WORKFLOW MANAGEMENT IN A GLOBAL SUPPORT ORGANIZATION

• US 20100100412A1
• Filed: 10/20/2008
• Published: 04/22/2010
• Est. Priority Date: 10/20/2008
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Fasterling, Oliver R., Mutnury, Bhyrav M., Cases, Moises
• Granted Patent: US 8,140,441 B2
• Time in Patent Office: Days
• US Class Current: 705/9
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/0633 Workflow analysis
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/016 After-sales

Abstract

Customer support involves multiple levels of support, where customer support personnel at higher levels have more experience and a higher cost associated with their services. A random assignment of support personnel to a problem, at lower levels, can lead to multiple call transfers, a customer being put “on hold”, ineffective resource utilization, and high service costs being billed to customers. Functionality can be implemented to assign a support person to resolve the customer'"'"'s problem based on a multi-dimensional dynamic social network database of resources (e.g., personnel experience, success rate, skill set, social network, etc.) which allows for efficient assignment of support personnel to a problem. Routing a customer call to the most appropriate support person at a given level before determining support personnel at higher levels can ensure optimization in terms of return on investment and resource utilization. Optimally selecting and assigning support personnel can also ensure customer satisfaction.

Claims

1. A method comprising:

determining a problem ticket for a customer, wherein the problem ticket indicates a problem and information about the customer;

searching a set of one or more customer support personnel databases based, at least in part, on the problem, a first customer support level, and the information about the customer, wherein said searching yields a first support person of the first customer support level;

routing the problem ticket to the first support person;

searching the set of one or more customer support personnel databases based, at least in part, on the problem, a second customer support level, and the information about the customer, wherein said searching yields a second support person of the second support level, wherein the second customer support level corresponds to a greater amount of one or more of skills, knowledge, and experience; and

routing the problem ticket to the second support person when the first support person fails to resolve the problem.

2. The method of claim 1, wherein said searching the set of one or more customer support personnel databases based, at least in part, on the problem, the first customer support level, and the information about the customer further comprises also searching a dynamic social network database based, at least in part, on the problem and the information about the customer.

3. The method of claim 2, wherein said searching the dynamic social network database is also based on information about the first support person.

4. The method of claim 1 further comprising searching the set of one or more databases and the dynamic social network database based, at least in part on the problem, the first customer support level, and the information about the customer when the first support person fails to resolve the problem, wherein said searching yields a second support person of the first customer support level.

5. The method of claim 1, wherein the customer support personnel databases comprise any one or more of a personnel experience database, a personnel knowledge and skill set database , a personnel location database, a personnel success rate database, and a personnel availability database.

6. The method of claim 1, wherein information in the dynamic social network database comprises personnel language, interests, one or more collaborating colleagues, number of chat conversations initiated, and number of emails exchanged.

7. A method comprising:

determining a problem ticket for a customer, wherein the problem ticket indicates a problem and information about the customer;

searching a set of one or more customer support personnel databases based, at least in part, on the problem, a first customer support level, and the information about the customer, wherein said searching yields a plurality of support persons of the first customer support level;

searching a dynamic social network database based, at least in part on the information about the customer, the problem, and indications of the plurality of support persons of the first customer support level, wherein said searching yields a first of the plurality of support persons; and

routing the problem ticket to the first of the plurality of support persons.

8. The method of claim 7, further comprising:

determining that the first of the plurality of support persons resolved the problem; and

updating both the dynamic social network database and at least one of the set of customer support personnel databases to reflect the first of the plurality of support persons resolving the problem.

9. The method of claim 8, wherein the determining that the first of the plurality of support persons resolved the problem comprises one or more of detecting that the customer has disconnected a phone call and detecting that the customer has logged off a chat window.

10. The method of claim 7, wherein the first of the plurality of support persons shares, with the customer, any one of a common language, common cultural background, common interests, and common location.

11. One or more machine-readable media having stored therein a program product, which when executed a set of one or more processors causes the set of one or more processors to perform operations that comprise:

determining a problem ticket for a customer, wherein the problem ticket indicates a problem and information about the customer;

searching a set of one or more customer support personnel databases based, at least in part, on the problem, a first customer support level, and the information about the customer, wherein said searching yields a first support person of the first customer support level;

routing the problem ticket to the first support person;

searching the set of one or more customer support personnel databases based, at least in part, on the problem, a second customer support level, and the information about the customer, wherein said searching yields a second support person of the second support level, wherein the second customer support level corresponds to a greater amount of one or more of skills, knowledge, and experience; and

routing the problem ticket to the second support person when the first support person fails to resolve the problem.

12. The machine-readable media of claim 11, wherein said operation of searching the set of one or more customer support personnel databases based, at least in part, on the problem, the first customer support level, and the information about the customer further comprises searching a dynamic social network database based, at least in part, on the problem and the information about the customer.

13. The machine-readable media of claim 12, wherein said operation of searching the dynamic social network database is also based on information about the first support person.

14. The machine-readable media of claim 11, wherein the operations further comprise searching the set of one or more databases and the dynamic social network database based, at least in part on the problem, the first customer support level, and the information about the customer when the first support person fails to resolve the problem, wherein said searching yields a second support person of the first customer support level.

15. The machine-readable media of claim 11, wherein the customer support personnel databases comprise any one or more of a personnel experience database, a personnel knowledge and skill set database, a personnel location database, a personnel success rate database, and a personnel availability database.

16. The machine-readable media of claim 11, wherein information in the dynamic social network database comprises personnel language, interests, one or more collaborating colleagues, number of chat conversations initiated, and number of emails exchanged.

17. One or more machine-readable media, wherein the operations comprise:

determining a problem ticket for a customer, wherein the problem ticket indicates a problem and information about the customer;

searching a set of one or more customer support personnel databases based, at least in part, on the problem, a first customer support level, and the information about the customer, wherein said searching yields a plurality of support persons of the first customer support level;

searching a dynamic social network database based, at least in part on the information about the customer, the problem, and indications of the plurality of support persons of the first customer support level, wherein said searching yields a first of the plurality of support persons; and

routing the problem ticket to the first of the plurality of support persons.

18. The machine-readable media of claim 17, wherein the operations also comprise:

determining that the first of the plurality of support persons resolved the problem; and

updating both the dynamic social network database and at least one of the set of customer support personnel databases to reflect the first of the plurality of support persons resolving the problem.

19. The machine-readable media of claim 18, wherein said operation of determining that the first of the plurality of support persons resolved the problem comprises one or more of detecting that the customer has disconnected a phone call and detecting that the customer has logged off a chat window.

20. The machine-readable media of claim 17, wherein the first of the plurality of support persons shares, with the customer, any one of a common language, common cultural background, common interests, and common location.

21. An apparatus comprising:

a set of one or more processors;

a memory unit coupled with the set of one or more processors; and

an automated resource selection and allocation engine operable to;

determine a problem ticket for a customer, wherein the problem ticket indicates a problem and information about the customer;

search a set of one or more customer support personnel databases based, at least in part, on the problem, a first customer support level, and the information about the customer, wherein the search yields a first support person of the first customer support level;

route the problem ticket to the first support person;

search the set of one or more customer support personnel databases based, at least in part, on the problem, a second customer support level, and the information about the customer, wherein the search yields a second support person of the second support level, wherein the second customer support level corresponds to a greater amount of one or more of skills, knowledge, and experience; and

route the problem ticket to the second support person when the first support person fails to resolve the problem.

22. The apparatus of claim 21, wherein the automated resource selection and allocation unit being operable to search the set of one or more customer support personnel databases based, at least in part, on the problem, the first customer support level, and the information about the customer further comprises the automated resource selection and allocation engine being operable to search a dynamic social network database based, at least in part, on the problem and the information about the customer.

23. The apparatus of claim 21, further comprises the automated resource selection and allocation engine being operable to search the set of one or more databases and the dynamic social network database based, at least in part on the problem, the first customer support level, and the information about the customer when the first support person fails to resolve the problem, wherein the search yields a second support person of the first customer support level.

24. The apparatus of claim 21, further comprising:

a data collection and analysis engine operable to dynamically update a dynamic social network database based on any one or more of interactions between support personnel, the customers, interactions between the customers and the support personnel, and problem resolution.

25. The apparatus of claim 21, wherein the automated resource selection and allocation engine comprises one or more machine-readable media.