US2019058794A1PendingUtilityA1

System and method for optimizing physical placement of contact center agents on a contact center floor

Assignee: GENESYS TELECOMMUNICATIONS LABORATORIES INCPriority: Jul 29, 2016Filed: Oct 24, 2018Published: Feb 21, 2019
Est. expiryJul 29, 2036(~10 yrs left)· nominal 20-yr term from priority
H04M 2203/402H04M 3/5232G06Q 10/06393H04M 3/5175
50
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Claims

Abstract

A method includes: identifying, by a processor, one or more physical arrangements of resources in a customer contact center; predicting, by the processor, for each of the one or more physical arrangements of resources, a predicted performance metric of the physical arrangement of resources in accordance with one or more working environment parameters of the customer contact center; identifying, by the processor, a particular physical arrangement of the one or more physical arrangements having a corresponding predicted performance metric satisfying a threshold performance among the one or more physical arrangements; and outputting, by the processor, the particular physical arrangement of resources in the customer contact center.

Claims

exact text as granted — not AI-modified
What is claimed is: 
     
         1 . A method for modifying routing of interactions in a customer contact center in accordance with local disruptions, the method comprising:
 monitoring, by a processor, a performance metric in a portion of the customer contact center, the portion of the customer contact center corresponding to a physical location within the customer contact center;   comparing, by the processor, the performance metric with a typical performance value;   in response to determining that the performance metric is in a normal range, continuing to route interactions to the portion of the customer contact center; and   in response to determining that the performance metric is outside the normal range, refraining from routing interactions to the portion of the customer contact center.   
     
     
         2 . The method of  claim 1 , wherein the performance metric is in real-time. 
     
     
         3 . The method of  claim 1 , further comprising the step of:
 in response to determining that the performance metric is outside the normal range, routing interactions to other portions of the customer contact center.   
     
     
         4 . The method of  claim 1 , wherein the monitoring is performed continuously. 
     
     
         5 . The method of  claim 4 , further comprising the step of:
 in response to determining that the performance metric has returned to the normal range after a period of refraining, routing interactions to the portion of the customer contact center.   
     
     
         6 . A method for routing an incoming interaction to an agent of a customer contact center, the method comprising:
 identifying, by a processor, one or more agents of the customer contact center, each of the one or more agents having one or more skills satisfying one or more skills required by the incoming interaction;   computing, by the processor, for each identified agent, a predicted performance metric in accordance with the one or more skills required by the incoming interaction and in accordance with a working environment of the agent;   identifying, by the processor, one or more recipient agents having a predicted performance metric satisfying a threshold performance; and   routing, by the processor, the incoming interaction to at least one of the one or more recipient agents.   
     
     
         7 . The method of  claim 6 , wherein the computing the predicted performance metric for each identified agent comprises:
 retrieving, by the processor, a predictor corresponding to the identified agent;   supplying, by the processor, one or more parameters of the working environment of the agent to the predictor; and   outputting, by the processor, a predicted performance metric in accordance with the predictor.   
     
     
         8 . The method of  claim 7 , wherein the predictor comprises a linear regression model between the one or more working environment parameters and a performance metric. 
     
     
         9 . The method of  claim 7 , wherein the predictor comprises a neural network having input features comprising the one or more working environment parameters, and an output corresponding to the predicted performance metric. 
     
     
         10 . A system for modifying routing of interactions in a customer contact center in accordance with local disruptions, comprising:
 means for monitoring a performance metric in a portion of the customer contact center, the portion of the customer contact center corresponding to a physical location within the customer contact center;   means for comparing the performance metric with a typical performance value;   means for, in response to determining that the performance metric is in a normal range, continuing to route interactions to the portion of the customer contact center; and   means for, in response to determining that the performance metric is outside the normal range, refraining from routing interactions to the portion of the customer contact center.   
     
     
         11 . The performance metric of  claim 10 , wherein the performance metric is in real-time. 
     
     
         12 . The system of  claim 10 , further comprising:
 means for, in response to determining that the performance metric is outside the normal range, routing interactions to other portions of the customer contact center.   
     
     
         13 . The monitoring of  claim 10 , wherein the monitoring is performed continuously. 
     
     
         14 . The system of  claim 13 , further comprising:
 means for, in response to determining that the performance metric has returned to the normal range after a period of refraining, routing interactions to the portion of the customer contact center.

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