System and method for travel carrier contract management and optimization

• US 7,313,548 B2
• Filed: 06/05/2006
• Issued: 12/25/2007
• Est. Priority Date: 04/20/2001
• Status: Expired due to Fees

• Current Assignee: Liberty Peak Ventures, LLC (Dominion Harbor Enterprises, LLC)
• Original Assignee: American Express Travel Related Services Company, Inc. (American Express Company)
• Inventors: Florio, Dionino, Sauser, Olivier
• Primary Examiner(s): Hayes, John W.
• Assistant Examiner(s): NELSON, FREDA ANN
• Application Number:
  US11/422,272
• Publication Number:
  US 20060212320A1
• Time in Patent Office: 568 Days
• Field of Search: 705 5- 6, 705/47, 705/400, 706/47
• US Class Current: 705/400
• CPC Class Codes: G06Q 10/02 Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 10/025 Coordination of plural reservations, e.g. plural trip segments, transportation combined with accommodation
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0283 Price estimation or determination

Abstract

A method and system for air carrier contract management and optimization is disclosed. In particular, the present invention receives and tracks client travel data and air carrier contract data, analyzes this data and configures the data structure to be used in a goal programming algorithm to determine an optimum travel carrier solution.

Claims

1. A method for facilitating travel carrier optimization comprising the steps of:

receiving data from a set of input parameters;

facilitating data quality control processing on said data;

preparing said data by subtracting rebates from client travel spend to compute a base net-sector price;

defining constraint cells by at least one of airport pairs, class of service or ticket currency of origin;

calculating global monetary rebate on said cells;

computing global base client travel spend;

building constraints from at least a portion of said data, wherein upper or lower limits are added to establish the client travel spend or sector for each carrier;

deriving a maximum potential number of sectors;

excluding the lowest value cells from a ticket data set;

calculating a maximum potential limit correction for each travel carrier and cell;

facilitating data quality controls, wherein low ticket prices are removed or the average sector price is adjusted to a mean value;

adding a sector filters data set;

adding a client travel spend filters data set;

executing a goal programming processor to determine an optimal solution, wherein said optimal solution includes an optimal said sector, said carrier, said sector price, and said client travel spend; and

,

preparing a report based on said optimal solution.

2. The method of claim 1, further comprising the steps of:

adding original data from the client data set to said optimal solution to facilitate a report;

assigning a potential ticket price to an appropriate travel carrier;

wherein said potential ticket price is computed considering a potential rebate due to a strong share shift of the current travel carrier;

assigning an actual base ticket price to the appropriate travel carrier for each cell where a goal programming algorithm is minimized; and

,

adding previously excluded sectors with low client travel spend to said optimal solution.

3. The method of claim 2, further comprising the steps of:

facilitating a benchmark for the optimization;

wherein an optimal solution benchmark is created;

computing an air carrier flights distribution; and

estimating a percentage of segments excluded from optimization.

4. The method of claim 1, wherein receiving data comprises receiving travel contract data relating to a travel carrier contract.

5. The method of claim 1, wherein receiving data comprises receiving travel contract data relating to a travel carrier contract, wherein said travel contract data includes at least one of:

volume, segments, volume share, segment index, volume index, contract code, contract description label, contract validity period, referred client code, cost measurement indicia, agency International Air Transport Association (IATA) code, carrier code, booking code, tour type, tour box information, destination country code, fare basis code, ticket currency code, eventual IATA currency country, threshold value, and percentage of corresponding rebate value.

6. The method of claim 1, wherein client travel data comprises at least one of primary ticket number, tour type, travel carrier code, booking code, fare basis code, travel port pair, corporate accounts number, corporate travel ID, ticket date, ticket currency, ticket amount, ticket amount in US dollars, ticket tax amount, IATA code, ticket currency code, ticket credit amount, sequential travel data, travel port description, travel departure, travel arrival, departure country, arrival country, and sub-mileage distance.

7. The method of claim 4, further comprising:

matching said travel contract data with said client travel data; and

,

determining a sector price for each of said constraint cells, wherein a potential price is considered when a number of said constraint cells that are assigned exceeds an actual number of sectors and a base price is considered when a number of said constraint cells is less than or equal to said actual number of sectors.

8. The method of claim 7, further comprising generating a constraint from said constraint cells, said client travel data and said travel contract data, wherein said generated constraint comprises at least two of segment data, class of service data, travel port pair data, sector data, travel carrier data, client travel spend, and market share derived from said client travel spend and said sector data.

9. The method of claim 8, further comprising generating a penalty function constraint based on said travel contract data, wherein said penalty function constraint limits travel carrier values per sector according to travel factors, wherein said travel factors include evaluating a maximum potential capacity per carrier and at least one of carrier seat capacity, flight frequency, quality of service, and availability of direct connections per sector.

10. The method of claim 9, further comprising performing a spend share shift analysis based on said sector price, said generated penalty function constraint and said generated constraint.

11. The method of claim 10, further comprising utilizing goal programming to optimize said client travel spend based on said spend share shift analysis, and creating a report based on said optimized client travel spend.

12. The method of claim 10, further comprising configuring an analytical solutions software to facilitate said spend share shift analysis.

13. The method of claim 12, wherein said analytical solutions software is at least one of statistical analysis system (SAS), Statistical Package for the Social Sciences (SPSS), STATA, MINITAB, Matlab, and Mathematica.

14. The method of claim 8, further comprising creating an objective function to evaluate said generated constraint, wherein said objective function facilitates optimization of said client travel spend.

15. The method of claim 1, further comprising configuring a price weighting factor.

16. The method of claim 1, further comprising generating potential prices.

17. The method of claim 1, further comprising evaluating an average sector price by at least one of:

travel carrier, class of service, route, country of ticketing, and travel contract conditions.

18. The method of claim 8, further comprising configuring said generated constraint by adding a series of sectors.

19. The method of claim 1, further comprising determining a potential price, wherein said potential price comprises a ticket price as a function of a number of tickets assigned to a specific travel camer.

20. The method of claim 11, further comprising benchmarking said optimized client travel spend with an original solution to compute incremental savings.