Tally sheet

Booking ID	# Passengers	# Passengers Carried	Revenue
A (example)	100	Given in Phase III	Given in Phase III
SUBTOTALS
		Passengers	Gross Revenue
Oversale Adjustment (if over 100)
Spoilage Adjustment (if under 100)
NET REVENUE (Gross Revenue Adjustment)

Yield Management Game and Instructions The yield management game illustrates the trade-off between overbooking (selling more than capacity) and spoilage (having idle capacity), with the objective of maximizing revenue when faced with excess demand in the form of various revenues per passenger and different passenger volumes. This particular game focuses on airline capacity management, but is applicable to all fixed capacity services (e.g., hotels and cruise ships). When allocating seats to prospective passengers, the yield management analyst confronts a problem of maximizing total revenue for each flight. This includes capturing the ideal mix of discount and premium passengers at full capacity utilization without overselling too many customers. The objective of revenue maximization is simple (fill the airplane with the highest paying passengers), but uncertainty makes it a challenge. Specifically, historical booking trends in the airline industry indicate that the more flexible discount or leisure traveler makes reservations far in advance of departure, while the inflexible premium or business traveler waits until the last minute, often walking up to the plane at the time of departure. To capitalize on this passenger behavior, the airlines have exercised price discrimination to differentiate the passengers with advance purchase, time-of-day, and duration of stay requirements. While price discrimination helps the airline to manage its capacity constrained resource, it does not address how many seats to sell each customer segmentbusiness or leisure passengers. To further complicate the yield management analyst's task of maximizing total revenue, last minute cancellations, passengers missing connections (misconnect), and no-shows threaten to "spoil" (empty seats) seats and lose potential revenue. You will be using the strategies of discount allocation and overbooking to address this problem. Discount allocation is necessary because a plane can be filled long before departure with discount passengers-clearly not a page 331 revenue maximizing strategy. Therefore, the yield management analyst attempts to "save" seats for the last-minute premium demand by allocating only a certain amount of seats to early-booking leisure passengers. While overbooking helps overcome spoilage, it opens the possibility for oversales. The yield management analyst attempts to weigh the cost of an oversale against the cost of "spoiling" seats or losing potential revenue from an additional sale. The analyst prefers to oversell the flight up to the point where the oversale cost equals the additional revenue of adding a passenger. In this game, you will act as the yield management analyst in charge of a pseudo-flight. Based on the historical booking pattern for your flight, leisure passenger demand, typically large groups, appears as far out as 100 days before departure up until 14 days before departure. Business passenger demand enters the market closer to departure at approximately nine days prior to departure up until the time of departure. Other historical market statistics for your plane show that the average misconnect, no-show, and cancellation rate for this peak season flight is 20 percent and the average revenue per passenger is $400. Both oversales and spoilage cost the airline revenue: oversales are a direct expense, while spoilage is lost potential revenue. The higher the number of oversales, the more money gate agents must pay to get passengers off the plane. Your objective is to maximize total revenue generated on this flight GAME FACTS Airplane Capacity: 100 seats Historical Market Information: Average no-show, misconnect, and cancellation rate: 20 percent Average revenue per passenger: $400 Spoilage penalty: $200 for each empty seat Oversale penalty 1-5 oversales 6-10 1015 16+ $200 per passenger $500 $800 $1,000 Game Phases The game will be played in three phases reflecting the different time periods prior to departure. Phase / is total passenger demand received outside of 13 days prior to departure. Phase Il is total passenger demand between 13 days prior to departure and the day of departure. Historical market trends suggest that large groups and families make reservations during Phase I, while individuals and business passengers make reservations during Phase II. Phase Ill shows you the number of passengers who actually show up for the flight and their resulting revenue contribution. Objective: Maximize Total Revenue! Yield Management Game and Instructions The yield management game illustrates the trade-off between overbooking (selling more than capacity) and spoilage (having idle capacity), with the objective of maximizing revenue when faced with excess demand in the form of various revenues per passenger and different passenger volumes. This particular game focuses on airline capacity management, but is applicable to all fixed capacity services (e.g., hotels and cruise ships). When allocating seats to prospective passengers, the yield management analyst confronts a problem of maximizing total revenue for each flight. This includes capturing the ideal mix of discount and premium passengers at full capacity utilization without overselling too many customers. The objective of revenue maximization is simple (fill the airplane with the highest paying passengers), but uncertainty makes it a challenge. Specifically, historical booking trends in the airline industry indicate that the more flexible discount or leisure traveler makes reservations far in advance of departure, while the inflexible premium or business traveler waits until the last minute, often walking up to the plane at the time of departure. To capitalize on this passenger behavior, the airlines have exercised price discrimination to differentiate the passengers with advance purchase, time-of-day, and duration of stay requirements. While price discrimination helps the airline to manage its capacity constrained resource, it does not address how many seats to sell each customer segmentbusiness or leisure passengers. To further complicate the yield management analyst's task of maximizing total revenue, last minute cancellations, passengers missing connections (misconnect), and no-shows threaten to "spoil" (empty seats) seats and lose potential revenue. You will be using the strategies of discount allocation and overbooking to address this problem. Discount allocation is necessary because a plane can be filled long before departure with discount passengers-clearly not a page 331 revenue maximizing strategy. Therefore, the yield management analyst attempts to "save" seats for the last-minute premium demand by allocating only a certain amount of seats to early-booking leisure passengers. While overbooking helps overcome spoilage, it opens the possibility for oversales. The yield management analyst attempts to weigh the cost of an oversale against the cost of "spoiling" seats or losing potential revenue from an additional sale. The analyst prefers to oversell the flight up to the point where the oversale cost equals the additional revenue of adding a passenger. In this game, you will act as the yield management analyst in charge of a pseudo-flight. Based on the historical booking pattern for your flight, leisure passenger demand, typically large groups, appears as far out as 100 days before departure up until 14 days before departure. Business passenger demand enters the market closer to departure at approximately nine days prior to departure up until the time of departure. Other historical market statistics for your plane show that the average misconnect, no-show, and cancellation rate for this peak season flight is 20 percent and the average revenue per passenger is $400. Both oversales and spoilage cost the airline revenue: oversales are a direct expense, while spoilage is lost potential revenue. The higher the number of oversales, the more money gate agents must pay to get passengers off the plane. Your objective is to maximize total revenue generated on this flight GAME FACTS Airplane Capacity: 100 seats Historical Market Information: Average no-show, misconnect, and cancellation rate: 20 percent Average revenue per passenger: $400 Spoilage penalty: $200 for each empty seat Oversale penalty 1-5 oversales 6-10 1015 16+ $200 per passenger $500 $800 $1,000 Game Phases The game will be played in three phases reflecting the different time periods prior to departure. Phase / is total passenger demand received outside of 13 days prior to departure. Phase Il is total passenger demand between 13 days prior to departure and the day of departure. Historical market trends suggest that large groups and families make reservations during Phase I, while individuals and business passengers make reservations during Phase II. Phase Ill shows you the number of passengers who actually show up for the flight and their resulting revenue contribution. Objective: Maximize Total Revenue