Real-Time Probability Determined Iteratively Throughout a Period of Time

Abstract

A system is disclosed for determining a real-time probability iteratively throughout a period of time. The system conducts an upgrade analysis by determining that an expected marginal seat revenue for a sale of an additional coach seat is greater than an expected marginal seat revenue for a sale of an additional first class seat.

1 . A method, comprising:
 determining, by a processor and in real-time iteratively throughout a period of time, an achievable coach seat demand for a flight (demand coach ) of an airplane, wherein the airplane comprises a plurality of seats, and wherein the seats are associated with at least one of a first class of service (first) or a second class of service (coach),   executing, by the processor and using the information about the demand coach  and a total number of seats in coach (CAP) and in real-time iteratively throughout the period of time, an upgrade analysis, the upgrade analysis comprising:
 determining, by the processor and in real-time, that there is excess demand coach , wherein the determining that there is excess demand coach  comprises determining that the achievable demand coach  is greater than the CAP; 
 determining, by the processor and in real-time, an expected marginal seat revenue for a sale of an additional first class seat (EMSR first ) on the flight; 
 determining, by the processor and in real-time, an expected marginal seat revenue for a sale of an additional coach seat (EMSR coach ) on the flight, and 
 in response to determining, by the processor and in real-time, that EMSR coach  is greater than EMSR first , updating an upgrade authorization parameter to offer an additional upgrade seat on the flight for sale; 
   creating, by the processor and in real-time iteratively throughout the period of time, a flight-dependent and time-dependent voucher for the additional upgrade seat for the flight, wherein the voucher dynamically and iteratively changes throughout the day based on the updating the upgrade authorization parameter and most current conditions to minimize costs;   providing, by the processor and in real-time iteratively throughout the period of time and to a customer mobile device, the offer for the additional upgrade seat on the flight to access the additional upgrade seat on the flight based on EMSR coach  being greater than EMSR first .   
     
     
         2 . The method of  claim 1 , further comprising:
 providing, by the processor, the offer to a revenue management system;   wherein the offer impacts the revenue management system and a reservation system,   wherein the revenue management system determines, based on the offer, a number of the additional upgrade seats to be offered for the flight and a respective price for each additional upgrade seat, and   wherein the revenue management system transmits to the reservation system the number of additional upgrade seats to be offered for the flight and the respective price for each additional upgrade seat.   
     
     
         3 . The method of  claim 1 , further comprising:
 adjusting, by the processor, the demand coach  for an error in the forecast, wherein the determining the demand coach  comprises bookings for coach seats plus the demand for coach seats based on a forecast for a timeframe from an analysis date to the scheduled departure of the flight; and   adjusting, by the processor and in real-time, for the risk of double sell, wherein a first class seat is sold for coach pricing and the first class seat is also sold for first class pricing.   
     
     
         4 . The method of  claim 1 ,
 wherein the determining the expected marginal seat revenue for a sale of an additional first class seat (EMSR first ) on the flight is determined by multiplying a demand price of the additional first class seat by the probability that the first class seat will be sold,   wherein the EMSR first  is a function of demand and likelihood that a ticket will be sold, and   wherein the demand decreases as time gets closer to the departure time of the flight;   wherein the determining the expected marginal seat revenue for a sale of an additional coach seat (EMSR coach ) on the flight is determined by multiplying a demand price of the additional coach seat by the probability that the coach seat will be sold,   wherein the EMSR coach  is a function of demand and likelihood that a ticket will be sold,   wherein the demand decreases as time gets closer to the departure time of the flight, and   wherein the updating the upgrade authorization parameter to offer the additional upgrade seat on the flight for sale is for a period of time until excess of demand coach  is reduced before the scheduled departure of the flight.   
     
     
         5 . The method of  claim 1 , further comprising repeating the upgrade analysis until at least one of:
 EMSR coach  is less than or equal to EMSR first  to determine a total number of upgrade seats to be sold for the flight (total upgrade seats);   the total upgrade seats is greater than or equal to a predetermined maximum;   the total upgrade seats is greater than or equal to a predetermined percentage of the total number of seats in coach (CAP); or   the total upgrade seats is greater than or equal to a predetermined percentage of the total number of seats in first class.   
     
     
         6 . The method of  claim 5 , further comprising determining an optimal time to authorize the total number of upgrade seats to be sold and, at the optimal time, updating the upgrade authorization parameter to equal the total upgrade seats. 
     
     
         7 . The method of  claim 6 , wherein the determining the optimal time comprises determining that achievable demand coach  is less than or equal to an authorized number of seats to be sold in coach (AU)+total upgrade seats. 
     
     
         8 . The method of  claim 7 , wherein the achievable demand coach  is adjusted to account for an error in a forecast, and wherein the achievable demand coach  is based upon the forecast. 
     
     
         9 . The method of  claim 7 , wherein AU is determined as an optimal AU that minimizes an overbooking cost associated with the flight based upon a CAP, a no-show forecast (NSF), a spoiled seat cost and a denied boarding cost, and wherein the denied boarding cost is dynamically calculated based upon a plurality of forecasts determining a re-accommodation cost for each of a plurality of denied passengers for the flight. 
     
     
         10 . The method of  claim 9 , wherein the NSF is determined based upon a next active leg analysis. 
     
     
         11 . The method of  claim 1 , further comprising:
 storing, by the processor, the information about the demand coach  and the CAP in a database;   tuning, by the processor, the database to optimize database performance,
 wherein the tuning includes placing frequently used files on separate file systems to reduce in and out bottlenecks; 
   designating, by the processor, a key field in data tables to speed searching for the information about the demand coach  and the CAP;   sorting, by the processor, the information about the demand coach  and the CAP according to a known order to simplify the lookup process; and   obtaining, by the processor, the information about the demand coach  and the CAP from the database.   
     
     
         12 . The method of  claim 1 , further comprising determining that the risk of a double sell is greater than an acceptable risk threshold. 
     
     
         13 . The method of  claim 12 , further comprising determining the risk of the double sell as the joint probability that the additional first class seat will be sold as a first class seat and that the additional first class seat will be sold as a coach seat. 
     
     
         14 . The method of  claim 7 , further comprising mitigating the risk of a double sell by periodically repeating the upgrade analysis to calculate an adjustment to the total upgrade seats. 
     
     
         15 . The method of  claim 14 , wherein the frequency of the repeating the upgrade analysis increases as the timeframe before departure of the flight decreases. 
     
     
         16 . The method of  claim 14 , further comprising mitigating the risk of the double sell by adjusting the upgrade seat total so that the upgrade seat total is less than at least one of a predetermined number or a predetermined percent of a total number of first class seats. 
     
     
         17 . A method, comprising:
 determining, by a processor and in real-time iteratively throughout a period of time, an achievable coach seat demand for a flight (demand coach ) of an airplane, wherein the airplane comprises a plurality of seats, and wherein the seats are associated with at least one of a first class of service (first) or a second class of service (coach);   wherein the determining demand coach  comprises bookings for coach seats plus the demand for coach seats based on a forecast for a timeframe from an analysis date to the scheduled departure of the flight;   adjusting, by the processor and in real-time iteratively throughout the period of time, demand coach  for an error in the forecast;   executing, by the processor and in real-time iteratively throughout the period of time and using the achievable coach seat demand coach,  a probability that the seat first  will be sold, a probability that the seat coach  will be sold, a seat coach  demand price and a seat first  demand price, an upgrade analysis, the upgrade analysis comprising:
 determining, by the processor and in real-time, that there is excess demand coach ; 
 determining, by the processor and in real-time, an expected marginal seat revenue for a sale of an additional first class seat (EMSR first ) on the flight, wherein EMSR first  is equal to the seat first  demand price multiplied by the probability that the seat first  will be sold flight by multiplying a demand price of the additional first class seat by the probability that the first class seat will be sold, 
 wherein EMSR first  is a function of demand and likelihood that a ticket will be sold, and 
 wherein the demand decreases as time gets closer to the departure time of the flight; 
 determining, by the processor and in real-time, an expected marginal seat revenue for a sale of an additional coach seat (EMSR coach ) on the flight, wherein EMSR coach  is equal to the seat coach  demand price multiplied by the probability that the seat coach  will be sold by multiplying a demand price of the additional coach seat by the probability that the coach seat will be sold, 
 wherein EMSR coach  is a function of demand and likelihood that a ticket will be sold, and 
 wherein the demand decreases as time gets closer to the departure time of the flight; 
 adjusting, by the processor and in real-time, for the risk of double sell, wherein a first class seat is sold for coach pricing and the first class seat is also sold for first class pricing; and 
 in response to determining and in real-time, by the processor, that EMSR coach  is greater than EMSR first , updating an upgrade authorization parameter to offer an additional upgrade seat on the flight for sale for a period of time until excess of demand coach  is reduced before the scheduled departure of the flight; 
   creating, by the processor and in real-time iteratively throughout the period of time, a flight-dependent and time-dependent voucher for the additional upgrade seat for the flight, wherein the voucher dynamically and iteratively changes throughout the day based on the updating the upgrade authorization parameter and most current conditions to minimize costs;   providing, by the processor and in real-time iteratively throughout the period of time and to a customer mobile device, the offer for the additional upgrade seat on the flight to access the additional upgrade seat on the flight based on EMSR coach  being greater than EMSR first .   
     
     
         18 . The method of  claim 17 , further comprising:
 providing, by the processor, a certain number of updated tickets to access the additional upgrade seat on the flight;   providing access information, by the processor and to an airline kiosk, that allows access to the additional upgrade seat on the flight to certain passengers with the updated tickets,   wherein the airline kiosk provides an updated boarding passes with machine readable data to the passengers;   receiving, by the processor and from an airport scanner, scanned data from the updated tickets, wherein access to the additional upgrade seat on the airplane is provided in response to the airport scanner scanning the machine readable data on the updated tickets and verifying the machine readable data on the updated tickets.   
     
     
         19 . The method of  claim 17 , wherein at least one of the seat coach  demand price or the seat first  demand price is determined based upon a timeframe from an analysis date to a date of departure of the flight. 
     
     
         20 . A computer-based method, comprising:
 determining, by an upgrade analyzer in communication with a and in real-time iteratively throughout a period of time, an achievable coach seat demand for a flight (demand coach ) of an airplane, wherein the airplane is comprised of a plurality of seats, and wherein the seats are associated with at least one of a first class of service (first) or a second class of service (coach);   wherein the determining demand coach  comprises bookings for coach seats plus the demand for coach seats based on a forecast for a timeframe from an analysis date to the scheduled departure of the flight;   adjusting, by the processor and in real-time iteratively throughout the period of time, demand coach  for an error in the forecast;   executing, by the and in real-time iteratively throughout the period of time and using the information about the demand coach  and a total number of seats in coach (CAP), an upgrade analysis, the upgrade analysis comprising:
 determining, by the and in real-time, that there is excess demand coach , wherein the determining that there is excess demand coach  comprises determining that the achievable demand coach  is greater than the CAP; 
 determining, by the and in real-time, an expected marginal seat revenue for a sale of a first class seat (EMSR first ) on the flight by multiplying a demand price of the additional first class seat by the probability that the first class seat will be sold, 
 wherein EMSR first  is a function of demand and likelihood that a ticket will be sold, and 
 wherein the demand decreases as time gets closer to the departure time of the flight; 
 determining, by the and in real-time, an expected marginal seat revenue for a sale of a coach seat (EMSR coach ) on the flight by multiplying a demand price of the additional coach seat by the probability that the coach seat will be sold, 
 wherein EMSR coach  is a function of demand and likelihood that a ticket will be sold, and 
 wherein the demand decreases as time gets closer to the departure time of the flight; 
 adjusting, by the processor and in real-time, for the risk of double sell, wherein a first class seat is sold for coach pricing and the first class seat is also sold for first class pricing; and 
 in response to determining that EMSR coach  is greater than EMSR first , updating, by the computer and in real-time, an upgrade authorization parameter to offer an additional upgrade seat on the flight for sale for a period of time until excess of demand coach  is reduced before the scheduled departure of the flight; 
   creating, by the and in real-time iteratively throughout the period of time, a flight-dependent and time-dependent voucher for the additional upgrade seat for the flight, wherein the voucher dynamically and iteratively changes throughout the day based on the updating the upgrade authorization parameter and most current conditions to minimize costs;   providing, by the and in real-time iteratively throughout the period of time, the offer for the additional upgrade seat on the flight to access the additional upgrade seat on the flight based on EMSR coach  being greater than EMSR first ; and   providing access information and an upgraded ticket, by the and in real-time iteratively throughout the period of time and to a customer mobile device, that allows access to the additional upgrade seat on the flight.