Systems and methods for repurposing paid time off
The present disclosure relates generally to utilizing paid time off. In one example, the systems and methods described herein may provide an infrastructure to repurpose paid time off into other uses, such as cash, travel, bill payments, and the like.
1. A computer-implemented method comprising:
receiving through an interface a request to repurpose a paid time off (PTO) benefit for travel, wherein the request corresponds to an employee associated with an employer, and wherein the request indicates a set of travel option selections provided through the interface;
processing performance data and historical workforce demand data corresponding to the employer through a trained machine learning algorithm to predict future periods of time associated with increased workforce demand;
transmitting an employee data payload, wherein the employee data payload includes the set of travel option selections and an indication of the future periods of time, and wherein when the employee data payload is received at a travel router, the travel router uses the employee data payload to identify a set of available travel options corresponding to the employee data payload;
dynamically updating the interface to provide the set of available travel options, wherein an available travel option is presented with a corresponding PTO benefit amount required for purchase of the available travel option;
detecting through the interface a selection of a particular available travel option, wherein the selection corresponds to a PTO benefit amount associated with the employee;
transmitting a monetary amount corresponding to the PTO benefit amount for the particular available travel option, wherein when the monetary amount is received by the travel router, the travel router issues an instrument associated with the particular available travel option;
updating a system associated with the employer to indicate a new amount of the PTO benefit available to the employee; and
updating a different machine learning algorithm using the selection and historical PTO benefit usage data, wherein the historical PTO benefit usage data corresponds to different workforce option selections over time, and wherein the different machine learning algorithm is trained to generate different workforce options for repurposing PTO benefits.
2. The computer-implemented method of claim 1 , wherein the set of available travel options includes one or more recommended travel options, wherein the one or more recommended travel options are generated based on a set of employee preferences, and wherein the set of employee preferences corresponds to preferred destinations for the travel.
3. The computer-implemented method of claim 1 , further comprising:
continuously monitoring a Global Distribution System (GDS) according to the future periods of time predicted through the trained machine learning algorithm to obtain the set of available travel options.
4. The computer-implemented method of claim 1 , further comprising:
identifying one or more policies associated with the employee, wherein the one or more policies define limitations on travel destinations available to the employee, and wherein the one or more policies are used to refine the set of available travel options.
5. The computer-implemented method of claim 1 , further comprising:
generating a calendar, wherein the calendar indicates the future periods of time associated with the increased workforce demand; and
providing the calendar through the interface.
6. The computer-implemented method of claim 1 , further comprising:
providing an opportunity to cancel the particular available travel option, wherein the opportunity is provided for a particular period of time; and
providing the instrument associated with the particular available travel option as a result of the employee not having canceled the particular available travel option during the particular period of time.
7. The computer-implemented method of claim 1 , wherein the future periods of time are further associated with probabilities that PTO requests submitted during the future periods of time are approved.
8. A system, comprising:
one or more processors; and
memory storing thereon instructions that, as a result of being executed by the one or more processors, cause the system to:
receive through an interface a request to repurpose a paid time off (PTO) benefit for travel, wherein the request corresponds to an employee associated with an employer, and wherein the request indicates a set of travel option selections provided through the interface;
process performance data and historical workforce demand data corresponding to the employer through a trained machine learning algorithm to predict future periods of time associated with increased workforce demand;
transmit an employee data payload, wherein the employee data payload includes the set of travel option selections and an indication of the future periods of time, and wherein when the employee data payload is received at a travel router, the travel router uses the employee data payload to identify a set of available travel options corresponding to the employee data payload;
dynamically update the interface to provide the set of available travel options, wherein an available travel option is presented with a corresponding PTO benefit amount required for purchase of the available travel option;
detect through the interface a selection of a particular available travel option, wherein the selection corresponds to a PTO benefit amount associated with the employee;
transmit a monetary amount corresponding to the PTO benefit amount for the particular available travel option, wherein when the monetary amount is received by the travel router, the travel router issues an instrument associated with the particular available travel option;
update a system associated with the employer to indicate a new amount of the PTO benefit available to the employee; and
updating a different machine learning algorithm using the selection and historical PTO benefit usage data, wherein the historical PTO benefit usage data corresponds to different workforce option selections over time, and wherein the different machine learning algorithm is trained to generate different workforce options for repurposing PTO benefits.
9. The system of claim 8 , wherein the set of available travel options includes one or more recommended travel options, wherein the one or more recommended travel options are generated based on a set of employee preferences, and wherein the set of employee preferences corresponds to preferred destinations for the travel.
10. The system of claim 8 , wherein the instructions further cause the system to:
continuously monitor a Global Distribution System (GDS) according to the future periods of time predicted through the trained machine learning algorithm to obtain the set of available travel options.
11. The system of claim 8 , wherein the instructions further cause the system to:
identify one or more policies associated with the employee, wherein the one or more policies define limitations on travel destinations available to the employee, and wherein the one or more policies are used to refine the set of available travel options.
12. The system of claim 8 , wherein the instructions further cause the system to:
generate a calendar, wherein the calendar indicates the future periods of time associated with the increased workforce demand; and
provide the calendar through the interface.
13. The system of claim 8 , wherein the instructions further cause the system to:
provide an opportunity to cancel the particular available travel option, wherein the opportunity is provided for a particular period of time; and
provide the instrument associated with the particular available travel option as a result of the employee not having canceled the particular available travel option during the particular period of time.
14. The system of claim 8 , wherein the future periods of time are further associated with probabilities that PTO requests submitted during the future periods of time are approved.
15. A non-transitory, computer-readable storage medium storing thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to:
receive through an interface a request to repurpose a paid time off (PTO) benefit for travel, wherein the request corresponds to an employee associated with an employer, and wherein the request indicates a set of travel option selections provided through the interface;
process performance data and historical workforce demand data corresponding to the employer through a trained machine learning algorithm to predict future periods of time associated with increased workforce demand;
transmit an employee data payload, wherein the employee data payload includes the set of travel option selections and an indication of the future periods of time, and wherein when the employee data payload is received at a travel router, the travel router uses the employee data payload to identify a set of available travel options corresponding to the employee data payload;
dynamically update the interface to provide the set of available travel options, wherein an available travel option is presented with a corresponding PTO benefit amount required for purchase of the available travel option;
detect through the interface a selection of a particular available travel option, wherein the selection corresponds to a PTO benefit amount associated with the employee;
transmit a monetary amount corresponding to the PTO benefit amount for the particular available travel option, wherein when the monetary amount is received by the travel router, the travel router issues an instrument associated with the particular available travel option;
update a system associated with the employer to indicate a new amount of the PTO benefit available to the employee; and
updating a different machine learning algorithm using the selection and historical PTO benefit usage data, wherein the historical PTO benefit usage data corresponds to different workforce option selections over time, and wherein the different machine learning algorithm is trained to generate different workforce options for repurposing PTO benefits.
16. The non-transitory, computer-readable storage medium of claim 15 , wherein the set of available travel options includes one or more recommended travel options, wherein the one or more recommended travel options are generated based on a set of employee preferences, and wherein the set of employee preferences corresponds to preferred destinations for the travel.
17. The non-transitory, computer-readable storage medium of claim 15 , wherein the executable instructions further cause the computer system to:
continuously monitor a Global Distribution System (GDS) according to the future periods of time predicted through the trained machine learning algorithm to obtain the set of available travel options.
18. The non-transitory, computer-readable storage medium of claim 15 , wherein the executable instructions further cause the computer system to:
identify one or more policies associated with the employee, wherein the one or more policies define limitations on travel destinations available to the employee, and wherein the one or more policies are used to refine the set of available travel options.
19. The non-transitory, computer-readable storage medium of claim 15 , wherein the executable instructions further cause the computer system to:
generate a calendar, wherein the calendar indicates the future periods of time associated with the increased workforce demand; and
provide the calendar through the interface.
20. The non-transitory, computer-readable storage medium of claim 15 , wherein the executable instructions further cause the computer system to:
provide an opportunity to cancel the particular available travel option, wherein the opportunity is provided for a particular period of time; and
provide the instrument associated with the particular available travel option as a result of the employee not having canceled the particular available travel option during the particular period of time.
21. The non-transitory, computer-readable storage medium of claim 15 , wherein the future periods of time are further associated with probabilities that PTO requests submitted during the future periods of time are approved.