of business). While the next figure explain the relationship between these costs and its average values, indicating the direct cost of passenger may happen after 20 min of delay time, and its impact on the passenger loyalty, image and the brand value of the airline. Impacts of Engineering and Maintenance: Referring to the Boeing Study, the share impact of maintenance and engineering causes may reach 30-40 of total delay causes. And the technical causes are the main reasons for cancellation of the flights and as its shows in the previous figures, the maximum delay period for maintenance cause is 45-120 if there is no cancellation. And the consequential effects of late aircraft arrival play a major rule in rescheduling the flights again. Delay Cost - Yemenia Case Study: The period of 02/01/2010 to 12/03/2010 characterize by repeated many delays in flights –Yemenia. Among of that , the technical delays and engine failures of B737-800 fleet which create a total mess in the flight scheduling program. So the dealy cases can be address in two directions; First: counting the repeated delays issues Second: the delay time So delays can be caused by one of the following reasons: 1- Delay of the flight of the same aircraft type. 2- Delay of the flight may cause the need to change the type of the aircraft from bigger to smaller capacity which lead to extra cost of spill passengers. 3- Delay of the flight may cause the need to change the type of the aircraft from smaller to bigger capacity CAMA Magazine | issue 16 | September, 2012 Figure (1) Measuring the time period costs American Airlines Study. Figure (2) Delay Cost Elements - American Airlines Study.
    • 19STUDY 23 CAMA Magazine | issue 16 | September, 2012 Delay Time in Minute Figure (3) Delay Factors of Yemen Airways Figure (4) Frequency Distribution of Delay Periods Delay Categories FrequenciesFrequencies which lead to extra cost of losing the opportunity of un utilize seats for sale in last minutes. 4- Aircraft Grounded cost, by sending another aircraft for taking the passengers and supported spare parts. 5- Some time suddenly two aircrafts ground in the same time, and rise a hard time for planners and consequently may lead to cancel the flight. 6- Un readiness of the aircraft for unexpected time. 7- Longer maintenance programs may lead to delay the flights. Analysis: In spite of defining Boeing Company the main factors that may cause the delays, pointing out the maintenance /engineering and bad weather but yemenia analysis results indicates another factors that impact high influence of those mentioned in Boeing Study. However technical and engine failures remains the main factor in the period of 02/01/2010 to 12/03/2010 1- Transit Passengers 2- Technical Problem 3- Airport Security 4- ATC 5- Late Arrival of Aircraft 6- Bad Weather 7- Maintenance Problems 8- Other factors As indicated in graph, the other factors take the large share in the delay reasons, yemenia should review all the delay items category so that the other reasons well defined in the analysis and re casted in the right way. Also similar category should be merge to be one category as maintenance and technical. This lead us to the result of the analysis, so Number of Delays with less than 20 min =121 delays with cumulative time = 1355 min Number of Delays with greater than 20 min =87 delays with cumulative time = 4185 min but for technical delays, it take larger time to fix and rectify in spite of hidden function issues Summary: 1- The analysis show the un availability of support fleet, as the scheduling designed with one supported aircraft. But in some cases of two aircraft grounded in the same time led to a total mess in scheduling that need to rescheduling and delay the other flights. 2- The technical delay have the majority causes of delays, and when its happen, its take a long time. 3- In spite of the impact of transit passengers on delay, the maximum allowable time period for transit passengers is 45-60 min, but the delay period may reach to 5 hours or more and effects on the airline image in the market. 4- Advanced and prior corporation between commercial and technical departments so that they adapted and implemented a the right scheduling without interruption based on the sound of the market. 5- Brand name of the airline in the market may get lose, if the airline repeat these delays, and changing the capacities of aircrafts in the last minutes.■ 30~40% from the total delay cost for the flight in airline industry in the engineering and maintenance issues and problems for aircraft.
    • 24 study Winners vs. Losers A irline industry is a perishable industry. Today big names in the aviation world declare their bankruptcy, why!, I don’t think they don’t have the facilities and tools to afford recovery and repositioning their carriers tracks. Actually it is like a big ship sinking and deriving (driving) everything down. Today airline business runs as a wheel. If airlines make a good start and continue fairly with economic shocks from time to time, unless it will collapse. In some cases for political reasons airline survive, while some counties prefer to spend the money on their flag carriers. If the Thumb is characterized by 32 marks and Eye by 520 marks, then how we can define airline characteristic of point to point airline business model. Definitely the basic airline data are Traffic Demand, Market Fare, and Operating Network (Distances). So each airline is characterized by these three mean factors, while the fourth one is its Operating Cost. We will span and manipulate those three factors while cost element will be considered as defined single figure (as step function). Off course we can use the actual value of the airline cost in the analysis, but that will be meaningless as the objective is to develop the optimum operating curve of airline which represents the characteristic of the airline.So based on the airline inputs the issue can be classified by multi-dimensional matrix which develop and reflect the outcomes of optimum operating curve of the airline. Consequently defining airline positioning in that Matrix as winner or loser airline!. Mohammed Salem Awad Research Scholar Aviation Management CAMA Magazine | issue 16 | September, 2012
    • 25study Summary The key principle of the analysis is to position the tangible line that landmark the coordinate of the matrix on the curve. The outcome results will be of RASK and CASK; while by mapping optimum operating curve, the board explores the complete financial picture of airline position in region. In case mix fleet airline, the annual final results may give some initial signals of airline financial health.■ Survival Airline: This represents upper-right part above the optimum operating curve. It is initially started by Low Cost Carriers and ended by Mega Carriers driven by cost and relayed on economy of scale, fleet commonalty, large capacity, higher frequency and many economic factors that maintain the airline in survival level. It is hardly gaining its profits with a very tight margin. Its RASK is slightly higher than the CASK. This situation is more likely to move winners situation if they reduce their cost. Critical Airline: This is the lower-left part below the optimum operating curve. Airlines suffer a hard situation where they are operating by small capacities in a low yield environments. It may represents some regional airlines where their CASK is usually matching their RASK. It is more likely to move the loser situation. The issue of these airlines is serving a wrong markets. They don’t define their markets properly. While they can be moved to winner situation if they apply cost reduction strategy and implement turnaround philosophy. Loser Airline: Most of airlines located in this part. It is the lower-right part, simply indicated when CASK is greater than RASK. It is characterized by higher cost with low yield. These airlines need urgent restructuring e and implementing cost reduction strategy. Carries do not have a clear vision and strategy. It may represent flag carriers. Some mega carriers that have poor brand name. RASK & CASK: The main product of the airline is offering seat to move from one city to another city, i. e. distance, in aviation terminology called ASK, Available Seat Kilometers. The related cost element is called CASK, i . e. Cost/ASK. Likewise in revenue part, the income revenue determine by the term RASK, i. e. Revenue/ASK. Simply Profit equal Revenue minus Cost while in airline industry may represent by dividing this equation by ASK, resulting the following form: PASK = RASK-CASK where PASK represent Profit per ASK. Allocating the Right Aircraft Capacity: The main factor for successful airlines is to match the demand passengers/market demand by the right configuration of aircraft. Based on airline inputs of passengers, fares and proposed network, using the concept of U curve technique, the right capacity can be defined. It might be matched the exciting aircraft capacity it might be not. If it matches, the airline on right track. If not, the airline needs to reposition and restructure its fleet. Airline Optimum Operating Curve: In point to point airline business model, airline can be defined by its Designed Network, Market Fares, and Demand Passengers. These are the basic factors that derive Optimum Operating Curve of the airline. It acts as thumb for airline that differentiates airline from other airlines,, no two airline can be similar. The unit cost per ATK or ASK is used as step function in these scenarios, to plot and map optimum operating curve of the airline. Mathematically, the airline formula is defined by the following terms ,i. e, (Capacity, Frequency) = function of (Pax, Fare, Distance, and Cost). Based on airline strategy, either to emphasis on capacity or frequency, these two terms have a counteract effects. So the airline can position its fleets according to the actual cost the aircraft and its configurations and capacities in terms of seats, i. e. aircrafts that lay on the curve represent the best solution for the airline. But if we look closely to the curve, we can read and explore airline heath situation by defining the boundaries of the analysis in multi-dimensional matrix. Winner vs Loser Position Matrix Based on the output of optimum operating curve of the airline, the exciting fleet will plot and map on the graph, there will be four decision outcomes to reach the healthy situation of airline. These situations are Winner, Survival, Critical and Loser airlines. Usually the starting origin point is 160 seat Winner Airline: Airlines position themselves on the upper- left part above the optimum operating curve. They are characterized by high yields, lower cost, medium capacity, clear strategy and well organized and structure airline. They operate based on the sound of the market, these includes Air Taxi, Business Jets, and Legacy Airlines. Simply it can be realized when, RASK is greater than CASK in their annual reports. Survival Loser Winner Critical CostinUS$ C Total Cost Selected Parameter A Cost of Services B Cost of Lose Opportunity CAMA Magazine | issue 16 | September, 2012 A321 A318 A320 A319 B737-800 B737-700 Capacity(Seat) Cost per ATK
    • 28 Prepared by: Mohammed Salem Awad Research Scholar – Aviation Management Matching Long Range Data Targets By Short Range Data Targets “Plans are nothing; planning is everything.” Dwight D. Eisenhower Airports Forecasting Forecasting is the right tool for a fair decision making, we use it to create a proper plans ,activities and setting up budgets. But what is the right effective model, what are the right parameters to measure the goodness of fits, and how to plan to match the long range targets by a short range targets, can we get same answer from different models. This is what we will address it in…. Nice Airport Case Study: 1- Developing Long Range Targets: Trend Model: Based on annual historical data period (1950-2011) Input Data: 51 sets (Annually) Coefficient of Determination: 99.6% Signal Tracking: 0.0000011 Results: Passengers Forecast 2012= 10,467,360 Passengers Forecast 2013= 10,493,391 2- Developing Short Range Targets: Seasonality Model: Based on monthly 3 years data period (2009-2011) Input Data: 36 sets (Monthly) Coefficient of Determination: 96.7% Signal Tracking: -30.14 Results: Passengers Forecast 2012= 10,467,360 Passengers Forecast 2013= 10,493,391 Summary: The results are fairly matched, so it possible to plan in such a way that, we utilize the annual trends to meet the annual cumulative forecast of the seasonality model for two forecasted years, keeping in mind the pre-request constrains for both models. 400000 500000 600000 700000 800000 900000 1000000 1100000 1200000 1300000 NoofPassengers TIME (Month) Forecast Actual 0 2000000 4000000 6000000 8000000 10000000 12000000 Passengers Years Forecast Passengers Forecasting 2012, 2013 Seasonlity Model Forecasting 2012, 2013 1950 - 2011 Passengers Coefficient of Determination = 0.996 Signal Tracking = 0.0000011 R 2 = 96.7% S.T.= -30.17 2012 (F)= 10,467,360 Pax 2013 (F)= 10,493,391 Pax 2012(F)= 10,467,360 Pax 2013(F)= 10,493,391 Pax CAMA Magazine | issue 16 | September, 2012
    • 29AIRPORTS Forecasting Airports Forecasting: Airport forecasting is an important issue in Aviation industry. It becomes an integral parts of transportation planning. It sets targets and goals for the airports, either for long term or medium term planning. The primary statistical methods used in airport aviation activity forecasting are market share approach, econometric modeling, and time series modeling. Model Used: BaBased on a historical data of the airports, (3 years on monthly bases) the mathematical model is developed where its fairness and goodness of fit can be defined by two important factors: R 2 (Coeff. Of Determination) > 80% S. T (Signal Tracking) ..(-4 < S.T. < 4) This time we try to set (S.T.) to Zero Airport Performances: There are many factors that may measure the airport performance, mainly: 1) Number of Passengers 2) Aircraft Movement and; 3) Freight SANA’A Airport Sana’a International Airport or El Rahaba Airport (Sana’a International) (IATA: SAH, ICAO: OYSN) is an international airport located in Sana’a, the capital of Yemen. Recently Yemen passes in a transition phase, as results a democracy. This situation effects on 2011 data base. So the basic analysis addressing 2008, 2009, and 2010. And the forecasted period are 2011 and 2012. But in this issue we are addressed the Yemenia and Other Operators Yemenia: Passenger Forecasting 2012 = 764,398 Pax Peak Periods: July-August Annual Growth : (0.02) % The Model is not fair as R = 44% Other Operators: Passenger Forecasting 2012 = 600513Pax Peak Periods: July Annual Growth : 0.08 % The Model is not fair as R = 77% Total – Yemenia and Other Operators Passenger Forecasting 2012 = 1,340,118Pax Peak Periods: July - August Annual Growth : 0.01 % The Model is not fair as R = 66% yemen Airports Sanaa Airport, Forecasting 2011, 2012 Seasonlity Model (Other Carriers) Sanaa Airport, Forecasting 2011, 2012 Seasonlity Model (Yemenia) Sanaa Airport, Forecasting 2011, 2012 Seasonlity Model (IY + Other Carriers) 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000 70000 NoofPassengers TIME (Month) Forecast Actual 80000 90000 100000 110000 120000 130000 140000 150000 160000 NoofPassengers TIME (Month) Forecast Actual R 2 = 77% S.T.= 00 2012(F) = 600,513 Pax Annual Growth : 0.08 R 2 = 66% S.T.= -0.00 2012(F)= 1,340,118 Pax Annual Growth : 0.01 40000 50000 60000 70000 80000 90000 100000 NoofPassengers TIME (Month) Forecast Actual R 2 = 44% S.T.= 00 2012(F)= 764,398 Pax Annual Growth: (0.02) CAMA Magazine | issue 16 | September, 2012
    • 30 AIRPORTS Forecasting international Airports Paris-Charles de Gaulle Airport (IATA: CDG, ICAO: LFPG) (French: Aéroport Paris- Charles de Gaulle), is one of the world’s principal aviation centers, as well as France’s largest airport. It is named after Charles de Gaulle (1890–1970), leader of the Free French Forces and founder of the French Fifth Republic. It is located within portions of several communes, 25 km (16 mi) to the northeast of Paris. The airport serves as the principal hub for Air France. In 2011, the airport handled 60,970,551 passengers and 514,059 aircraft movements, making it the world’s sixth busiest airport and Europe’s second busiest airport (after London Heathrow) in passengers served. Passenger Forecasting 2012= 62,166,461 Pax Annual Growth: 2.6% The Model is fair fitted as R 2 = 93% Denver International Airport (IATA: DEN, ICAO: KDEN, FAA LID: DEN), often referred to as DIA, is an airport in Denver, Colorado. In 2011 Denver International Airport was the 11th- busiest airport in the world by passenger traffic with 52,699,298 passengers. It was the fifth-busiest airport in the world by aircraft movements with over 635,000 movements in 2010.. Denver International Airport is the main hub for low-cost carrier Frontier Airlines and commuter carrier Great Lakes Airlines. It is also the fourth-largest hub for United Airlines. Passenger Forecasting 2012 = 53,986,884 Pax Annual Growth: 2.21% The Model is fair fitted as R 2 = 97.7% Chicago O’Hare International Airport (IATA: ORD, ICAO: KORD, FAA LID: ORD), also known as O’Hare Airport, O’Hare Field, Chicago Airport, Chicago International Airport, or simply O’Hare, is a major airport located in the northwestern-most corner of Chicago, Illinois, United States. prior to 1998, O’Hare was the busiest airport in the world in terms of the number of passengers. O’Hare has a strong international presence, with flights to more than 60 foreign destinations: it is the fourth busiest international gateway in the United States behind John F. Kennedy International Airport in New York City, Los Angeles International Airport and Miami International Airport. Passenger Forecasting 2012 = 67,859,340 Pax Annual Growth: 1.34 % The Model is fair fitted as R 2 = 97.3% Forecasting 2012, 2013 Seasonlity Model Forecasting 2012, 2013 Seasonlity Model Forecasting 2012, 2013 Seasonlity Model 3000000 3500000 4000000 4500000 5000000 5500000 6000000 6500000 NoofPassengers TIME (Month) Forecast Actual R 2 = 93 % S.T.= 0 2012(F)= 62,166,461 Pax 2013 (F)= 63,812,317 Pax Annual Growth= 2.6% 3000000 3500000 4000000 4500000 5000000 5500000 6000000 NoofPassengers TIME (Month) Forecast Actual R 2 = 97.7 % S.T.= 0 2012 (F)= 53,986,884 Pax 2013 (F)= 55,184,393 Pax Annual Growth: 2.21% 3000000 3500000 4000000 4500000 5000000 5500000 6000000 6500000 7000000 NoofPassengers TIME (Month) Forecast Actual R 2 = 97.3% S.T.= 0.00 2012 (F)= 67,859,340 Pax 2013 (F)= 68,773,005 Pax Annual Growth: 1.34% CAMA Magazine | issue 16 | September, 2012
    • Edmonton International Airport (IATA: YEG, ICAO: CYEG) is the primary air passenger and air cargo facility in the Edmonton region of the Canadian province of Alberta. It is a hub facility for Northern Alberta and Northern Canada, providing regularly scheduled nonstop flights to over fifty communities in Canada, the United States, Latin America and Europe. It is one of Canada’s largest airports by total land area, the 5th busiest airport by passenger traffic, and the 10th busiest by aircraft movements. Operated by Edmonton Airports and located 14 NM (26 km; 16 mi) south southwest of downtown Edmonton, in Leduc County, and adjacent to the City of Leduc, it served over 6.2 million passengers in 2011. Passenger Forecasting 2012 = 6,329,057 Pax Annual Growth : 1.4 % The Model is fair fitted as R2 = 91.9 % London Heathrow Airport or Heathrow (IATA: LHR, ICAO: EGLL) is a major international airport serving London, England, United Kingdom. Located in the London Borough of Hillingdon, in West London, Heathrow is the busiest airport in the United Kingdom and the third busiest airport in the world (as of 2012) in terms of total passenger traffic, handling more international passengers than any other airport around the globe. It is also the busiest airport in the EU by passenger traffic and the third busiest in Europe given the number of traffic movements, with a figure surpassed only by Paris- Charles de Gaulle Airport and Frankfurt Airport. Passenger Forecasting 2012 = 70,557,827 Pax Annual Growth : 2.6 % The Model is fair fitted as R2 = 89 % Nice Côte d’Azur Airport (IATA: NCE, ICAO: LFMN) is an airport located 3.2 NM (5.9 km; 3.7 mi) southwest of Nice, in the Alpes-Maritimes department of France. The airport is positioned 7 km (4 mi) west of the city centre, and is the principal port of arrival for passengers to the Côte d’Azur. It is the third busiest airport in France after Charles de Gaulle International Airport and Orly Airport, both in Paris. Due to its proximity to the Principality of Monaco, it also serves as the city-state’s airport, Some airlines marketed Monaco as a destination via Nice Airport. it is also serves as a hub for Air France. Passenger Forecasting 2012 = 10,496,380 Pax Annual Growth : 2.62 % The Model is fair fitted as R2 = 98.3 % 31AIRPORTS Forecasting international Airports Forecasting 2012, 2013 Seasonlity Model Forecasting 2012, 2013 Seasonlity Model Forecasting 2012, 2013 Seasonlity Model 400000 500000 600000 700000 800000 900000 1000000 1100000 1200000 1300000 NoofPassengers TIME (Month) Forecast Actual Optimum Solution R 2 = 98.3 % S.T.= 0 2012 (F)= 10,496,380 Pax 2013 (F)= 10,772,005 Pax Annual Growth : 2.6 % 450000 470000 490000 510000 530000 550000 570000 590000 610000 NoofPassengers TIME (Month) Forecast Actual R 2 = 91.9% S.T.= 0 2012(F)= 6,329,057 Pax 2013 (F)= 6,419,625 Pax Annual Growth= 1.4% 4000000 4500000 5000000 5500000 6000000 6500000 7000000 7500000 NoofPassengers TIME (Month) Forecast Actual R 2 = 89% S.T.= 0 2012(F)= 70,557,827 Pax 2013(F)= 72,406,685 Pax Annual Growth: 2.6% CAMA Magazine | issue 16 | September, 2012