Traffic forecasts Fare Policy Yield Management

Transcription

1 Traffic forecasts Fare Policy Yield Management Michel LEBOEUF SNCF, Director for Major Projects Paris, France 1/100

2 Traffic forecasts Fare policy Yield management 2/100

3 You want to implement a High Speed Rail link between A and B. What will the traffic volume be? What revenues can be expected from the passengers? 3/100

4 The profitability and the public welfare utility of a project are strongly linked to its ability to attract new passengers The traffic forecasts are essential in assessing a project profitability and its public welfare utility. One of the two major risks of a HSR project is the commercial risk Therefore, the traffic forecasts are a key issue when dealing with the project financing and risk allocation 4/100

5 Predicting traffic volumes and revenues involves modelling techniques mainly based on statistical approaches. There are numerous modelling techniques. We have learnt that: -very sophisticated models require a lot of accurate data -data gathering is a long and very costly process -complexity in a model is often a weakness -traffic prediction should be comprehensible for non-specialists 5/100

6 Traffic forecasts by OD pairs Origin City A Destination City B G A C D E 19 One way OD pairs F B AD AE AF AB AG CD CE CFCB CG DE DF DB DG EF EB EG FB FG 6/100

7 Baseline Situation Annual traffic volumes from A to B Reference situation for road Project situation for road Project situation for rail road air rail Reference situation for air Project situation for air Reference situation for rail /100

8 First choice Travel No travel Public transportation Private car Bus Plane Train Rationality 8/100

9 Time Value of time Money 9/100

10 Traffic Forecasts and Marketing for High Speed Train Services 10$ 20$ 50$ 10/100

11 % Log-normal distribution 100% people Value of time ($/hour) 11/100

12 Air/rail competition 100$ 1hour Origin City Destination City 60$ 3 hours 12/100

13 Air/rail competition Generalized Cost (Air)= Price (Air)+ v*travel Time (Air) GC Air = 100$+ v*1hour Origin City Destination City Generalized Cost (Rail)= Price (Rail)+ v*travel Time (Rail) GC Rail = 60$+ v*3 hours 13/100

14 Generalized Cost (Air) Price (Air)+ v*travel Time (Air) Air/rail competition GC Air = 100$+ v*1hour = Generalized Cost (Rail) Price (Rail)+ h*travel Time (Rail) GC Rail = 60$+ v*3 hours People who value time as 20$/hour don t care about the transport mode because: 100$ + 1*20$ = 60$ + 3*20$ People who value time as less than 20$/hour prefer the train because: 100$ + 1*10$ > 60$ + 3*10$ 14/100

15 Rail passengers 55% % Air passengers 45% Value of time ($/hour) 15/100

16 Baseline Situation Annual traffic volumes from A to B Reference situation for road Project situation for road Project situation for rail road air rail Reference situation for air Project situation for air Reference situation for rail /100

17 Rail passengers 55% % Air passengers 45% Value of time ($/hour) 30% 70% Value of time ($/hour) 17/100

18 Air/rail competition 100$ 1hour Origin City Destination City 70$ 60$ 3 hours 2 hours 18/100

19 Generalized Cost (Air) Price (Air)+ v*travel Time (Air) Air/rail competition GC Air = 100$+ v*1hour = Generalized Cost (Rail) Price (Rail)+ h*travel Time (Rail) GC Rail = 70$+ v*2 hours People who value time as 30$/hour don t care about the transport mode because: 100$ + 1*30$ = 70$ + 2*30$ 19/100

20 % Modal shift from air to rail Rail passengers 30% Air passengers 70% + 25% = 55% Value of time ($/hour) - 25% = 45% 20/100

21 % Rail / Rail+Air ,0 2,0 4,0 6,0 8,0 10,0 Hours 21/100

22 120,00% Market shares on the Rail+Air market on the Madrid-Sevilla OD pair 100,00% 80,00% 60,00% 40,00% 20,00% 0,00% Air 76,30 79,30 48,40 18,40 20,00 18,80 18,40 18,50 18,80 17,10 16,60 15,80 15,90 Rail 23,70 20,70 51,60 81,60 80,00 81,20 81,60 81,50 81,20 82,90 83,40 84,20 84,10 22/100

23 % Rail / Rail+Air ,0 2,0 4,0 6,0 8,0 10,0 Hours 3h 5h30 23/100

24 HS1.2 HS ,338 EUROSTAR annual traffic In million passengers /100

25 Daily rhythm Number of Eurostar tickets week by week NUMBER OF EUROSTAR TRIPS SOLD Without the HS1 1 With the HS1 1 Commissioning of the CTRL1 25/100

26 Evolution (%) Evolution of air traffic volume between Paris and Marseilles Mediterranean TGV Commissioning AIR LIBERTE Id TGV month M -Y/month M (Y-1) 20,00% 10,00% 0,00% -10,00% -20,00% -30,00% -40,00% ma rs-01 avr- 01 mai- 01 juin- 01 juil- 01 août- sept oct- 01 nov- 01 déc- 01 janv- 02 févr- 02 ma rs-02 avr- 02 mai- 02 juin- 02 juil- 02 août- sept oct- 02 nov- 02 déc /100

27 Gravity model & mobility d S S S = k Mm d 2 u M:Mass m:mass d:distance S: strength k: constant 27/100

28 Gravity model & mobility Generalized travel cost (Gc) City A Traffic Traffic City B T = k POP * pop Gc 2 28/100

29 Gravity model & mobility Gc = f (travel time, access and egress times, average price, number of connections, service frequency) 29/100

30 Gravity model & mobility Generalized travel cost (Gc ij ) City A T AB City B T A B = K * PopEm A * Pop Att B Gc γ A B T K Em Att Gc Traffic on the (ij) OD pair Constant factor Characteristic of the Emission zone Characteristic of the Attraction zone Generalized cost of transport between zones i & j 30/100

31 Gravity model & mobility Generalized travel cost (Gc ij ) City A T A B +ΔT A B City B T A B = ΔT AB -γ K * PopEm A * Pop Att B ΔGc A = Gc γ A B Gc A B T AB B 31/100

32 Gravity model & mobility City A T A B ΔT AB -γ T AB +ΔT A B = Gc A City B ΔGc A B B Where does the traffic increase come from? 32/100

33 Partly from road and from a mobility increase 33/100

34 The best strategy against competition by road is to increase the service frequency. High speed trains are apt to be operated like shuttles. 34/100

35 The time table is based on departures every 4 to 12 minutes between Tokyo and Omiya and Takasaki from 6AM to 11 PM. "ASAHI" (Tokyo - Niigata) Takasaki Omiya 35/100

36 28 trains a day between Paris and Brussels a departure every 30 minutes from 6h25 to 22h31 with a 1h25 trip duration 36/100

37 37/100 Conclusion on traffic forecasts

38 Forecast Traffic volume multiplier comparision between forecasts and actual figures 38/100

39 Modal split on the Madrid-Sevilla market before the commissioning of the AVE car Conventional train 15% air 11% bus 14% 60% Modal split on the Madrid-Sevilla market after the commissioning of the AVE The car has lost more than 40% of its market share 52% 8% 2% 4% 34% car Conventional train air bus AVE Air has lost more than 60% of its market share 39/100

40 On OD pairs to and from Paris TGV plays a major role Nationwide, the car is still the dominant mode Market shares in France 9% 54% 37% TGV Car Air 62% 1% 37% 40/100

41 Traffic forecasts Fare policy Yield management 41/100

42 42/100 The SNCF fare policy for long distance passenger services has been strongly linked to the history of the company

43 43/100 3 fare policies have been successively experienced, based on

44 1 A fare policy based on the production cost 1937: Creation of SNCF by socializing the former private companies 44/100

45 P f2 = P 0 + d*p P f2 = full fare 2 nd class P 0 = constant d = distance (km) p = unit price per km 45/100

46 P f1 = 1.5* P f2 P f1 = full fare 1 st class P f2 = full fare 2 nd class 46/100

47 Customer ticket price: P c = P f1 or f2 *(1-discounting rate/100) 47/100

48 2 types of discounts: - Social discounts - Commercial discounts 48/100

49 2 main issues: 1 Which part of the production cost is fixed and which part is variable? 2 What is the most relevant parameter for the variable charges? 49/100

50 Main features of the price formula: - Equality between all routes and regions - Decreasing in relation to distance, - The price level is based on the long term economic viability of the rail sector, 50/100

51 2 The transition to a fare policy based on the market 51/100

52 2 The transition to a fare policy based on the market 1981/1983: Commissioning of the new high speed line from Paris to Lyon 52/100

53 Bayonne Hendaye Lignes à grande vitesse Dax Lignes à grande vitesse en construction Lignes classiques empruntées par les TGV Oloron London Le Havre Pau Tarbes Toulouse Buzy Lourdes Calais Frethun Boulogne Agen Rouen Calais-V. Dunkerque Montauban Carcassonne Oostende Lens Arras Perpignan Den Haag Lille Valenciennes TGV Haute-Picardie Champagne-Ardenne Amsterdam Rotterdam Antwerpen Bruxelles Meuse Lannion Paris Lorraine Strasbourg Brest Massy TGV Marne-la-Vallée - Chessy Nancy St Brieuc Melun Quimper Rennes Colmar Sélestat Lorient Sens Le Mans Vannes Belfort Mulhouse Vendôme TGV Montbard La Baule Angers Tours Besançon Montbéliard Zürich St-Pierre-des-Corps Le Croisic Dijon Nantes Dole Mouchard Bern Chalon Le Creusot TGV sur-s. Futuroscope Lons-le Argenton/Creuse Lausanne -Saunier Poitiers Brig Niort Bourg Mâcon TGV en-b. Genève La Rochelle St-Gervais-les-Bains Lyon Saint Exupéry Lyon TGV Bourg-St-Maurice Angoulême St-Étienne Milano Modane Grenoble Bordeaux Libourne Valence Ville Valence TGV Torino 500 Arcachon Montélimar Namur Nîmes Avignon Centre Nice Montpellier Arles Avignon TGV Aix-en-Provence Béziers TGV Narbonne Marseille Liège Orange Metz Toulon Köln Ventimiglia PROFIL DE LA LIGNE ANCIENNE PARIS-DIJON-LYON altitude ( en m ) Paris distance ( en km ) PROFIL DE LA LIGNE NOUVELLE PARIS-SUD-EST altitude ( en m ) Paris Combs-la-Ville distance ( en km ) SAÔNE 425 Lyon-Part-Dieu 512 Lyon-Perrache 53/100 53

54 A Route 20% shorter: The issue raised by the new high speed offer: A much better service for a lower price? 54/100

55 Of doors and windows in the fare policy 55/100 55

56 Benefits brought by the seat booking obligation for the customer: - Better sizing of the production means, - Service guarantee for the client, - Better knowledge of the market, - Possibility to adjust the fare according to the departure hour. 56/100

57 On the Paris-Lyon route, the TGV ticket is proposed at the same price as the ticket with conventional trains 57/100

58 SNCF specifications document (art 14): 1 ) The price paid by the customer is determined by SNCF according to a general basic fare to be applied for a 2nd class passenger; 2 )The basic fare will have to be agreed by the State : A new SNCF and a new transport regulation 58/100

59 1993: Commissioning of the Northern TGV 59/100

60 Two improvements of the fare policy: - Trains with extra charges - Blue-white-red fare policy 60/100

61 The state government agrees to abandon the distance based fare policy and SNCF moves towards market prices 1994: Change in the SNCF guidelines 61/100

62 62/100 3 The client risk sharing and loyalty

63 : SNCF revamps its booking system and starts revenue management 63/100

64 The Value For money Revenue management techniques are based on market segmentation and the assumption that all customers do not appraise the value of a product or a service at the same level 64/100

65 65/100 The value for money price level makes the synthesis of the various components and strengths acting on the market in real time

66 A new range of fares based on -the client loyalty -the service provided to the client -the client flexibility 66/100

67 Generalization of market prices Frequent travellers Season Tickets (>-50%) 12/25 discount Card (-50%) 3 Casual travellers 2 «Discovery» (-25%) Road/air/non mobile 1 67/100

68 No anticipation +discount function of The client loyalty Booking at D-120 No possibility Up to D-1 Up to H-1 From H+1 Up to D+60 Exchange lattitude 68/100

69 Vernon Chars London Oostende Antwerpen Calais-V. Dunkerque Bruxelles Calais Frethun Lille Boulogne Liège Lens Arras Namur Valenciennes Charleville-Mézières TGV Sarrebrücken Reims Haute-Picardie Le Havre Rouen Granville Champagne-Ardenne Metz Meuse Lannion Paris Strasbourg Toul Lorraine Strasbourg Brest Massy TGV Marne-la-Vallée Troyes - ChessyNancy St Brieuc Melun Rennes Orléans Mulhouse Sélestat Quimper Colmar Lorient ( Les Sens Aubrais) Culmont- Le Mans Chalindrey Vannes Belfort Mulhouse Vendôme TGV Montbard La Baule Angers Tours Montbéliard Bourges Besançon Zürich St-Pierre-des-Corps Nevers Le Croisic Dijon Nantes Dole Mouchard Bern Chalon Les Sables Le Creusot TGV Argenton/Creuse -d'olonne Futuroscope sur-s. Lons-le Lausanne Poitiers -SaunierÉvian Brig Niort -en-b. Bourg Mâcon TGV La Rochelle en-b. Genève St-Gervais St-Gervais-les-Bains Lyon Bourg-St-Maurice Lyon Saint Exupéry TGV Bourg-St-Maurice Angoulême St-Étienne Milano Modane Bordeaux Grenoble Valence TGV Libourne Valence Ville Torino Arcachon Montélimar Agen Montauban Orange Dax Nîmes Avignon Centre Nice Ventimiglia Toulouse Montpellier Avignon TGV Bayonne Arles Aix-en-Provence Hendaye Pau Tarbes Béziers TGV Oloron Buzy Lourdes Carcassonne Marseille Narbonne Toulon Lignes à grande vitesse Lignes à grande vitesse en construction Lignes classiques empruntées par les TGV Perpignan Amsterdam Den Haag Rotterdam Köln 69/100

70 Traffic Forecasts for High Speed Train Services Traffic Forecasts for High Speed Train Services Best Travel Times Brest 4h01 3h31 3h00 Reims 1h25 0h45 PARIS Metz/Nancy 2h45/2h40 1h30 Strasbourg 3h50 2h20 2h00 Quimper 4h13 3h43 3h00 Nantes 2h01 1h53 Bordeaux 2h57 2h25 2h09 1h00 2h00 3h00 Chambéry 2h40 2h10 4h00 5h00 6h00 Mulhouse 4h31 3h10* 2h30 Évian 4h35 4h05 Toulouse 5h07 4h42 4h10/ 3h00 Montpellier 3h15 3h00 Marseille 3h00 Nice 5h30 4h35 /3h25 70/100

71 Traffic Forecasts for High Speed Train Services Traffic Forecasts for High Speed Train Services Best Travel Times Londres 3h00 2h10 Amsterdam 4h10 3h10 Bruxelles 1h25 Cologne 3h56 3h36 3h00 Luxembourg 3h35 2h15 Francfort 5h35 3h45 3h25 Stuttgart 5h55 3h50 3h30 Munich 8h20 6h00 5h40 PARIS 1h00 2h00 3h00 4h00 5h00 6h00 Bâle 4h50 3h30 2h49 Genève 3h34 3h00 Turin 5h23 4h53 3h15 Milan 6h50 5h28 4h02 71/100 Madrid 13h00 8h15 8h00 7h25 Barcelone 8h25 5h50 5h35 5h00 sources : DGDC & TGV Est

72 180,0 160,0 150,0 140,0 120,0 High speed traffic in France (million passengers) 109,2 157,0 159,0 154,5 151,6 148,0 145,0 142,0 137,7 132,0 128,8 124,6 118,9 160,9 Forecasted traffic growth with network extension 100,0 80,0 60,0 40,0 31,8 46,7 49,3 39,3 41,7 42,6 57,6 65,7 95,4 98,8 100,8 92,191,0 87,5 83,4 77,7 72,0 20,0 0,0 1,5 21,9 14,6 16,716,6 18,019,5 7,3 9,9 72/100

73 Traffic forecasts Fare policy Yield management 73/100

74 Yield management is the way you manage train capacity and sales in real time 74/100

75 Internet has completely changed customer behaviour: real time information drives the market toward perfection 75/100

76 However train tickets are not to be auctioned off 76/100

77 Railway yield management is extremely complex: much more comlex than in the air industry. 77/100

78 There are roughly two situations whether the operator has or does not have any constraints: public (even part) ownership of infrastructure will always lay constraints on any private operator 78/100

79 The low cost air companies case somehow illustrates the no-constraint model 79/100

80 Departure day Basic principle for a constraint-free model Number of reservations for a given train Double unit train capacity? (3) Single unit train capacity?? (2) (1) D-120 First reading day D Time (days) 80/100

81 Train occupancy G A D E F B 100% C 50% AD AE AF AB AG CD CE CFCB CG DE DF DB DG EF EB EG FB FG 0% :00 Train number Departure time 81/100

82 Departure day Basic principle for a constraint-free model Price per seat ($) Forecasting model Double unit train capacity Single unit train capacity Real time assessment? (2) of the appropriate fare level to maximize? (3) revenues? (1) and/or occupancy Competition? D-120 First rreading day D Time (days) 82/100

83 Ramp up profiles Departure day Basic principle for a constraint-free model Number of reservations for a given train Double unit train capacity Single unit train capacity D-120 D Time (days) 83/100

84 Departure day Basic principle for a constraint-free model Number of reservations for a given train Double unit train capacity? (3) Single unit train capacity?? (2) (1) D-120 First reading day Second reading day D Time (days) 84/100

85 Departure day Basic principle for a constraint-free model Price per seat ($) Double unit train capacity Single unit train capacity? D-120 First rreading day Second reading day D Time (days) 85/100

86 Train occupancy 100% 50% 0% :00 Train number Departure time 6:30 9:00 86/100

87 Basic principle for a constrained model Constraints may be laid on: - Maximum fare - Average fare - 1st and 2nd class - Social discounts - Others (children groups, for example) 87/100

88 Service Train occupancy Basic principle for a constrained model 100% 1st class 50% 2nd class 0% :00 Train number Departure time 6:30 9:00 88/100

89 No anticipation +discount function of the client loyalty Booking at D-120 No possibility Up to D-1 Up to H-1 From H+1 Up to D+60 Exchange latitude 89/100

90 Loyalty Train occupancy Basic principle for a constrained model Frequent Travellers 100% 1st class Casual Travellers Frequent Travellers 50% 2nd class Casual Travellers 0% :00 Train number Departure time 6:30 9:00 90/100

91 Risk Train occupancy Basic principle for a constrained model Frequent Travellers 100% 1st class Casual Travellers Frequent Travellers Refundable 50% Non refundable 2nd class Casual Travellers 0% :00 Train number Departure time 6:30 9:00 91/100

92 Departure day Basic principle for a constrained model Price per seat ($) Forecasting model Double unit train capacity Single unit train capacity Real time allocation of seats between classes of service? (2) and loyalty/risk quotas so as to maximize? (3) the revenues or the occupancy? (1) Competition? D-120 First rreading day D Time (days) 92/100

93 Basic principle for both models: Optimization of the pricing so that yield system will maximize the revenues or the traffic volume 93/100

94 Services proposés SNCF DB RENFE Services available on board the high speed trains Premium 1 ère classe Club Preferente ETR 500 ETR 460/480 ETR 450 Catering at the seat X* X X X Glass of welcome X X* X* X* X* X* Snack meal X* X* X* Newspapers X X X X X* X* X* Bar / Cafeteria / restaurant X X X X X X Mobile grocery X Video X X X Audio (4 musical channels) X X X X X Games for children Cloakroom X X 2 On board telephone X X X Parking (i) X X Taxi booking X X Access to club lobby X 1 X* X* X* X X X Baby wraping facilities Commodities for disabled people X X Compartments dedicated to parents with children X Electric plugs X X X X Mobile stations X Dedicated Business compartments X X * Included in the 1st class ticket price 1 Free for SNCF "grand voayageurs" 2 in ICE 3 FS 94/100

95 Prem s Easyjet TGV Comparison of the width of the scale of fares of Easyjet and TGV on the Paris-Geneva route 95/100

96 Price ranges for 2-hour high speed trip duration Rail Market share above 90% Rail Market share above 85% 96/100

97 Price ranges ère Classe PT + 1ère Classe PT Prem's 60 2de classe TR maxi Paris Lyon Würzburg Hanovre Stuttgart Köln Madrid Séville Madrid Barcelona 97/100

98 98/100 Conclusion

99 Traffic forecasts Pricing Yield management 99/100

100 100/100 Thank you for your attention!