System and method for travel carrier contract management and optimization

• US 20020194038A1
• Filed: 04/22/2002
• Published: 12/19/2002
• Est. Priority Date: 04/20/2001
• Status: Active Grant

• Current Assignee: Liberty Peak Ventures, LLC (Dominion Harbor Enterprises, LLC)
• Original Assignee: American Express Travel Related Services Company, Inc. (American Express Company)
• Inventors: Sauser, Olivier, Florio, Dionino
• Granted Patent: US 7,286,998 B2
• Time in Patent Office: Days
• US Class Current: 705/5
• 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 travel carrier contract management and optimization method, comprising the steps of:

providing a host system for facilitating a travel optimization model;

receiving contract data relating to at least one travel carrier contract;

receiving client data associated with a client;

matching said contract data with said client data to facilitate a spend share shift analysis;

generating program constraints from at least said client data and said contract data; and

performing a spend share shift analysis on said constraints to optimize travel carrier contracting in order to optimize client spend.

2. The method of claim 1, said performing step further comprising the step of configuring an analytical solutions software program to facilitate said spend share shift analysis.

3. The method of claim 2, wherein said analytical solutions software is selected from a group of software solutions consisting of SAS, SPSS, STATA, MINITAB, Matlab, and Mathematica.

4. The method of claim 1, further comprising the step of creating an objective function to evaluate the constraints;

wherein said objective function is configured to facilitate the optimization of client spend.

5. The method of claim 1, further comprising the step of generating a penalty function;

wherein said penalty function is configured to evaluate at least the carrier seat capacity, flight frequency, or direct/indirect flight routes.

6. The method of claim 1, further comprising the step of configuring one or more price weighting factors.

7. The method of claim 1, further comprising the step of generating potential prices.

8. The method of claim 1, further comprising the step of evaluating the average sector price by at least one of:

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

9. The method of claim 1, wherein said constraints comprise one or more of the following:

segment data, class of service data, airport pair data, sector data, travel carrier, client spend, market share, and any key value indicator derived from client spend and sectors.

10. The method of claim 9, wherein said sector data constraint comprises travel carrier data, airport pair data, ticket origin data and class of service data.

11. The method of claim 10, further comprising the step of configuring a constraint by adding a series of sectors.

12. The method of claim 1, further comprising the step of fixing a ticket price.

13. The method of claim 1, further comprising the step of determining a potential price;

wherein said potential price comprises the ticket price as a function of the number of tickets assigned to a specific travel carrier.

14. The method of claim 1, further comprising the step of configuring a penalty function constraint;

wherein said penalty function constraint limits air carrier value according to travel factors.

15. The method of claim 14, wherein said travel factors includes one or more of the following:

maximum potential capacity per sector, quality of service, and availability of direct connections.

16. The method of claim 1, further comprising the step of benchmarking said optimal solution with original solution to compute incremental savings.

17. The method of claim 1, wherein said client data is received from a travel agency system.

18. The method of claim 1, wherein said contract data is received from a travel carrier system.

20. The method of claim 19, 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 the appropriate travel carrier;

wherein said potential ticket price is computed considering the 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;

adding previously excluded sectors with low spend to said optimal solution; and

preparing report.

21. The method of claim 20, 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 the percentage of segments excluded from optimization.

19. 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 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 spend;

building constraints from at least a portion of said data;

wherein upper or lower limits are added to establish the 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 spend filters data set; and

executing a goal programming processor to determine an optimal solution.

22. A system for facilitating travel carrier contract management, comprising:

data acquisition component for facilitating the acquisition of contract and client data;

a data quality engine configured to facilitate the quality and integrity of said contract data and said client data;

a processing component for facilitating the analysis of said contract and client data to achieve an optimized result; and

a reporting component for facilitating reporting said optimized result.

23. The system of claim 22, further comprising a data storage component to facilitate hosting a client data directory, a contracts directory;

a relational data directory; and

an aggregated data set directory.

24. The system of claim 22, further comprising a sector constraint;

wherein said sector constraint is a four-dimensional constraint comprising the air carrier, airport pair, ticket origin, and class of service.

25. The system of claim 22, further comprising result data tables.

26. The system of claim 25, wherein said result data tables comprise a benchmark summary table, an air carrier summary table, a benchmark table and a solutions table.