Dynamic schedule mediation

• US 7,693,735 B2
• Filed: 11/23/2004
• Issued: 04/06/2010
• Est. Priority Date: 11/23/2004
• Status: Active Grant

• Current Assignee: TOA Technologies, Inc. (Oracle Corporation)
• Original Assignee: TOA Technologies, Inc. (Oracle Corporation)
• Inventors: Brisker, Yuval, Carmi, Irad
• Primary Examiner(s): Sterrett; Jonathan G.
• Assistant Examiner(s): CHOI, PETER H
• Application Number:
  US10/994,313
• Publication Number:
  US 20060111957A1
• Time in Patent Office: 1,960 Days
• Field of Search: 705/9
• US Class Current: 705/7.16
• CPC Class Codes: G06Q 10/063116 Schedule adjustment for a person or group
• CPC Class Codes: G06Q 10/06398 Performance of employee with respect to a job function
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting
• CPC Class Codes: G06Q 10/1095 Meeting or appointment
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

An apparatus and method provides dynamic schedule mediation by scheduling and monitoring appointments between a service provider and customers. The apparatus and method uses a statistical analysis to determine a best appointment time based on at least one of: historical performance patterns, the type of service requested during the appointment, geographic location of the customer or the service provider, time of day, time of year, weather, skills of the service provider, and automobile traffic conditions. The system and method continuously monitors changes to the appointment initiated by the customer or the service provider and notifies the other. The statistical information of a service provider may also be used to evaluate the rules of the service provider and to evaluate individual field service personnel of the service provider.

Claims

1. An apparatus for managing appointments between a customer and a service provider comprising a plurality of individuals, said apparatus comprising:

a communication gateway configured to receive and deliver communications;

a microprocessor configured to determine the estimated time of arrival or performance of a service appointment; and

a statistics engine, wherein a statistical determination of a performance of the service provider is based on at least one of;

historical performance patterns, a type of service requested during a requested appointment, geographic location of the customer or the service provider, time of day, time of year, weather, skills of at least one individual of the service provider, or automobile traffic conditions,

wherein the microprocessor is configured to determine if a delay occurs in a schedule of appointments and determines if the delay will propagate to affect other appointments,

wherein the determination if a delay will propagate is based on at least one of a type of appointment of the requested appointment, a type of delay of the delay, and a statistical determination of delay propagation based on historical information related to the requested appointment,

wherein said microprocessor is configured to monitor performance of each of said plurality of individuals so as to provide a continuously updated statistical evaluation for each of said plurality of individuals,

wherein the microprocessor is configured to maintain a self-calibrating repository of personal performance patterns for each individual based on at least one of skills, customer location and historical performance patterns, configured to store a hierarchy of individuals in a database based on performance, and configured to select an individual from said plurality of individuals for an appointment based on at least one of skills, customer location, and historical performance patterns of the plurality of individuals,

wherein the microprocessor is configured to schedule said service appointment based on at least one of said estimated time of arrival or performance, a communication from a customer, business rules of a service provider and the statistical determination of performance of the service provider,

wherein said microprocessor is configured to determine the estimated time of arrival or performance of a service appointment based on an individual'"'"'s learned historical performance patterns, and

wherein the microprocessor is configured to determine the estimated time of arrival or performance of the service appointment further based on real time service delivery data.

2. The apparatus of claim 1, further comprising a notification engine configured to provide a predetermined notification to the customer related to an appointment.

3. The apparatus of claim 2, wherein the predetermined notification includes a reminder to the customer of an appointment.

4. The apparatus of claim 2, wherein the predetermined notification includes a notification of a change in an appointment schedule.

5. The apparatus of claim 1, wherein the statistical determination is based on at least one of duration of appointment, start of appointment, or end of appointment.

6. The apparatus of claim 1, wherein the microprocessor is configured to select a service provider from a plurality of service providers for an appointment based on the historical performance patterns of the plurality of service providers.

7. A method of dynamically managing appointments between a customer and a service provider, said service provider including a plurality of individuals, said method comprising the steps of:

receiving requests for a service appointment from a customer;

monitoring performance of each of said plurality of individuals so as to provide a continuously updated statistical evaluation for each of said plurality of individuals;

determining, using a microprocessor, the estimated time of arrival or performance of the service appointment based on an individual'"'"'s learned historical performance patterns;

determining, using a statistics engine, statistical characteristics of a performance of the service provider based on at least one of;

historical performance patterns, a type of service requested during a requested appointment, geographic location of the customer or the service provider, time of day, time of year, weather, skills of the service provider, or automobile traffic conditions;

determining, using a microprocessor, if a delay occurs in a schedule of appointments and determining if the delay will propagate to affect other appointments,

wherein the determination if a delay will propagate is based on at least one of a type of appointment of the requested appointment, a type of delay of the delay, and a statistical determination of delay propagation based on historical information related to the requested appointment;

maintaining a self-calibrating repository of personal performance patterns for each individual based on at least one of skills, customer location and historical performance patterns, storing a hierarchy of individuals in a database based on performance, and selecting an individual from said plurality of individuals for an appointment based on at least one of skills, customer location, and historical performance patterns of the plurality of individuals; and

scheduling the service appointment of a customer with a service provider based on at least one of said estimated time of arrival or performance, a communication from a customer, business rules of a service provider and the statistical characteristics of the performance of the service provider,

wherein the determining the estimated time of arrival or performance of the service appointment step is further based on real time service delivery data.

8. The method of claim 7, further comprising the step of modifying the appointment schedule if the delay is determined to propagate, and notifying customers of a change in appointment schedule.

9. The method of claim 8, wherein the step of determining if the delay will propagate includes determining one of:

whether the service is repetitive, whether the delay was caused by a global problem, or whether the delay is likely to propagate based on historical information indicative of characteristics of the appointment.

10. The method of claim 7, further comprising selecting a service provider from a plurality of service providers for an appointment based on the historical performance patterns of the plurality of service providers.

11. The method of claim 7, further comprising the steps of prompting customers to respond to automated messages confirming an appointment and applying a response of the customer to an existing appointment schedule.

12. The method of claim 7, further comprising the steps of periodically collecting statistical data indicative of the statistical determination of performance of at least one individual of the service provider, evaluating business rules of the service provider using the statistical data, and providing optimization recommendations.

13. A non-transitory computer readable storage medium with an executable program stored thereon, wherein the program instructs a microprocessor to perform the following steps for dynamically managing appointments between a customer and a service provider including a plurality of individuals, said method comprising the steps of:

receiving requests for a service appointment from a customer;

monitoring performance of each of said plurality of individuals so as to provide a continuously updated statistical evaluation for each of said plurality of individuals;

determining, using a microprocessor, the estimated time of arrival or performance of the service appointment based on an individual'"'"'s learned historical performance patterns;

determining, using a statistics engine, statistical characteristics of a performance of the service provider based on at least one of;

historical performance patterns, a type of service requested during a requested appointment, geographic location of the customer or the service provider, time of day, time of year, weather, skills of the service provider, or automobile traffic conditions;

determining, using a microprocessor, if a delay occurs in a schedule of appointments and determining if the delay will propagate to affect other appointments, wherein the determination if a delay will propagate is based on at least one of a type of appointment of the requested appointment, a type of delay of the delay, and a statistical determination of delay propagation based on historical information related to the requested appointment;

maintaining a self-calibrating repository of personal performance patterns for each individual based on at least one of skills, customer location and historical performance patterns, storing a hierarchy of individuals in a database based on performance, and selecting an individual from said plurality of individuals for an appointment based on at least one of skills, customer location, and historical performance patterns of the plurality of individuals; and

scheduling the service appointment of a customer with a service provider based on at least one of said estimated time of arrival or performance, a communication from a customer, business rules of a service provider and the statistical characteristics of the performance of the service provider,

wherein the determining the estimated time of arrival or performance of the service appointment step is further based on real time service delivery data.

14. The non-transitory computer readable storage medium of claim 13 further comprising instructions to perform the steps of modifying the appointment schedule if the delay is determined to propagate, and notifying customers of a change in appointment schedule.

15. The non-transitory computer readable storage medium of claim 13, wherein the step of determining if the delay will propagate includes determining one of:

whether the service is repetitive, whether the delay was caused by a global problem, or whether the delay is likely to propagate based on historical information indicative of characteristics of the appointment.

16. The non-transitory computer readable storage medium of claim 13, further comprising instructions to perform the step of selecting a service provider from a plurality of service providers for an appointment based on the historical performance patterns of the plurality of service providers.

17. The non-transitory computer readable storage medium of claim 13, further comprising instructions to perform the steps of prompting customers to respond to automated messages confirming an appointment and applying a response of the customer to an existing appointment schedule.

18. The non-transitory computer readable storage medium of claim 13, further comprising instructions to perform the steps of periodically scanning system logs to collect statistical data indicative of the statistical determination of performance of at least one individual of the service provider, evaluating business rules of the service provider using the statistical data, and providing optimization recommendations.