Proactive support process using case activity rate

• US 20060241957A1
• Filed: 04/22/2005
• Published: 10/26/2006
• Est. Priority Date: 04/22/2005
• Status: Abandoned Application

• Current Assignee: Dell Products LP (Dell Technologies Inc.)
• Original Assignee: Dell Products LP (Dell Technologies Inc.)
• Inventors: Boswell, Michael
• Application Number:
  US11/112,945
• Publication Number:
  US 20060241957A1
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change

Abstract

A system and method are presented for analyzing service case data in order to optimize the amount of physical material and human resources needed to maintain operation of complex systems, such as information handling systems. A first set of data related to the one or more customer'"'"'s experience with one or more models of information handling systems are recorded. In addition, a second set of data related to one or more models of information handling systems (regardless of customer) are also recorded. A CAR index is used to normalize the volume of service call cases that have been addressed based upon the population of systems that could responsible for any particular case. Use of the CAR index allows for a more informative comparison of support cases volume across time, customer, product lines and specific systems than previous figures of merit.

Claims

1. An information handling system capable of executing one or more instructions, the instructions comprising:

gathering actual data about an index type;

providing predicted data about the index type;

comparing the actual data with the predicted data;

if the difference between the actual data and the predicted data exceeds a threshold, then determining the root cause of the difference and develop a support plan to address the root cause.

2. The system of claim 1, wherein the index type is customer case type.

3. The system of claim 1, wherein the actual data is customer case data.

4. The system of claim 1, wherein the predicted data is PCAR data.

5. The system of claim 1, wherein the index type is a system case type.

6. The system of claim 1, wherein the actual data is system case data.

7. The system of claim 1, wherein the predicted data is lifetime CAR data.

8. The system of claim 1, wherein the index type is a product case type.

9. The system of claim 1, wherein the index type is contract case data.

10. A method of optimizing support resources comprising:

gathering actual data about an index type;

providing predicted data about the index type;

comparing the actual data with the predicted data;

if the difference between the actual data and the predicted data exceeds a threshold, then determining the root cause of the difference and develop a support plan to address the root cause.

11. The method of claim 10, wherein the index type is customer case type.

12. The method of claim 10, wherein the actual data is customer case data.

13. The method of claim 10, wherein the predicted data is PCAR data.

14. The method of claim 10, wherein the index type is a system case type.

15. The method of claim 10, wherein the actual data is system case data.

16. The method of claim 10, wherein the predicted data is lifetime CAR data.

17. The method of claim 10, wherein the index type is a product case type.

18. The method of claim 10, wherein the index type is contract case data.

19. A computer-readable medium containing a data structure comprising:

information for gathering actual data about an index type;

information for providing predicted data about the index type;

information for comparing the actual data with the predicted data;

information for determining if the difference between the actual data and the predicted data exceeds a threshold, then determining the root cause of the difference and develop a support plan to address the root cause.