Granted Patent B2

US 12,271,906 · App. 18/145,081 · Granted Apr 8, 2025

Inventors: Ming Qian (Allston, MA); Anne-Marie Mcreynolds (San Jose, CA); Christopher O'Bryon Hill (Bellevue, WA)

Assignee: Dell Products L.P.

G06Q30/015G06Q10/063112G06Q10/06398

Abstract

Claims (95)

1. A method for managing customer-encountered issues using service agents, the method being performed by a response management system (RMS) embodied by a data processing system and comprising:

obtaining, by the data processing system, the customer encountered issues, wherein the customer-encountered issues are stored in a storage of the data processing system and a processing of each of the customer-encountered issues requires consumption of a first quantity of limited computing resources of the processor and the storage, and wherein a first number of the customer-encountered issues is resolved per a unit of time based on the first quantity;

performing, by a processor of the data processing system performing the method, a multiphase optimization procedure to reduce the required consumption from the first quantity of limited computing resources to a second quantity lower than the first quantity such that a second number of the customer-encountered issues is resolved per the unit of time based on the second quantity wherein the second number is larger than the first number, the multiphase optimization procedure comprising:

identifying, as a first phase of the multiphase optimization procedure, a portion of the service agents that are qualified to handle a customer-encountered issue of the customer-encountered issues;

ranking, during a second phase of the multiphase optimization procedure, the service agents of the portion of the service agents based on efficiency estimates for resolving the customer-encountered issue by the service agents to obtain a first ranking;

further ranking, during the second phase of the multiphase optimization procedure, the service agents of the portion of the service agents based on alignment between the customer-encountered issue and previously resolved customer-encountered issues to obtain a second ranking, wherein all rankings performed during the second phase are performed independently of a scheduling availability of the portion of the service agents; and

selecting, during a third phase of the multiphase optimization procedure, a service agent of the service agents to remediate the customer-encountered issue based on the first ranking and the second ranking, wherein the scheduling availability of the portion of the service agents is assessed for the first time during the third phase; and

assigning, by the processor, the selected service agent to work and resolve the customer-encountered issue.

2. The method of claim 1 , wherein the portion of the service agents is identified based on a cognitive load estimate for resolving the customer-encountered issue, a skill estimate for resolving the customer-encountered issue, and skill ratings for the portion of the service agents.

3. The method of claim 2 , wherein ranking the service agents of the portion of the service agents based on the efficiency estimates for resolving the customer-encountered issue comprises:

identifying a type of the customer-encountered issue;

for each service agent of the portion of the service, identify an average time to resolution of previously resolved customer-encountered issues of the type of the customer-encountered issue and that were resolved by each service agent;

ordering the service agents of the portion of the service agents based on the average time to resolution associated with each of the service agents of the portion of the service agents to obtain the first ranking.

4. The method of claim 3 , wherein ranking the service agents of the portion of the service agents based on the alignment between the customer-encountered issue and other customer-encountered issues resolved by the service agents to obtain a second ranking comprises:

identifying attributes of the customer-encountered issue;

for each service agent of the portion of the service:

identify attributes of the previously resolved customer-encountered issues that were resolved by each service agent, and

obtaining a metric indicating a level of the alignment between the attributes of the customer-encountered issue and the attributes of the previously resolved customer-encountered issues that were resolved by each service agent;

ordering the service agents of the portion of the service agents based on the metric to obtain the second ranking.

5. The method of claim 4 , wherein selecting the service agent of the service agents to remediate the customer-encountered issue based on the first ranking and the second ranking comprises:

identifying a sub-portion of the portion of the service agents based on the first ranking and the second ranking; and

identifying a service agent of the sub-portion of the portion of the service agents that has available cognitive bandwidth to resolve the customer-encountered issue within a time to resolution goal, the available cognitive bandwidth being based on the scheduling availability of the portion of the service agents.

6. The method of claim 5 , wherein the time to resolution goal is based, at least in part, a context switching time for the customer-encountered issue.

7. The method of claim 4 , wherein obtaining the metric indicating the level of the alignment comprises:

identifying, for the customer-encountered issue, at least one attribute of the attributes from a group consisting of:

a product grouping;

a product reporting group;

a case type;

a case error code;

a case microcode;

a software version;

a severity level;

a top level case category; and

a case detailed category.

8. The method of claim 7 , wherein obtaining the metric indicating the level of the alignment further comprises:

comparing the identified at least one of the attributes to corresponding attributes of the previously resolved customer-encountered issues on a per attribute basis to identify aligned attributes and unaligned attributes; and

calculating the metric based on the aligned attributes and unaligned attributes.

9. A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor of a data processing system configured as a response management system (RMS), cause the processor to perform operations for managing customer-encountered issues using service agents, the operations comprising:

obtaining, by the data processing system, the customer encountered issues, wherein the customer-encountered issues are stored in a storage of the data processing system and a processing of each of the customer-encountered issues requires consumption of a first quantity of limited computing resources of the processor and the storage, and wherein a first number of the customer-encountered issues is resolved per a unit of time based on the first quantity;

performing, by the processor, a multiphase optimization procedure to reduce the required consumption from the first quantity of limited computing resources to a second quantity lower than the first quantity such that a second number of the customer-encountered issues is resolved per the unit of time based on the second quantity wherein the second number is larger than the first number, the multiphase optimization procedure comprising:

identifying, as a first phase of the multiphase optimization procedure, a portion of the service agents that are qualified to handle a customer-encountered issue of the customer-encountered issues;

ranking, during a second phase of the multiphase optimization procedure, the service agents of the portion of the service agents based on efficiency estimates for resolving the customer-encountered issue by the service agents to obtain a first ranking;

further ranking, during the second phase of the multiphase optimization procedure, the service agents of the portion of the service agents based on alignment between the customer-encountered issue and previously resolved customer-encountered issues to obtain a second ranking, wherein all rankings performed during the second phase are performed independently of a scheduling availability of the portion of the service agents; and

selecting, during a third phase of the multiphase optimization procedure, a service agent of the service agents to remediate the customer-encountered issue based on the first ranking and the second ranking, wherein the scheduling availability of the portion of the service agents is assessed for the first time during the third phase; and

assigning, by the processor, the selected service agent to work and resolve the customer- encountered issue.

10. The non-transitory machine-readable medium of claim 9 , wherein the portion of the service agents is identified based on a cognitive load estimate for resolving the customer-encountered issue, a skill estimate for resolving the customer-encountered issue, and skill ratings for the portion of the service agents.

11. The non-transitory machine-readable medium of claim 10 , wherein ranking the service agents of the portion of the service agents based on the efficiency estimates for resolving the customer-encountered issue comprises:

identifying a type of the customer-encountered issue;

for each service agent of the portion of the service, identify an average time to resolution of previously resolved customer-encountered issues of the type of the customer-encountered issue and that were resolved by each service agent;

ordering the service agents of the portion of the service agents based on the average time to resolution associated with each of the service agents of the portion of the service agents to obtain the first ranking.

12. The non-transitory machine-readable medium of claim 11 , wherein ranking the service agents of the portion of the service agents based on the alignment between the customer-encountered issue and other customer-encountered issues resolved by the service agents to obtain a second ranking comprises:

identifying attributes of the customer-encountered issue;

for each service agent of the portion of the service:

identify attributes of the previously resolved customer-encountered issues that were resolved by each service agent, and

obtaining a metric indicating a level of the alignment between the attributes of the customer-encountered issue and the attributes of the previously resolved customer-encountered issues that were resolved by each service agent;

ordering the service agents of the portion of the service agents based on the metric to obtain the second ranking.

13. The non-transitory machine-readable medium of claim 12 , wherein selecting the service agent of the service agents to remediate the customer-encountered issue based on the first ranking and the second ranking comprises:

identifying a sub-portion of the portion of the service agents based on the first ranking and the second ranking; and

identifying a service agent of the sub-portion of the portion of the service agents that has available cognitive bandwidth to resolve the customer-encountered issue within a time to resolution goal, the available cognitive bandwidth being based on the scheduling availability of the portion of the service agents.

14. The non-transitory machine-readable medium of claim 13 , wherein the time to resolution goal is based, at least in part, a context switching time for the customer-encountered issue.

15. The non-transitory machine-readable medium of claim 12 , wherein obtaining the metric indicating the level of the alignment comprises:

identifying, for the customer-encountered issue, at least one attribute of the attributes from a group consisting of:

a product grouping;

a product reporting group;

a case type;

a case error code;

a case microcode;

a software version;

a severity level;

a top level case category; and

a case detailed category.

16. The non-transitory machine-readable medium of claim 15 , wherein obtaining the metric indicating the level of the alignment further comprises:

comparing the identified at least one of the attributes to corresponding attributes of the previously resolved customer-encountered issues on a per attribute basis to identify aligned attributes and unaligned attributes; and

calculating the metric based on the aligned attributes and unaligned attributes.

17. A data processing system configured as a response management system (RMS), comprising:

a processor; and

a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations for managing customer-encountered issues using service agents, the operations comprising:

obtaining, by the data processing system, the customer encountered issues, wherein the customer-encountered issues are stored in a storage of the data processing system and a processing of each of the customer-encountered issues requires consumption of a first quantity of limited computing resources of the processor and the storage, and wherein a first number of the customer-encountered issues is resolved per a unit of time based on the first quantity;

performing, by the processor, a multiphase optimization procedure to reduce the required consumption from the first quantity of limited computing resources to a second quantity lower than the first quantity such that a second number of the customer-encountered issues is resolved per the unit of time based on the second quantity wherein the second number is larger than the first number, the multiphase optimization procedure comprising:

identifying, as a first phase of the multiphase optimization procedure, a portion of the service agents that are qualified to handle a customer-encountered issue of the customer-encountered issues;

ranking, during a second phase of the multiphase optimization procedure, the service agents of the portion of the service agents based on efficiency estimates for resolving the customer-encountered issue by the service agents to obtain a first ranking;

further ranking, during the second phase of the multiphase optimization procedure, the service agents of the portion of the service agents based on alignment between the customer-encountered issue and previously resolved customer-encountered issues to obtain a second ranking, wherein all rankings performed during the second phase are performed independently of a scheduling availability of the portion of the service agents; and

selecting, during a third phase of the multiphase optimization procedure, a service agent of the service agents to remediate the customer-encountered issue based on the first ranking and the second ranking, wherein the scheduling availability of the portion of the service agents is assessed for the first time during the third phase; and

assigning, by the processor, the selected service agent to work and resolve the customer-encountered issue.

18. The data processing system of claim 17 , wherein the portion of the service agents is identified based on a cognitive load estimate for resolving the customer-encountered issue, a skill estimate for resolving the customer-encountered issue, and skill ratings for the portion of the service agents.

19. The data processing system of claim 18 , wherein ranking the service agents of the portion of the service agents based on the efficiency estimates for resolving the customer-encountered issue comprises:

identifying a type of the customer-encountered issue;

for each service agent of the portion of the service, identify an average time to resolution of previously resolved customer-encountered issues of the type of the customer-encountered issue and that were resolved by each service agent;

ordering the service agents of the portion of the service agents based on the average time to resolution associated with each of the service agents of the portion of the service agents to obtain the first ranking.

20. The data processing system of claim 19 , wherein ranking the service agents of the portion of the service agents based on the alignment between the customer-encountered issue and other customer-encountered issues resolved by the service agents to obtain a second ranking comprises:

identifying attributes of the customer-encountered issue;

for each service agent of the portion of the service:

identify attributes of the previously resolved customer-encountered issues that were resolved by each service agent, and

obtaining a metric indicating a level of the alignment between the attributes of the customer-encountered issue and the attributes of the previously resolved customer-encountered issues that were resolved by each service agent;

ordering the service agents of the portion of the service agents based on the metric to obtain the second ranking.

Assignments (1)

Continuity (1)

References Cited (57)