System and method for intelligent task management and routing

Patent metadata

Field	Value
Publication number	US-2016378569-A1
Application number	US-201514754530-A
Country	US
Kind code	A1
Filing date	Jun 29, 2015
Priority date	Jun 29, 2015
Publication date	Dec 29, 2016
Grant date	—

Abstract

Systems and methods are shown for routing task objects to multiple agents that involve analyzing content of each task object in an input buffer to determine a classification relevant to the content of the task object that is added to task object metadata, which is placed in a second buffer. Objects in the second buffer are analyzed and the classification in the object metadata used to search workforce management data representing agent characteristics to identify agents who match the classification. A routing strategy is applied to the object to select an agent and the object is routed to the agent's workbin. Another aspect involves organizing workbin tasks objects by priority, according to recent system conditions excluding objects that cannot presently be processed based on a workflow strategy or status data and presenting remaining objects based on order of priority, or re-arranging objects between workbins based on recent status info.

First claim

We claim:

1 . A system for routing tasks to multiple agents, the system comprising one or more servers, each server having at least one processor for executing stored instructions to perform operations, where the one or more servers are configured to perform the following operations;
receive one or more tasks and, for each task, create a task object representing the task and a content of task, and place the task in an input buffer; analyze the content of each task object in the input buffer, determine it least one pre-defined classification that is relevant to the content of the task object and add the pre-defined classification to metadata of the task object, and place the task object in a second buffer; analyze the content of a task object in the second buffer, use the pre-defined classification in the metadata of the task object to search workforce management data representing agent characteristics, and identify one or more agents for assignment of the task object based on at least a partial match of the pre-defined classification with the agents workforce management data; and apply a pre-defined routing strategy to the task object in the second buffer to further identify one of the one or more agents identified for assignment of the task object and route the task object to a workbin corresponding to the one of the one or more agents

2 . The system of claim 1 , where the one or more servers are further configured to perform the following:
on at least one of a periodic, parametric and event basis, move unprocessed task objects from agent workbins to one of the input buffer and second buffer for re-assignment.

3 . The system of claim 2 , where the event basis further comprises a status change of at least one agent from unavailable to available.

4 . The system of claim 2 , where the parametric basis further comprises analysis of workload levels in the agents workbins.

5 . The system of claim 2 , where the periodic basis further comprises a pre-determined time interval.

6 . The system of claim 1 , where the operation of analyzing the content of a task object in the second buffer further includes:
utilizing statistical data relating to agent performance to identify at least one agent capable to process the task within a pre-defined performance criterion.

7 . The system of claim 6 , where the operation of utilizing statistical data relating to agent performance to forecast that an agent will be unlikely to process a task within a pre-defined performance criterion further includes:
utilizing statistical data relating to agent performance to determine an amount of time required to process tasks previously assigned to the agent.

8 . The system of claim I, where the operation of analyzing the content of as task object in the second buffer further includes:
utilizing workforce data to forecast at least one of availability and unavailability of an agent to process the task within a pre-determined performance criterion.

9 . The system of claim 1 , where the one or more servers are further configured to perform the following operations:
utilizing statistical data relating to agent performance, analyze task objects in an agent workbin to forecast that an agent will be unlikely to process a task within a pre-defined performance criterion and move the task object for the identified task from the agent's workbin to one of the input buffer and the second buffer for reassignment.

10 . The system of claim I, where the one or more servers are further configured to perform the following operations:
utilizing statistical data relating to agent performance, analyze task objects in an agent workbin to forecast that an agent will be unlikely to process a task within a pre-defined performance criterion and move the task object for the identified task from the agent's workbin to the second buffer for re-assignment.

11 . The system of claim 1 , where the one or more servers are further configured to perform the following operations:
utilizing statistical data relating to agent performance, analyze task objects in a first agent workbin to forecast that a first agent will be unlikely to process a task within a pre-defined performance criterion; apply the routing strategy to the task object in the first agent workbin to further identify a second agent for reassignment of the task object; and move the task object for the task from the first agent's workbin to the second agent's workbin.

12 . The system of claim 1 , where the system is further configured to operate to:
analyze task objects in an agent workbin to determine an order of priority of the task objects; exclude task objects that cannot be presently be processed based on at least one of a predefined workflow strategy and status data; and present one of the remaining task objects to the agent based on the order of priority of the task objects.

3 . The system of claim 12 , where the system is further configured to operate to:
further exclude task objects from presentation to the agent that cannot be processed within a predefined performance parameter based on a routing strategy and statistical data for the agent.

14 . The system of claim 12 , where the system is further configured to operate to:
move the excluded task objects to one of the input buffer and the second buffer for reassignment.

15 . The system of claim 12 , where the system is further configured to operate to:
order the remaining task objects for presentation based on a workflow strategy.

16 . The system of claim I where the operation of analyzing the content of a task object in the input buffer further includes:
applying a predefined model to the task object and automatically adding an additional destination to the task object based on the content of the task object.

17 . The system of claim 1 , where the operation of analyzing the content of as task object in the input buffer further includes:
analyzing the content of the task object in the input buffer and adding a keyword to the metadata of the task object, where the keyword is relevant to the content of the task object.

18 . The system of claim 1 , where the tasks further comprise interactions.

19 . The system of claim 1 , where the operation of analyzing the content of a task object in the input buffer further includes:
determining whether an agent has previously interacted with a source of the task object and adding metadata identifying the agent.

20 . A method for managing tasks for processing by agents, the tasks being represented by task objects, the method comprising steps for:
analyzing each task object in an input buffer to identify at least one of a predefined classification or keyword relevant to the task, adding the identified relevant classification or keyword to the task object as metadata, and moving the task object to a second buffer; and assigning each task object in the second buffer to an agent by:
using the identified relevant classification or keyword from the metadata of the task object to request workforce management data representing agent characteristics,
receiving workforce management data for one or more agents having workforce management data that at least partially matches the relevant classification or keyword,
applying a predefined routing strategy to the task object and the workforce management data for one or more agents to further identify one of the one or more agents for assignment of the task object, and
assigning the task object to the identified agent by movi

Assignees

• Genesys Telecommunications Laboratories Inc

Inventors

• Ristock Herbert Willi Artur
• Placiakis Vidas
• Teryoshin Vitaliy
• Korolev Nikolay I
• Petrovykh Yevgeniy
• Nitin Anand Pai Krishnanand

Classifications

• G06Q10/06316

  Sequencing of tasks or work · CPC title

• G06F9/5083 Primary

  Techniques for rebalancing the load in a distributed system · CPC title

• G06Q10/00 Primary

  Administration; Management · CPC title

• H04M2203/556

  Statistical analysis and interpretation · CPC title

• H04M3/523

  with call distribution or queueing · CPC title