Kenzamethodology Prepared & presented by Daniel SALLIER - ADP.

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Presentation transcript:

Kenzamethodology Prepared & presented by Daniel SALLIER - ADP

Kenza methodology 2 © ADP, April 2002 Content Method assumptions 3 Traffic characterisation4 General or business oriented market5 Principles of the computation process7 Starting market8 Maturing market9 Mature market10 Leisure oriented market11 Market typology14 How different countries compare15 Same threshold of income, different market16 Market diagnostic17 Which fare policy?18 Who is travelling and how often?19 Can a fare decrease stimulates the market?20 What about the market turnover?21 Sector growth limitation22 Conclusions23

Kenza methodology 3 © ADP, April 2002 Method assumptions

Kenza methodology 4 © ADP, April 2002 Traffic characterisation General, business or leisure oriented traffic ; Ethnic traffic ; Other specific traffic. Before analysing or forecasting traffic, its characteristic should be determined : The method described in this document can only be applied for the first type of traffic.

Kenza methodology 5 © ADP, April 2002 General or business oriented market Only a part of the population has a social status which allows them to travel for leisure or business reasons ; This social status is characterised by income level ; The return ticket price determines a minimum threshold of income below which the number of people travelling by air is virtually insignificant ; The threshold of income and the cumulative distribution of incomes within the population, determines the number of passengers ; The region is presumed to be homogenous in terms of economical and population growth as well as distribution of income within the populations.

Kenza methodology 6 © ADP, April 2002 General or business oriented market (continued) Normalised income (x GDP per capita) 0% 10% 20% 30% 40% 50% 60% 70% 80% 100% 90% Cumulative distribution of income Threshold of income before fare decrease Part of the population which can travel after fare decrease % of population Threshold of income after fare decrease Part of the population which can travel before fare decrease

Kenza methodology 7 © ADP, April 2002 Principles of the computation process Average return ticket price Time No of flights per year Constant Threshold ratio Time Average normalised ticket price GDP per capita Time Normalised income threshold Time No of passengers or traffic growth rate Time Yield Time Stage length Time Penetration Time Global traffic turnover or turnover growth rate Time GDP Time Population Time Number of travelers Time Cumulative distribution of income Normalised income

Kenza methodology 8 © ADP, April 2002 Starting market : no elasticity to ticket price Normalised income (x GDP per capita) 0% 10% 20% 30% 40% 50% 60% 70% 80% 100% 90% Threshold of income before fare decrease % of population Changes in fares or the economical situation, do not affect significantly the level of demand Threshold of income after fare decrease Quality of service drives competition

Kenza methodology 9 © ADP, April 2002 Maturing market : slight elasticity to ticket price Normalised income (x GDP per capita) 0% 10% 20% 30% 40% 50% 60% 70% 80% 100% 90% Threshold of income before fare decrease % of population Threshold of income after fare decrease Fares start to drive the competition Changes in fares or the economical situation slightly affect the level of demand

Kenza methodology 10 © ADP, April 2002 Mature market : highly sensitive to ticket price Normalised income (x GDP per capita) 0% 10% 20% 30% 40% 50% 60% 70% 80% 100% 90% Threshold of income before fare decrease % of population Slight changes in fares or the economical situation, may dramatically affect the level of demand Fares & economical situation drive the market and the competition Threshold of income after fare decrease

Kenza methodology 11 © ADP, April 2002 Leisure oriented market The package price includes transportation and accommodation. It determines the lower threshold of income below which the number of people travelling by air is virtually insignificant ; The package price determines the upper threshold of income upon which people travelling by air, prefer more "exotic" and expensive destination ; The thresholds of income and the cumulative distribution of incomes within the population, determines the number of passengers ; It is implicitly assumed that for a given package price, tourist destinations have kept and will keep their market share constant.

Kenza methodology 12 © ADP, April 2002 Leisure oriented market (continued) Normalised income (x GDP per capita) 0% 10% 20% 30% 40% 50% 60% 70% 80% 100% 90% Cumulative distribution of income Part of the population which can travel after fare decrease Thresholds of income before fare decrease % of population Part of the population which can travel before fare decrease Thresholds of income after fare decrease

Kenza methodology 13 © ADP, April 2002 Leisure oriented market : maturity = saturation Normalised income (x GDP per capita) 01 40% 50% 60% 70% 80% 100% 90% % of population Lower fares, same market level, lower profitability. Fare competition destroys the market

Kenza methodology 14 © ADP, April 2002 Market typology

Kenza methodology 15 © ADP, April 2002 How different countries compare 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % of population Normalised Income (x GDP per capita) BRAZIL GDP/capita computed on the reduced population FRANCE INDIA GDP/capita computed on the reduced population UK USA

Kenza methodology 16 © ADP, April 2002 Same threshold of income, different market size 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % of population Normalised Income (x GDP per capita) FRANCE UK Same normalised threshold of income Potential British Market : 19 % of population Potential French Market : 11 % of population

Kenza methodology 17 © ADP, April 2002 Market diagnostic

Kenza methodology 18 © ADP, April 2002 Which fare policy? Normalised income (x GDP per capita) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Threshold of income in 1994 Decreasing fares cannot stimulate traffic Mexican domestic market Threshold of income in 1994 Slight increase of fares depresses traffic, but can be more profitable % 90% 100% % of population

Kenza methodology 19 © ADP, April 2002 Who is traveling and how often? Mexican domestic market Maximum penetration (% of total population) 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% Only the very rich can travel... M of travelers M of passengers and they travel very often

Kenza methodology 20 © ADP, April 2002 Can a fare decrease stimulates the market? M of passengers Yield = US¢ 12 per Km Yield = US¢ 9 per Km Brazilian domestic market

Kenza methodology 21 © ADP, April 2002 What about the market turnover? Crore Similar turnover growth in the next future irrespective of the fare or GDP growth Indian domestic market

Kenza methodology 22 © ADP, April 2002 Sector growth limitation : a matter of demand elasticity Average income produced by a passenger (return flight) (Constant Euro 2000) Demand elasticity to the fare Demand elasticity to the GDP Area of economical saturation Area of economical stimulation Area of geared effect of the GDP growth Area of no geared effect of the GDP growth €200 to €230 Structural change in the economical dynamic of demand French domestic market

Kenza methodology 23 © ADP, April 2002 Conclusions

Kenza methodology 24 © ADP, April 2002 Beyond the math, physics! The Kenza methodology is mostly dedicated at the analysis and forecasting of a market of which the outputs can be scaled down at the level of a route or an airline's network later on. The Kenza methodology provides pieces of information about the physical behaviour of the market : number of travellers; part of the population which is likely to travel; variable elasticity of the demand over the time; weight of the underground economy; turnover and profit margin evolution of the sector; … The Kenza methodology is only one of the approaches ADP is using and developing in order to gain a better expertise of the air transport sector.

Kenza methodology 25 © ADP, April 2002 Why Kenza?

Kenza methodology 26 © ADP, April 2002 Daniel SALLIER Statistics, Forecasting & Simulations Director ADP – DCSPR Strategy Department Orly Sud ORLY AEROGARE CEDEX FRANCE tel. : Int'l fax. : Int'l © ADP, April 2002 Printed in France