Probability Analysis and Prediction Modeling

Abstract

A system is disclosed for forecasting costs and determining probabilities, along with the use of prediction modeling. The system analyzes previous actions to determine future actions, while using cost prediction modeling.

1 . A system comprising:
 a network interface in communication with a memory;   the memory in communication with a processor for enabling forecasting and overbooking;   the processor, when executing a computer program, executes operations comprising:   forecasting, by the processor, a spoiled seat (SS) cost for each seat in a plurality of seats associated with the flight, wherein the plurality of seats associated with a flight are obtained from an airline central data repository over the internet by invoking logic within modules by passing parameters relating to requests for data;   forecasting, by the processor, a denied boarding (DB) cost for the flight based on a probability of a volunteer not taking the flight;   determining, by the processor and in real-time iteratively throughout the period of time and based on passenger name record characteristics, a booked passenger no-show forecast (NSF) for each booked passenger associated with the flight, wherein the booked passenger NSF is based upon whether the respective passenger flew on a previous leg of a passenger itinerary;   aggregating, by the processor and in real-time iteratively throughout the period of time, the booked passenger NSF and an unbooked passenger NSF to create a flight NSF; and   determining, by the processor and in real-time iteratively throughout the period of time and using a flight cost prediction model, an authorized seat allocation (AU) for the flight that minimizes an overbooking cost, wherein the overbooking cost is based upon an accumulation of each SS cost, the DB cost and the flight NSF.   
     
     
         2 . The system of  claim 1 , wherein at least one of the reservation system and the revenue management system uses the AU to determine the number of additional seats to be sold for the flight and the respective price for each additional seat. 
     
     
         3 . The system of  claim 1 , wherein the SS cost is based upon at least one of a current selling class of the flight and historic fares associated with the flight. 
     
     
         4 . The system of  claim 1 , wherein the forecasting the DB cost comprises determining a first probability that a first DB passenger will be involuntary or voluntary. 
     
     
         5 . The system of  claim 4 , wherein the forecasting the DB cost further comprises determining a second probability that a second DB passenger will be involuntary or voluntary, wherein the second probability is based upon the first probability. 
     
     
         6 . The system of  claim 4 , wherein the DB cost is based upon at least one of a non-compensation factor, a voucher amount, a voucher breakage factor, an expected percentage of volunteers, an ill-will factor, an involuntary DB cost, an expected accommodations cost, a double DB factor or the probability of voluntary denial. 
     
     
         7 . The system of  claim 1 , wherein the booked passenger NSF is further based upon at least one of the complete passenger itinerary of each respective passenger or an adjustment factor, wherein the adjustment factor is determined based upon historical NSF data. 
     
     
         8 . The system of  claim 1 , wherein the determining the booked passenger NSF comprises determining, for at least a subset of booked passengers, a conditional probability of a passenger showing for a second leg given the passenger flew a first leg. 
     
     
         9 . The system of  claim 8 , further comprising adjusting the booked passenger NSF in response to determining, for at least a subset of booked passengers, whether the first leg and the second leg are scheduled for the same day. 
     
     
         10 . The system of  claim 1 , further comprising determining a next active leg (NAL) for a first booked passenger, wherein the first booked passenger is one of a plurality of passengers associated with the flight. 
     
     
         11 . The system of  claim 10 , further comprising determining a first booked passenger NSF as a probability that the first booked passenger will show for the NAL, wherein the booked passenger NSF is based upon the first booked passenger NSF. 
     
     
         12 . The system of  claim 1 , further comprising:
 transmitting, by the computer, the AU to a reservation system and a revenue management system;
 wherein the revenue management system determines, based on the updated authorization parameter, a number of additional seats to be sold for the flight and a respective price for each additional seat, 
   receiving, by the computer and from the reservation system and the revenue management system, the number of additional seats to be sold for the flight and the respective price for each additional seat;   providing, by the computer, a certain number of tickets to access the flight based on the AU and the number of additional seats; and   providing access information, by the computer and in real-time, that allows access to the flight for the certain number of the tickets.   
     
     
         13 . The system of  claim 1 , wherein the booked passenger NSF is based upon at least one of a previous leg, a subsequent leg or direction of travel for each booked passenger. 
     
     
         14 . The system of  claim 1 , further comprising:
 calculating, by the processor, a first expected marginal seat revenue (EMSR) for each first class seat on the flight; and   comparing, by the processor, the respective EMSR to a second EMSR for a potential sale of an additional coach seat.   
     
     
         15 . The system of  claim 14 , wherein the comparing the respective EMSR to a second EMSR comprises adjusting for the risk of double sell. 
     
     
         16 . The system of  claim 15 , further comprising determining a coach upgrade parameter based upon the comparing. 
     
     
         17 . The system of  claim 16 , wherein at least one of a reservation system or a revenue management system uses the coach upgrade parameter to determine a number of additional seats to be offered for sale for the flight and a respective price for each additional seat. 
     
     
         18 . The system of  claim 16 , further comprising determining an optimal time for the additional seats to be offered for sale and making the optimal time available to the at least one of the reservation system or the revenue management system. 
     
     
         19 . The system of  claim 18 , wherein the determining the optimal time comprises determining that a coach achievable demand is less than the AU plus the coach upgrade parameter. 
     
     
         20 . The system of  claim 1 , further comprising:
 creating, by the processor and in real-time iteratively throughout a period of time, a flight-dependent and time-dependent voucher based on the SS cost, the DB cost, the booked passenger NSF, the unbooked passenger NSF, the flight NSF, the AU, the overbooking cost and most current conditions to minimize costs,   wherein the voucher dynamically and iteratively changes throughout the day to minimize costs based on the SS cost, the DB cost, the booked passenger NSF, the unbooked passenger NSF, the flight NSF, the AU, the overbooking cost and most current conditions; and   providing, by the processor and in real-time iteratively throughout the period of time and to a customer mobile device, the offer for the AU.