Systems and methods for scheduling tasks to field professionals are provided. In one implementation, a system may receive a first request for an on-site service and schedule a task associated with the first request to be performed on a first scheduled date. After scheduling the task associated with the first request, the system may receive a second request from a connected device for an on-site service. The system may determine a time period that corresponds with an urgency level of the on-site service for the connected device, and schedule a task associated with the second request on a second scheduled date based on the urgency level. The first scheduled date and the second scheduled date may be the same date or different dates. Thereafter, the system may receive confirmation that the task associated with the first request and the task associated with the second request have been completed.

Methods, apparatuses, and systems for scheduling tasks to field professionals include a memory configured to store historical data associated with past demand for field professionals, a network interface, and at least one processor connectable to the network interface. The at least one processor is configured to access the memory and to: receive a set of requests reflecting a current demand for on-site services; predict imminent demand for on-site services based on the historical data; generate a schedule for a set of field professionals based on the current demand for on-site services; and reserve in the schedule availability based on the predicted imminent demand for on-site services.

Methods, apparatuses, and systems for scheduling tasks to field professionals include: storing, in a database, a plurality of records reflecting characteristics associated with completing a set of technical services, wherein information in each record is derived from historical experience of completing each of the technical services; receiving a request for a new technical service associated with a location; and assigning a field professional to perform the new service having determined from information in the database a likelihood that the field professional will complete the new technical service in a single on-site visit at the location.

Method and systems for scheduling tasks to field professionals include: receiving from a user at least one request for at least one on-site service associated with a location; assigning at least one field professional to at least one task of providing the at least one on-site service at the location; following completion of the at least one on-site service, obtaining data associated with the at least one on-site service; receiving from the user an additional request for an additional service, wherein the additional service is associated with the same location; retrieving information including data associated with the at least one on-site service; and assigning a field professional to perform the additional service based on the retrieved information.

Systems and methods for fixing schedule of tasks using a remote optimization engine are provided. In one implementation, the system may periodically receive from a local server a data associated with a native scheduling engine. The system may process in a stateless manner the data periodically received from the local server using the optimization engine to update a prediction model. The system may also be configured to transmit information associated with the updated prediction model to the local server for enabling improvement of the native scheduling engine.

Methods, apparatuses, and systems for scheduling tasks to field professionals include: determining real-time schedule information for field professionals independent from any schedule update received therefrom; determining, from the real-time schedule information associated with a first field professional, existence of a delay associated with tasks assigned to the first field professional; determining a likelihood that the delay will interfere with the first field professional arriving to an identified location associated with an assigned task at a scheduled time; determining from real-time schedule information associated with a second field professional whether the second field professional can arrive to the identified location; reassigning the assigned task based on the real-time schedule information associated with the first field professional and the real-time schedule information associated with the second field professional; and providing to at least one of the first field professional and the second field professional information reflecting the reassignment of the task.

Systems and methods for scheduling tasks to field professionals are provided. In one implementation, the system receives real-time information about a progress of a field professional assigned to a set of tasks. The real-time information may reflect a likelihood the field professional will complete the assigned a set of tasks. The system dynamically determines a window of opportunity to assign an additional task to the field professional based on the real-time information. Thereafter, the system identifies a plurality of optional tasks that the field professional can complete during the window of opportunity. In some cases, the window of opportunity includes an unplanned event likely to interfere with at least one scheduled task. The system can either present the optional tasks to the field professional and assign a task based on the field professional's selection; or automatically select a task for assignment to the field professional based on historical data.

Systems and methods for scheduling tasks to field professionals are provided. In one implementation, the system receives real-time information about a progress of a field professional assigned to a set of tasks. The real-time information may reflect a likelihood the field professional will complete the assigned a set of tasks. The system dynamically determines a window of opportunity to assign an additional task to the field professional based on the real-time information. Thereafter, the system identifies a plurality of optional tasks that the field professional can complete during the window of opportunity. In some cases, the window of opportunity includes an unplanned event likely to interfere with at least one scheduled task. The system can either present the optional tasks to the field professional and assign a task based on the field professional's selection; or automatically select a task for assignment to the field professional based on historical data.

Systems and methods for fixing schedule of tasks using a remote optimization engine are provided. In one implementation, the system may periodically receive from a local server a data associated with a native scheduling engine. The system may process in a stateless manner the data periodically received from the local server using the optimization engine to update a prediction model. The system may also be configured to transmit information associated with the updated prediction model to the local server for enabling improvement of the native scheduling engine.

Systems and methods for scheduling parts delivery are provided. In one implementation, a system may receive a set of requests for on-site services, wherein the on-site services of at least some of the requests require parts. The system may further schedule a set of tasks corresponding to the set of requests for a field professional. In addition, the system may determine a set of parts the field professional is likely to require to complete the set of tasks, and determine that the field professional needs an additional part not currently in the field professional's assigned inventory to complete the set of tasks. Thereafter, the system may schedule a task for delivery in the field of the at least one additional part to the field professional.