Systems and methods for scheduling call center agents using quality data and correlation-based discovery

• US 7,853,006 B1
• Filed: 02/22/2006
• Issued: 12/14/2010
• Est. Priority Date: 02/22/2006
• Status: Expired due to Fees

• Current Assignee: Verint Americas Incorporated (Verint Systems Incorporated)
• Original Assignee: Verint Americas Incorporated (Verint Systems Incorporated)
• Inventors: Bourke, Michael Robert Jr., Watson, Joseph, Hegebarth, Kevin, Iannone, Jeff, Nourbakhsh, Illah, Hamilton, Edward, Fama, Jason
• Primary Examiner(s): Kuntz; Curtis
• Assistant Examiner(s): Le; Karen L
• Application Number:
  US11/359,909
• Time in Patent Office: 1,756 Days
• Field of Search: 379/365.06
• US Class Current: 379/265.06
• CPC Class Codes: H04M 2201/12 Counting circuits
• CPC Class Codes: H04M 2201/36 Memories
• CPC Class Codes: H04M 2201/38 Displays
• CPC Class Codes: H04M 2203/401 Performance feedback
• CPC Class Codes: H04M 2203/402 Agent or workforce management
• CPC Class Codes: H04M 3/5175 Call or contact centers supervision arrangements

Abstract

Systems and methods for visualization of call center performance are provided. An exemplary method includes the steps of: obtaining quality performance of agents data that includes information on the quality of service and quality characteristics of the agent, obtaining call center operations data that includes information on statistics and details of a call center, correlating the quality performance of agents data and the call center operations data, identifying correlation-based discovery, and optimizing call center performance based on the correlation-based discovery.

Claims

1. A method for visualization of call center performance, comprising the steps of:

obtaining quality performance of agents data that includes information on a quality of service and quality characteristics of the agent;

obtaining call center operations data that includes information on statistics and details of a call center;

discovering a correlation between the quality performance of agents data and the call center operations data, wherein the correlation is computed using one or a combination of the following methods;

Pearson linear correlation, clustering computing method, and statistical trend analysis, wherein the computation using Pearson linear correlation outputs correlation coefficient r and statistical measurement p with data set size N; and

optimizing call center performance based on the correlation.

2. The method of claim 1, wherein the quality performance of agents data further includes call quality scores, agent name, agents identity, call quality score, and call identification, wherein the call center operations data includes call identification, call type, agent name, call statistics, and temporal details, and further comprising obtaining agent schedule data that includes information on shift details and shift-related information of the agents, the agent schedule database further including skill levels, skill types, worked days, worked dates, break times, attended meetings, and training types.

3. The method of claim 1, further comprising:

obtaining quality scores of agents, the quality scores being a measurement of quality that the agents provide to a call center;

defining a scheduled interval;

defining a quality goal for the scheduled interval, the quality goal being a desired measurement of quality that the agents collectively provide to the call center;

determining a quality goal score for the scheduled interval based on the quality scores of agents; and

determining a schedule for the agents based on the quality goal, the quality goal score, and the correlation.

4. The method of claim 1, wherein determining the quality goal based on the correlation.

5. The method of claim 1, wherein the step of discovering a correlation includes using a call quality score of agents with X data, where X data is one of the quality performance of agents data and call center operations data.

6. The method of claim 1, further comprising pre-process filtering the quality performance of agents data and call center operations data, wherein filtering the data includes removing the correlated data that have greater than two standard deviations away from mean/median.

7. The method of claim 1, further comprising selective user-induced filtering of the quality performance of agents data and the call center operations data for correlation.

8. A system for visualization of call center performance, comprising:

a quality performance of agents database including data on a quality of service and quality characteristics of the agent;

a call center operations database including data on statistics and details of a call center; and

a performance correlation application that discovers a correlation between the quality performance of agents data and the call center operations data, the performance correlation application optimizing call center performance based on the correlation;

the performance correlation application configured to correlate using one or a combination of the following methods;

Pearson linear correlation, clustering computing method, and statistical trend analysis, wherein the computation using Pearson linear correlation outputs correlation coefficient r and statistical measurement p with data set size N.

9. The system of claim 8, wherein the quality performance of agents data further includes call quality scores, agent name, agents identity, call quality score, and call identification, wherein the call center operations data includes call identification, call type, agent name, call statistics, and temporal details, and further comprising agent schedule database that includes data on shift details and shift-related information of the agents, the agent schedule database further including skill levels, skill types, worked days, worked dates, break times, attended meetings, and training types.

10. The system of claim 8, further comprising an agent scheduling application that is capable of receiving quality scores of agents, the quality scores being a measurement of quality that the agents provide to a call center, the agent scheduling application transmitting the quality scores of agents over a network;

and

a manager scheduling application that is operative to;

receiving the quality scores of agents;

receiving a scheduled interval;

receiving a quality goal for the scheduled interval, the quality goal being a desired measurement of quality that the agents collectively provide to the call center;

determining a quality goal score for the scheduled interval based on the received quality scores of agents; and

determining a schedule for the agents based on the quality goal, the quality goal score, and the correlation.

11. The system of claim 10, wherein the manager scheduling application determines the quality goal based on the correlation.

12. The system of claim 8, wherein the performance correlation application correlates data using a call quality score of agents with X data, where X data is one of the quality performance of agents data and call center operations data.

13. The system of claim 8, the performance correlation application is capable of pre-process filtering the quality performance of agents data and call center operations data, wherein filtering the data includes removing the correlated data that have greater than two standard deviations away from mean/median.

14. The method of claim 8, further comprising a selective user-induced filter that provides at least parameters from the quality performance of agents data and the call center operations data for correlation.

15. A system for visualization of call center performance, comprising the steps of:

means for obtaining quality performance of agents data that includes information on quality of service and quality characteristics of the agent;

means for obtaining call center operations data that includes information on statistics and details of a call center;

means for discovering a correlation between the quality performance of agents data and the call center operations data by correlating using one or a combination of the following methods;

Pearson linear correlation, clustering computing method, and statistical trend analysis, wherein the computation using Pearson linear correlation outputs correlation coefficient r and statistical measurement p with data set size N; and

means for optimizing call center performance based on the correlation.

16. The system of claim 15, wherein the quality performance of agents data further includes call quality scores, agent name, agents identity, call quality score, and call identification, wherein the call center operations data includes call identification, call type, agent name, call statistics, and temporal details, and further comprising means for obtaining agent schedule data that includes information on shift details and shift-related information of the agents, the agent schedule data further including skill levels, skill types, worked days, worked dates, break times, attended meetings, and training types.

17. The system of claim 15, further comprising:

means for obtaining quality scores of agents, the quality scores being a measurement of quality that the agents provides to a call center;

means for defining a scheduled interval;

means for defining a quality goal for the scheduled interval, the quality goal being a desired measurement of quality that the agents collectively provide to the call center;

means for determining a quality goal score for the scheduled interval based on the quality scores of agents; and

means for determining a schedule for the agents based on the quality goal, the quality goal score, and the correlation.

18. The method of claim 17, wherein means for determining the quality goal is based on the correlation.