Current revenue management at Vietnam Airlines

husiastic guidance and encouragement that inspired the author a lot during the process of writing the thesis. I would like to acknowledge my colleges and experts; managers of departments of Vietnam Airlines for providing the material needed for the thesis. I owe a great deal to my family, relatives and friends, especially to my parents, my wife and my children for their valuable encouragement and unceasing supports in my academic pursuits ABBREVIATION CRM Customer relationship management CX Cathay pacific airways HAN Ha Noi JL Japan airlines O-D Origin – Destination PAX Passenger PNH Pnompenh REP Siem Reap city RM Revenue Management SGN Ho Chi Minh city SQ Singapore airlines VNA Vietnam airlines LIST OF TABLES Table 2.1. Typical airline fare class structure 22 Table 2.2. Nesting on a flight leg 24 Table 2.3 Distance to airlines hub in region. 27 Table 2.4 tourist arrivals in ASEAN 2007 28 Table 3.1 passenger revenue and volume 2006-2008 31 Table 3.2: Vietnam Airlines market share 2005- 2008 period 31 Table 3.3 Revenue management organization of Vietnam airlines 34 Table 3.4 fare structure for route Hanoi/ Hochiminh city to Paris 37 Table 3.5 Overbooking ratio applying for Vietnam airlines ( in general) 38 Table 3.6 Revenue from Overbooking: 39 Table 3.7 Load factor Vietnam airlines (in general) 39 Table 3.8: Quantities of denied boarding passengers 41 Table 3.9 : Compensation of denied boarding passenger due to oversold causes: 44 Table 4.1 Target business VNA (2009, 2020) and other airline 46 Table 4.2 Fleet of Vietnam airlines to 2020 47  LIST OF FIGURES Figure 1.1 Research Procedure 11 Figure 2.1 Airlines Passenger Origin Destination simulation flow (POD model) 20 Sources: Hoppers tad, the Boeing Company. 20 Figure 2.2: Revenue Management process flow 26 Figure 3.1: Passenger revenue period 1995-2004………………….. ……...30 Fingure: 3.2 Airlines Passenger Origin Destination simulation flow (POD model) 40 TERMINOLOGIES In the thesis, there have been some Airlines terminologies. In order to agree upon the meaning of these technical words and avoid misunderstanding, the following words are understood as follow: Airlines Alliances: is an agreement between two or more airlines to cooperate on a substantial level. (The three largest passenger alliances are the Star Alliance, SkyTeam and Oneworld). Cancellation: guests make reservations for flight but then cancel the reservation. Denied Boarding passenger: Passenger have confirmed ticket and reservation but airlines can not arrange seats on flight due to overbooking and all seats of flight occupied at departure times of flight. Forecast: the process of predicting events and trends in business Load factor: is a measure of the amount of utilization of the total available capacity of a commercial transport vehicle. It is useful for calculating the average occupancy on various routes of airlines. Low-cost airlines :( also known as a no-frills, discount or budget carrier or airline) is an airline that offers generally low fares in exchange for eliminating many traditional passenger services No show: a guest who made a reservation but not show up at check-in counter for departure. Overbooking: accepting more reservation than the seat of flight available. Over-selling: Selling more seats on flight than those available. Spoilage: results from the inability to sell seats for a certain period of time and thus causes the permanent loss of revenue for that period. EXECUTIVE SUMMARY Airlines have faced with the empty seats after flights departure due to the no-shows and cancellations of passengers at last minute, the empty seats of flight will cause the loosing revenue of airlines. With a fixed cost that airlines have to spend for every flight (fuel, aircraft…), filling up the seats and the load factor, fare mixes and selling up are necessary requirements for the airlines to maximize the revenue and lead to gain optimal profit. And to solve these problems, airlines apply the Revenue management system. Airlines management (or yield management) is defined as to maximize passenger revenue by selling the right seats to the right customers at the right time. In this thesis, base on the theory of revenue management and knowledge of operation management subject studied, I analyzed Revenue Management activities at Vietnam Airline. Vietnam airlines have deployed the revenue management system for years in its operation, such as forecast demand, seats inventory control, fare mix and overbooking application, these also brings a given success for Vietnam airlines. However, there some problems such as still exist the empty seat on plane after plane takeoff although the booking system had sold over capacity of airplane or existing the cases that forced to deny boarding passengers due to can not arrange seats for them because of deploying overbooking policies, this happened has affected to the revenue and bad image of Vietnam airlines. After analyzing the situations at Vietnam airline in terms of history, staffing, facilities and specially the RM activities from fare structure, overbooking policies and seats inventory control, annual reports gained from 2005 to 2008, and the interviews with the experts and manager working at revenue management, the research has identified some problems and shortcomings that Vietnam Airline is facing as follow: 1) Unreasonable overbooking in low frequency routes , 2) Revenue management Control system, 3) Flight Report system, 4) Unstable schedule leads to difficult for forecasting demand and collecting data, 5)Lack of capacity in peak season, 6) Compensation policy for denied boarding passenger, 7) Human resources. These problems and shortcoming have influenced the effective operation of Vietnam airline especially in maximizing revenue and profits. To help solves these problems and shortcomings some recommendations were put forward. They are: 1)Applying appropriate overbooking ratio, 2) Increasing compensation for denied boarding passenger,3) Maintain the stable flight schedule, 4)Good capacity and demand forecast, 5)Training human resources, Improving sufficient and efficient information database system, 6)More flexible fare-mix policies. CHAPTER 1. INTRODUCTION 1.1 Rationale of research For airlines industries, revenue management plays a very important role for existence and development. With a fixed cost that airlines have to spend for every flight (fuel, aircraft…), filling up the seats and the load factor, fare mixes and selling up are necessary requirements for the airlines to maximize the revenue and lead to gain optimal profit. Vietnam airlines have deployed the revenue management system for its operation such as controlling space and applying fare mixes in sale system especially in applying the overbooking policies on reservation system, and its also brings a given success for Vietnam airlines. However, there some problems such as still exist the empty seat on plane after plane takeoff although the booking system had sold over capacity of airplane or existing the cases that forced to deny boarding passengers due to can not arrange seats for them because of deploying overbooking policies, this happened has affected to the revenue and bad image of Vietnam airlines. So, there need to have an analysis revenue management to evaluate how well it has been applied and has worked, to identify if there are ways for improvement or necessary adjustment. 1.2 Research problem The research is designed to analyze the revenue management system at Vietnam airlines especially in operation as overbooking, Fare structure, and Demand forecast, control revenue management system fields to identify possible improvement or adjustment for that system operating more efficiency. Research objectives With the identified problem, the following objectives are set for the research: Provide an overview of Vietnam airlines business activities related to Revenue management system. Analyze the revenue management at Vietnam airlines in operational field. Find out the problems of the existing Revenue management at Vietnam airlines Propose some recommendations for improvement to revenue management of Vietnam airlines. Research scope and limitation The research focuses on the working or revenue management in the period from 2005 to 2008 Time and budget is limited, and the data collection in Vietnam airlines HDQ from 2005 to 2008. Research methodology Figure 1.1 Research Procedures Secondary Data report, statistic, publication, previous study by VNA Primary Data Qualitative: 4 deep interviews, obrervation Analysis & Findings Recommendations for improvement Source: Author’s Summary Research method In this thesis, for the nature of the study about the operation of a system, qualitative research method was used intensively. The data were collected from secondary and primary sources. Qualitative method applied to find out perception, process and evaluation about Revenue management at Vietnam airlines. The following sections presents in details the way of collecting and analyzing the data sources used in this study. Data collected - Primary data: To assist in the identification of causes mentioned earlier, 4 in depth interviews with experts and managers in airline industry and RM system technicians are to be done, the first interview with Ms Nguyen Minh Hien – Helpdesk Manager of Space control center- Vietnam airlines, the second interview Mr Nguyen gia Loc – Director of Space control – Vietnam airlines, the third interview Mr Hoang Thanh Quy – deputy Director of Marketing and sales Department – Vietnam airlines, the forth interview Mr Dang Anh Tuan – Director of Noibai Operation center – Vietnam airlines. The purpose of the interviews is to get the experts’ ideas and opinions about the revenue management system of Vietnam airlines, what they have deployed for the revenue management system and how they run the system and how it has operated. The interviews shall not go into technical aspect but to the managerial aspect of using the system for decision making. The interviews also aim at getting ideas from experts on strategies and consideration in order to apply RM effectively. With my ten years experiences working in Vietnam airlines at operational field, I have analyzed about the revenue management system and discovered some the limits and disadvantages of Vietnam airlines revenue management system need to improve. - Secondary data: The second data composes a wide range of information published in relevant material. The main source is from internal records of Vietnam airlines. Especially it includes: Sales report, revenue management report and statistics collected by VNA Space control center, RM department in five year (2005-2008). 1.6 Research Structure Besides the parts of introductions, conclusion, reference and appendix, the content of this thesis includes 3 main chapters starting from chapter 2 Chapter 2: Theoretical Background In this chapter provide the concept of revenue management, definition of revenue management, the process of revenue management in airlines industry’s application. These the basic for analyzing the revenue management activities in Vietnam airlines at chapter 3 Chapter 3: Current Revenue management at Vietnam airlines In this chapter, provide the overview of Vietnam airlines business, revenue management activities that Vietnam airlines have implemented, such seats inventory control, fare structure, reservation system, overbooking application, the organization of revenue management of Vietnam airlines. Provide identifications problem in Vietnam airlines revenue management activities Chapter 4: Recommendation to improve revenue management at Vietnam airlines In this chapter, provide the overview of strategic of Vietnam airlines to 2020 and draw the recommendation to improve revenue management activities.. CHAPTER 2.THEORETICAL BACKGROUND 2.1 Concept of Revenue Management 2.1.1 Definition of Revenue Management There are several definitions of revenue management (also refer to as yield management) in the literature. American Airlines (1987) defined the goal of yield management as to “maximize passenger revenue by selling the right seats to the right customers at the right time.”[1, p22-p25] Pfeifer (in1989) described airline yield management as “process by which discount fares are allocated to scheduled flights for the purposes of balancing demand and increasing revenues.”[7, p149-p157] From the hotel industry’s perspective it have been defined as “charging a different rate for the same service to a different individual” [5] and “controlling the trade off between average rate and occupancy” [6]. Weatherford and Bodily (1992) have concluded from the above definitions that the term yield management is too limited in describing the broad class of revenue management approaches.[11] After analyzing situations in which yield management was used. They concluded that these situations had the following characteristics in common: There is one date on which the product or service becomes available and another after which it is either not available or it spoils. The product cannot be stored for significant periods of time-it eventually perishes. In the grocery store example, the fruit would spoil. There is a fixed number of units. Capacity cannot be charged in the short term. In the hotel example, there are so many rooms that may be sold at a given property location. There is the possibility of segmenting price-sensitive customers. In the airlines example, vacation travelers are much more sensitive to price than business travelers. Weatherford and bodily proposed the term perishable-asset revenue management to define this class of problems and described it as “the optimal revenue management of perishable assets through price segmentation” 2.1.2 Origin of Revenue Management The root of modern revenue management can be traced back to the early days of the U.S. airlines industry. Prior to the Airlines Deregulation Act of 1979, fares for airlines travel in the United States were regulated by the Civil Aeronautics Board (CAB). The CAB ensured that the airlines operated in a highly controlled environment designed to serve the public convenience and necessity.[2] The CAB required economic justification for any fares proposed by the airlines. Thus, there were few fares for customers to choose from. In the 1930’s all airlines offered all seats on a flight for the same price. But it was obvious to the airlines that passengers could be divided into two broad categories, based on their travel behavior and their sensitivity to prices. There were business travelers and leisure travelers. Business passengers tended to make their travel arrangement close to their departure date and stay at their destination for only a short time. There was little flexibility in their plans and were willing to pay higher prices for tickets. Leisure travelers, on the other hand, booked their flights well in advance of their travel date. They stayed longer at their destinations and had much more flexibility in their travel plans. They would often decide not to travel rather than pay high fares. Since there was only on fare offered to both types of passengers, many of leisure passengers chose not to fly, and many flights departed with empty seats. Airlines managers saw an opportunity to increase revenue by lowering fares in certain markets. The first experiment to offer low-fare service occurred in California on the San Francisco – Los Angles route in 1994[2]. United airlines began its Sky Coach Service using 10-passengers Boeing 247s and charging a one-way fare of $13.90. The CAB approved the low fares based on the lower operating cost of the B-247s and fewer amenities offered on board. The experiment was a success but ended shortly thereafter when the airline’s fleet was turn over to the armed forces during World War II. Throughout the next few decades, other discount fares were offered with varying degrees of success. First – class and coach – class became standard on all airlines. But the airlines were not permitted to offered different fares within the coach cabin and prices were set through a cost-plus pricing formula administered by the CAB. Carriers gradually became less efficient at operating their airlines, and coach fares rose over time as average costs increased. During the 1960s, the CAB began approving new types of fares such as night coach fares and 7-21 day excursion fares based on length of stay. However, the airlines placed no limits on the number of seats that could be sold at these fares, and all were available on a first-come, first served basis. In the early 1970s, the CAB responded to demand for more discount fares by easing regulations for charter airlines. With their lower operating costs, the charter carriers were able to offer low fares and still earn a profit. For example, in the winter of 1976, passengers could travel from New-York to Florida on a charter for as little as $99.[2] This fare was less than the average cost for major airlines to fly that market. So if the airlines matched the charter fare, then it would lose money on the flight, even if it filled every seat. This situation caused concern among the managers at the major airlines. Their initial though was to figure out a way to reduce costs so they could remain competitive. But that was impractical. The costs of operating a major airline with its staffing and airport needs were simply much higher than cost of running a charter operation. But then the executives at American Airlines realized something. On average, their planes were departing with half their seats empty. While the average cost of these seats were higher than the charter fares. The marginal cost was close to zero. So if they could find a way to sell just the empty seats at the charter fares, profits would increase dramatically. The challenge was to devise a plan that would make the empty seats available at the lower fare, while preventing passengers who were willing to pay the higher fare from buying low-fare seats. American airlines’ response to this challenge was the introduction of “Super Saver Fares” in 1977. With these fares came the beginning of modern day revenue management [9]. 2.2 Revenue Management in airlines industry. 2.2.1 Role of Revenue Management in airlines The airline industry is one in which production is very inflexible. Essentially, when committing to fly a flight from A to B, an airline both fixes the level of its output (the number of seats) and, for all practical purposes, the total cost of that output–independent of how many customer actually fly on the flight. It’s unit cost per seat sold, therefore, varies tremendously with the volume of sales, and once the capacity constraint is reached, no more production is possible. Worse yet, like all services, output cannot be inventoried, so production of air transport output in one period cannot be used to satisfy demand in later periods (e.g., an unsold seat on Monday cannot be used to supply the need of an excess passenger on Tuesday). All these factors combine to create extreme inflexibility in the technology of air transport service, and this is one of the key driving factors in the importance of RM in this industry to maximize revenue. 2.2.2 Contents of Revenue management in airlines 2.2.2.1 Forecast demand Forecast demand is play a important role in RM, accurate forecasts are crucial to a RM system. Poor estimates of demand lead to inadequate inventory controls and sub-optimal revenue performance. Forecast for airlines RM system is inherently difficult. Competitive action, seasonal factors, the economic environment, and contrast fare changes are a few of the hurdles that must be overcome; in addition, the fact that most of the historical demand data is censored further complicates the problem. The number of seats an airline can sell on a flight is determined by the booking limits set by the RM system. An airline continues to accept reservations in a fare class until the booking limit is reached. At the point, the airlines stops selling seats in that fare class-it also collecting valuable data. Demand for travel in that fare class may excess the booking limit, but the data does not reflect this. So the data is censored or “constrained” at the booking limit. Forecast at the level required by RM system is extremely difficult. Mc Gill and van Ryzin (1992) list the following factor as contributing to this difficulty: Seasonality: Passenger are more likely to fly to some destinations based on the time of year. For example, there is greater demand for flight to Europe in the summer than in the winter. Day-of-week and time of day variations: business traveler are more likely on weekdays than weekends, Early morning and evening flights are desired by business travelers who want to accomplish a day’ work at their destination and return the same day. Special events: Event such as the world cup cause a temporary increase in demand at specific location Sensitivity to pricing actions: Price increases and decrease result in demand decreases and increases respectively, but different passenger types have different elasticity. Demand dependencies between fare classes: Passenger who book full-fare seat might have met the restriction for lower fare seats. But there was no availability. Group booking: Groups tend to book and cancel reservations in large numbers. Cancellation: a RM system requires a forecast of how many passengers will book and travel in each fare class. Since som passengers make reservation and subsequently cancel them, this behavior must be considered. Censoring of historical demand data: An aircraft capacity and booking limits constrain the demand seen in the historical data. No-show: some passengers make reservations, decide not to travel and do not cancel their reservation. Types of forecast There are three types of forecast used in the airlines industry: Macro level, Passenger choice modeling, and micro level. Macro level forecast are usually made for aggregate forecasts of total airlines passenger demand. For example macro level forecast might be a projection of total annual domestic air travel or future travel between us and Europe. Passenger choice models attempt to predict future demand by modeling current passenger behavior based on socioeconomic factors and the characteristic of travel alternative options. Finally, micro level forecasting is used to predict passenger behavior at disaggregate level such as flight, date, and fare. So, based on historical data, forecast demand for airlines concentrate on the following types: Passengers demand Revenue for a flight Booking class of flight Overbooking ratio of flight Data for forecasting: Past flight data. Current flight performance. Market factors. Other factors affect to demand. POD model: Figure 2.1 Airlines Passenger Origin Destination simulation flow (POD model) Sources: Hoppers tad, the Boeing Company. According to POD model, the historical booking database collects information from previous flights and feeds this historical data into the forecaster, whose historical database is manually initialized at the beginning of each simulation run. The forecaster then uses this data along with booking currently on hand provided by the Revenue management optimizer to forecast future demand for a given flight. These expected future bookings are the fed into the Revenue management optimizer. With this data and actual path and class bookings and cancellations, the Revenue management optimizer then determines seat protection and availability. Finally, this data is fed into the passenger choice model, which uses it to assign new prospective passengers to available path fare combination according to their decision window and budget. All information is then input back into Revenue management optimizer as historical data to be used by the airlines for future flight departure. 2.2.2.2 Seat inventory control Seat inventory control problem in airlines revenue management concern the allocation of the finite seat inventory to the demand that occur over time. In order to decide whether or not accept a booking request, the opportunity costs of losing the seats taken up by the booking have to be evaluated and compared to the revenue generated by accepting the booking request. Solution method for seat inventory control problem are concerned with approximating these opportunity and incorporating them in a booking control policy such that expected future revenue are maximized. Comeback to “Super saver fare” which American airlines had deployed in 1977(referred at beginning of this chapter), the Super saver fare were the first capacity-controlled restricted discount fare. That is, they were offered in limited numbers and certain conditions had to be met for the fare to be valid. For example, the tickets needs to be purchased at least 21 days in advance of travel and the itinerary had to include a Saturday night stay. These restrictions were meant to prevent the high-fare passengers from purchasing the low-fare tickets. It reflected the airlines’ belief that business travelers did not have enough flexibility in their plans to meet the restrictions and, therefore, would continue to pay higher fares. American began its Super saver fares by offering approximately 30% of the seats on each flight to these fares [2, chapter 47]. But they soon found the number of seats needed to be controlled carefully to increase total revenue. If too many discount seats were sold, then the airlines would turn away late-booking high-fare business passengers. If too few seats were sold to discount passengers, then the planes would depart with empty seats. The correct number of seats to be allocated to the discount passengers could only be calculated from an accurate forecast of demand for high-fare ticket. Research thus began to develop the appropriate models to forecast demand and calculate discount seat allocations. Since the first super saver fare appeared on the market, the airlines pricing structure has changed dramatically. Airlines publish a variety of fare in an attempt to segment the market. Their goal is to design what is referred to as fare products are differentiated by advance purchase restriction, minimum stay requirement and penalties for refunds. The fare products correspond to the price elasticity airlines have identified among their customers. For example, discount passengers who desire a low price must be willing to purchase their tickets weeks in advance of travel and stay at their destination for at least one Saturday night. If they cancel or change their plans then they will be charged a penalty. On the other hand, business travelers place a high value on flexibility. They may purchase their tickets at any time and change their reservation without penalty. There are no restrictions on the amount of time they must stay at their destination. For this flexibility, the business traveler is willing to pay a higher fare than the leisure passenger [12, p92-p93]. So while these two types of passengers may be seated next to each other on a flight. They are paying different and receiving different products. Airlines using single letter class codes to distinguish between fare products. For example Y might be used for full-fare class coach, M and Q for discounts. V for deeper discounts and others classes which vary by airlines [9, p8-p31]. There are often six class or more different fare classes offered by a singe airlines in a given origin and destination (O&D) market in the coach cabin of aircraft. An example of a typical airline fare class structure is given in table 2.2 Table 2.1. Typical airline fare class structure Fare class Fare product type Y Full coach fare with no restrictions B Unrestricted discount fares M Seven-day advance purchase with minimum stay requirement Q Fourteen date advance purchase with minimum stay requirement V Deeply discount or industry fare use for airlines staffs Source: Richard H.Zeni Modern revenue management systems forecast demand for each one of these fare classes by using historical booking data from the same fare class of similar flight departures. This data is usually aggregated by departure time, day of week and time of day [4]. These forecast are them used as inputs to optimization models that calculate booking limits and control the number of seat available at various fare levels. Obviously, an airline would like to carry as many of the high-fare business passenger as possible. Only those seats that cannot be sold to business passengers should be made available to the leisure passengers. The problem is that leisure passengers tend to book their reservation first. And even if they did not the advance purchase restrictions most airlines place on leisure-fare tickets often force this behavior. So, before any seats are sold, the revenue management system must forecast how many business passengers will still want to book on a flight after the leisure passengers have made their reservations. Then it must set aside or “protect” these seats so that they will be available when the business passengers request them. The seat inventory control problem has been approached from a variety of perspective. Seat inventory can be controlled over individual flight legs (take off and landing of one flight) or over the airline’s entire network. Most airlines manage seat inventories by fare class at leg level. That is they attempt to maximize revenue on each individual flight leg. Reservation request are evaluated by airlines based on the availability of a particular fare class on each flight leg. A passenger’s entire origin and destination itin._.