ENHANCING WORK FORCE MANAGEMENT WITH SPEECH ANALYTICS

• US 20150381807A1
• Filed: 06/30/2014
• Published: 12/31/2015
• Est. Priority Date: 06/30/2014
• Status: Active Grant

• Current Assignee: Genesys Telecommunications Laboratories Incorporated (Genesys Cloud Services Incorporated)
• Original Assignee: Genesys Telecommunications Laboratories Incorporated (Genesys Cloud Services Incorporated)
• Inventors: Konig, Yochai, Ristock, Herbert Willi Artur, Konig, David
• Granted Patent: US 10,116,799 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/063112 Skill-based matching of a person or a group to a task
• CPC Class Codes: H04M 2203/402 Agent or workforce management
• CPC Class Codes: H04M 3/5233 Operator skill based call distribution

Abstract

A method for generating an agent work schedule includes: analyzing, on a processor, a plurality of recorded interactions with a plurality of contact center agents to classify the recorded interactions based on a first plurality of interaction reasons and a plurality interaction resolution statuses; analyzing, on the processor, the classified recorded interactions to compute agent effectiveness of an agent of the plurality of agents, wherein the agent effectiveness corresponds to an interaction reason of the first interaction reasons; forecasting, on the processor, a demand of the contact center agents for a first time period for handling interactions classified with the interaction reason; and generating, on the processor, the agent work schedule for the first time period based on the forecasted demand and the computed agent effectiveness.

Claims

1. A method for generating an agent work schedule, the method comprising:

analyzing, on a processor, a plurality of recorded interactions with a plurality of contact center agents to classify the recorded interactions based on a first plurality of interaction reasons and a plurality interaction resolution statuses;

analyzing, on the processor, the classified recorded interactions to compute agent effectiveness of an agent of the plurality of agents, wherein the agent effectiveness corresponds to an interaction reason of the first interaction reasons;

forecasting, on the processor, a demand of the contact center agents for a first time period for handling interactions classified with the interaction reason; and

generating, on the processor, the agent work schedule for the first time period based on the forecasted demand and the computed agent effectiveness.

2. The method of claim 1, wherein the analyzing, on the processor, the plurality of recorded interactions further comprises determining, on the processor, an interaction handling time, and

wherein the agent effectiveness comprises an average interaction handling time computed from the interaction handling time.

3. The method of claim 2, wherein the agent work schedule is further generated based on an average tare time.

4. The method of claim 1, wherein the analyzing the classified recorded interactions to compute the agent effectiveness of the agent comprises:

identifying, on the processor, from among the plurality of recorded interactions, a subset of recorded interactions in which the agent participated in the recorded interaction and which were classified with the interaction reason;

identifying, on the processor, from among the subset of recorded interactions, a plurality of unresolved interactions in which an interaction resolution status of the interaction resolution statuses associated with the subset of recorded interactions is set as unresolved; and

computing, on the processor, the agent effectiveness with respect to the interaction reason based on a number of unresolved recorded interactions and a number of interactions in the subset of recorded interactions.

5. The method of claim 1, further comprising updating, on the processor, the computed agent effectiveness by analyzing a second plurality of recorded interactions to classify the second plurality of recorded interactions based on a second plurality of interaction reasons and a second plurality of interaction resolution statuses.

6. The method of claim 5, wherein the second interaction reasons comprise at least one new interaction reason different from each of the first interaction reasons.

7. The method of claim 6, wherein the analyzing the classified recorded interactions to compute agent effectiveness of the agent comprises:

identifying, on the processor, from among the plurality of recorded interactions, a subset of recorded interactions in which the agent participated in the recorded interaction and which were classified with the at least one new interaction reason;

identifying, on the processor, from among the subset of recorded interactions, a plurality of unresolved interactions in which an interaction resolution status of the interaction resolution statuses associated with the subset of recorded interactions is set as unresolved; and

computing, on the processor, the agent effectiveness with respect to the at least one new interaction reason based on a number of unresolved recorded interactions and a number of interactions in the subset of recorded interactions.

8. The method of claim 6, further comprising forecasting, on the processor, a demand of the contact center agents for a second time period for handling interactions classified with the new interaction reason, the second time period being different from the first time period.

9. The method of claim 5, wherein the first interaction reasons comprise at least one interaction obsolete interaction reason different from each of the second interaction reasons.

10. The method of claim 9, further comprising forecasting, on the processor, a demand of the contact center agents for a second time period for handling the second interaction reasons without forecasting a demand for handling the at least one obsolete interaction reason, the second time period being different from the first time period.

11. A system comprising:

a processor; and

memory storing instructions that, when executed on the processor, cause the processor to;

analyze a plurality of recorded interactions with a plurality of contact center agents to classify the recorded interactions based on a first plurality of interaction reasons and a plurality interaction resolution statuses;

analyze the classified recorded interactions to compute agent effectiveness of an agent of the plurality of agents, wherein the agent effectiveness corresponds to an interaction reason of the first interaction reasons;

forecast a demand of the contact center agents for a first time period for handling interactions classified with the interaction reason; and

generate the agent work schedule for the first time period based on the forecasted demand and the computed agent effectiveness.

12. The system of claim 11, wherein the memory further stores instructions that, when executed by the processor, cause the processor to determine an interaction handling time, wherein the agent effectiveness comprises an average interaction handling time computed from the interaction handling time.

13. The system of claim 12, wherein the agent work schedule is further generated based on an average tare time.

14. The system of claim 11, wherein the instructions stored in the memory that cause the processor to analyze the classified recorded interactions to compute the agent effectiveness comprise instructions that, when executed by the processor, cause the processor to:

identify, from among the plurality of recorded interactions, a subset of recorded interactions in which the agent participated in the recorded interaction and which were classified with the interaction reason;

identify, from among the subset of recorded interactions, a plurality of unresolved interactions in which an interaction resolution status of the interaction resolution statuses associated with the subset of recorded interactions is set as unresolved; and

compute the agent effectiveness with respect to the interaction reason based on a number of unresolved recorded interactions and a number of interactions in the subset of recorded interactions.

15. The system of claim 11, wherein the memory further stores instructions that, when executed by the processor, cause the processor to update the computed agent effectiveness by analyzing a second plurality of recorded interactions to classify the second plurality of recorded interactions based on a second plurality of interaction reasons and a second plurality of interaction resolution statuses.

16. The system of claim 15, wherein the second interaction reasons comprise at least one new interaction reason different from each of the first interaction reasons.

17. The system of claim 16, wherein the instructions stored in the memory that cause the processor to compute agent effectiveness of the agent comprise instructions that, when executed by the processor, cause the processor to:

identify, from among the plurality of recorded interactions, a subset of recorded interactions in which the agent participated in the recorded interaction and which were classified with the at least one new interaction reason;

identify, from among the subset of recorded interactions, a plurality of unresolved interactions in which an interaction resolution status of the interaction resolution statuses associated with the subset of recorded interactions is set as unresolved; and

compute the agent effectiveness with respect to the at least one new interaction reason based on a number of unresolved recorded interactions and a number of interactions in the subset of recorded interactions.

18. The system of claim 16, wherein the memory further stores instructions that, when executed by the processor, cause the processor to forecast a demand of the contact center agents for a second time period for handling interactions classified with the new interaction reason, the second time period being different from the first time period.

19. The system of claim 15, wherein the first interaction reasons comprise at least one interaction obsolete interaction reason different from each of the second interaction reasons.

20. The system of claim 19, wherein the memory further stores instructions that, when executed by the processor, cause the processor to forecast a demand of the contact center agents for a second time period for handling the second interaction reasons without forecasting a demand for handling the at least one obsolete interaction reason, the second time period being different from the first time period.