Keith R. McFarlane - Denver CO Andrew Derek Flockhart - Thornton CO Lucinda M. Sanders - Boulder CO Paul L. Richman - Boulder CO Darryl J. Maxwell - Lafayette CO
Assignee:
Avaya Technology Corp. - Basking Ridge NJ
International Classification:
H04M 300
US Classification:
37926505, 37926605
Abstract:
The system for integrating agent database access skills in call center agent assignment applications dynamically generates data indicative of an agents effective skill level by mapping the agents acquired skills into their augmented skills representative of their ability to use the various automated resources that are required to satisfy the customers request. The determined effective skill level is automatically updated as changes in the agents effective skills are measured. In order to distribute work among the agents based upon agent skill levels, there must be a measure of each agents competence with a particular skill. The pool of agents is divided into categories of those who must use guided problem solving tools to service a customer request, those who can address issues beyond the scope of the guided problem solving tool, and those who exhibit various levels of efficacy in using the guided problem solving tool. The system for integrating agent database access skills in call center agent assignment applications automatically computes an agents effective skill level, which is a term used herein to describe a metric indicative of the agents overall knowledge management ability consisting of both acquired skills and augmented skills.
Workflow-Scheduling Optimization Driven By Target Completion Time
Andrew D. Flockhart - Thornton CO Darryl J. Maxwell - Lafayette CO Keith Robert McFarlane - Aurora CO Paul L. Richman - Boulder CO Lucinda M. Sanders - Boulder CO
Assignee:
Avaya Technology Corp. - Basking Ridge NJ
International Classification:
G06F 1900
US Classification:
700102, 700100, 705 8, 37926601
Abstract:
The flow of work items ( ) through a workflow process ( ) is optimized by repeatedly reordering (FIG. ) work items enqueued in inbox queues ( ) of workflow process tasks ( ) to maximize results according to a given business strategy expressed through target times. Each enqueued work item has an associated in-queue rating (IQR ) that represents the number of queue positions ( ) that the work item can be retarded or needs to be advanced to meet its target time. When a work item enters a queue and whenever a work item changes its queue position, its IQR is computed. An optimization function is then performed ( ) on the queue to determine an order of the enqueued work items that optimizes a metric of those work items that may fail to meet their target times. The work items in the queue are then reordered ( ) accordingly.
Integrated Work Management Engine For Customer Care In A Communication System
David L. Bauer - Cherry Hills Village CO Keith R. McFarlane - Pleasanton CA Andrew Derek Flockhart - Thornton CO Lucinda M. Sanders - Boulder CO Gary S. King - Broomfield CO Darryl J. Maxwell - Lafayette CO Steve R. Russell - Sausalito CA Robert Alan Stewart - Oakland CA Wendy S. Cook - Oakland CA
Assignee:
Avaya Inc. - Basking Ridge NJ
International Classification:
H04M 300
US Classification:
379242, 37926509, 709100, 709201
Abstract:
The present integrated work management engine for customer care orchestrates all forms of work relating to the servicing of customer requests across the entire business enterprise. This integrated work management engine brings together all types of disparate communication system components, applications and information storage systems so the business which provides the customer care via these systems can respond to their customer requests in a unified, efficient and effective manner. The integrated work management engine also integrates the real time operation of the front office customer communications and the batch data processing mode of the back office. The integrated work management engine accepts work through multiple access channels, where each work request is automatically mapped to a process flow that specifies the task associated with the handling of the particular work item. The integrated work management engine uses resource selection algorithms to select the customer agent who is best equipped to handle the next step of the work request where customer data is accessed, and customer case files are updated through the fulfillment process. The selected customer agent views the customer information, process information, forms, and performance statistics on their desktop terminal device through an API set that is tightly coupled to the integrated work management engine.
System For Automatically Assigning Skill Levels To Multiple Skilled Agents In Call Center Agent Assignment Applications
Keith R. McFarlane - Denver CO Andrew Derek Flockhart - Thornton CO Lucinda M. Sanders - Boulder CO Paul L. Richman - Boulder CO Darryl J. Maxwell - Lafayette CO
Assignee:
Avaya Inc. - Lincroft NJ
International Classification:
H04M 300
US Classification:
37926505, 37926605
Abstract:
The system for integrating agent database access skills in call center agent assignment applications dynamically generates data indicative of an agents effective skill level by mapping the agents acquired skills into their augmented skills representative of their ability to use the various automated resources that are required to satisfy the customers request. The determined effective skill level is automatically updated as changes in the agents effective skills are measured. In order to distribute work among the agents based upon agent skill levels, there must be a measure of each agents competence with a particular skill. The pool of agents is divided into categories of those who must use guided problem solving tools to service a customer request, those who can address issues beyond the scope of the guided problem solving tool, and those who exhibit various levels of efficacy in using the guided problem solving tool. The system for integrating agent database access skills in call center agent assignment applications automatically computes an agents effective skill level, which is a term used herein to describe a metric indicative of the agents overall knowledge management ability consisting of both acquired skills and augmented skills.
Andrew D. Flockhart - Thornton CO Keith Robert McFarlane - Pleasanton CA Lucinda M. Sanders - Boulder CO
Assignee:
Avaya Technology Corp. - Basking Ridge NJ
International Classification:
H04M 3523
US Classification:
37926512, 37920201, 37920701
Abstract:
In a customer contact center ( ), a plurality of customers communications are serviced simultaneously by one resource ( ) (agent or port). A conferencing function ( ) connects the plurality of customers ( ) to the one resource and/or to each other. When a resource becomes available, a batch service function ( ) determines ( ), for each skill of the resource, the value to the contact center of having the resource presently serve communications needing that skill, and uses the conferencing function to conference ( ) a plurality of communications needing the skill having the highest value with the resource. The conference connection may be listen-only, listen-and-talk, or listen-only/then listen-and-talk.
System For Context Based Media Independent Communications Processing
Gregory Lane Anderson - Dallas TX Lucinda M. Sanders - Boulder CO Robert W. Donnelly - New Brunswick NJ Eugene Mathews - Barrington IL Mark Landers - Fair Haven NJ
Assignee:
Avaya Technology Corp. - Basking Ridge NJ
International Classification:
H04M 300
US Classification:
379265
Abstract:
The present media independent communications processing system functions to provide business useful services to customers with the anymedia resources that are required to satisfy the customer's request. In particular, the system carries call information across the entirety of a transaction with the call being managed as an anymedia multi-transactional event. The model used for the present media independent communications processing system, as embodied in a call center, comprises a hallways and rooms paradigm that enables the customer to dynamically navigate their anymedia communications connection to a desired information providing source. As the customer's call is routed during the duration of the communication session, the call context information is stored and used by the rules-based call routing process to identify a source of information/services that is best adapted to serve the needs of this customer. The communication connection is viewed as one segment of a potentially long-term interaction between customer and service provider, with the present media independent communications processing system providing both the customer and serving agent with access to relevant customer and service provider data. In this example, the customer context information includes, but is not limited to: customer data, customer profile/preferences/history, environment data; while the corresponding agent context information includes, but is not limited to: agent skills and job function, agent queue length, fairness of call routing.
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