System and method for facilitating the implementation of changes to the configuration of resources in an enterprise

• US 8,239,498 B2
• Filed: 10/28/2005
• Issued: 08/07/2012
• Est. Priority Date: 10/28/2005
• Status: Active Grant

• Current Assignee: Bank of America Corp.
• Original Assignee: Bank of America Corp.
• Inventors: Kephart, Aaron D., Gatrell, Carol, Kilpatrick, Brian R., Kirkland, Wallace A., Maloney, Robert J.
• Primary Examiner(s): Ibrahim, Mohamed
• Application Number:
  US11/163,738
• Publication Number:
  US 20070100712A1
• Time in Patent Office: 2,475 Days
• Field of Search: 709/217, 709/218, 709/219, 709/220, 709/221, 709/222
• US Class Current: 709/220
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/0875 Itemisation or classification of parts, supplies or services, e.g. bill of materials

Abstract

System and method for facilitating the implementation of changes to the configuration of resources in an enterprise. Embodiments of the present invention facilitate the use of historical information about an enterprise'"'"'s IT configuration to evaluate the risk and impact of proposed changes. Risk can be evaluated using a success history for an organization within the enterprise that is responsible for the proposed change, or by applying a neural network to the historical data to detect recognizable patterns in the historical data. A risk evaluation can take into account sensitivity of the change to dates assigned on a change calendar, based on sensitivity dates gathered from the historical data. Historical data can be maintained and provided by a configuration database.

Claims

1. A method of evaluating a proposed change to a configuration of information technology resources in an enterprise, the method comprising:

obtaining information about the proposed change, wherein the proposed change can be a past configuration, a current configuration, or a new configuration;

searching, through the use of a processing device, for historical data about the information technology resources in the enterprise pertaining to at least one past configuration of the information technology resources in the enterprise, wherein the at least one past configuration is related to the proposed change, and wherein the historical data comprises patterns that correlate to configuration changes that were a success or a failure;

searching, through the use of the processing device, for current data about the information technology resources in the enterprise pertaining to at least one current configuration of the information technology resources in the enterprise, wherein the at least one current configuration is related to the proposed change, and wherein the current data comprises configuration changes that are currently working;

searching, through the use of the processing device, for pending data about the information technology resources in the enterprise pertaining to at least one pending configuration of the information technology resources in the enterprise, wherein the at least one pending configuration is related to the proposed change; and

wherein the pending data comprises configuration changes that are pending implementation;

identifying, through the use of the processing device, a date on which the proposed change may be implemented;

accessing, through the use of the processing device, change calendar data pertaining to sensitivity dates for implementing configuration changes, wherein the sensitivity dates indicate dates on which implementing configuration changes may decrease or increase a successful implementation of the configuration changes;

evaluating, through the use of the processing device, a likelihood of success of the proposed change using a neural network for analyzing the information about the proposed change, the historical data, the current data, the pending data, the date on which the proposed change may be implemented, and the change calendar data, wherein the neural network detects recognizable patterns in the likelihood of success of the proposed change; and

producing, through the use of the processing device, an indication of risk associated with the proposed change to the configuration of the information technology resources in the enterprise based on the likelihood of success.

2. The method of claim 1 wherein the indication of risk produced by the neural network is a probability of success or failure of the configuration change.

3. The method of claim 2, further comprising:

storing configuration change data about the proposed change, wherein the configuration change data is the configuration change being implemented, the date of the configuration change being implemented, and the pass or failure of the configuration change;

training the neural network with the configuration change data to improve the effectiveness of the neural network in evaluating the likelihood of success of future configuration changes.

4. The method of claim 3 wherein the historical data is contained in at least one of a configuration database and a change database.

5. The method of claim 4 wherein the at least one of the configuration database and the change database comprises a plurality of configuration items.

6. The method of claim 5 wherein at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a midrange computer CI, a midrange partition CI, a mainframe computer CI, a logical partition (LPAR) CI, a software CI, a software component CI, and combinations of the foregoing.

7. The method of claim 2 wherein the historical data is contained in at least one of a configuration database and a change database.

8. The method of claim 7 wherein the at least one of the configuration database and the change database comprises a plurality of configuration items.

9. The method of claim 8 wherein at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a midrange computer CI, a midrange partition CI, a mainframe computer CI, a logical partition (LPAR) CI, a software CI, a software component CI, and combinations of the foregoing.

10. The method of claim 8 wherein at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a service CI, a delivery channel CI, an application CI, a sub-system CI, a hardware CI, a physical location CI, and combinations of the foregoing.

11. The method of claim 1 wherein the evaluating of the likelihood of success further comprises accessing a success history within the enterprise.

12. The method of claim 11 wherein the historical data is contained in at least one of a configuration database and a change database.

13. The method of claim 12 wherein the at least one of the configuration database and the change database comprises a plurality of configuration items.

14. The method of claim 13 wherein at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a midrange computer CI, a midrange partition CI, a mainframe computer CI, a logical partition (LPAR) CI, a software CI, a software component CI, and combinations of the foregoing.

15. The method of claim 13 wherein at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a service CI, a delivery channel CI, an application CI, a sub-system CI, a hardware CI, a physical location CI, and combinations of the foregoing.

16. The method of claim 11 wherein the producing of the indication of risk further comprises:

assigning relative weights to a success factor based on the success history and a plurality of risk factors to produce a plurality of factors; and

combining the plurality of factors to produce a risk value.

17. The method of claim 1 wherein the historical data is contained in at least one of a configuration database and a change database.

18. The method of claim 17 wherein the at least one of the configuration database and the change database comprises a plurality of configuration items.

19. The method of claim 18 wherein at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a midrange computer CI, a midrange partition CI, a mainframe computer CI, a logical partition (LPAR) CI, a software CI, a software component CI, and combinations of the foregoing.

20. The method of claim 18 wherein at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a service CI, a delivery channel CI, an application CI, a sub-system CI, a hardware CI, a physical location CI, and combinations of the foregoing.

21. The method of claim 1 further comprising:

evaluating an impact for the proposed change to the configuration of the information technology resources; and

producing an indication of the impact of the proposed change.

22. The method of claim 1 further comprising:

approving the proposed change if the indication of risk associated with the proposed change meets a percentage threshold risk set by a user.

23. A computer program product for evaluating a proposed change to a configuration of information technology resources in an enterprise, the computer program product comprising a non-transitory computer-readable medium including computer program code, the computer program code further comprising:

instructions for obtaining information about the proposed change, wherein the proposed change can be a past configuration, a current configuration, or a new configuration;

instructions for searching for historical data about the information technology resources in the enterprise pertaining to at least one past change to the configuration of the information technology resources in the enterprise, wherein the at least one past configuration is related to the proposed change, and wherein the historical data comprises patterns that correlate to configuration changes that were a success or a failure;

instructions for searching for current data about the information technology resources in the enterprise pertaining to at least one current configuration of the information technology resources in the enterprise, wherein the at least one current configuration is related to the proposed change, and wherein the current data comprises configuration changes that are currently working;

instructions for searching for pending data about the information technology resources in the enterprise pertaining to at least one pending configuration of the information technology resources in the enterprise, wherein the at least one pending configuration is related to the proposed change; and

wherein the pending data comprises configuration changes that are pending implementation;

instructions for identifying a date on which the proposed change may be implemented;

instructions for accessing change calendar data pertaining to sensitivity dates for implementing configuration changes, wherein the sensitivity dates indicate dates on which implementing configuration changes may decrease or increase a successful implementation of the configuration change;

instructions for evaluating a likelihood of success of the proposed change using a neural network for analyzing the information about the proposed change, the historical data, the current data, the pending data, the date on which the proposed change may be implemented, and the change calendar data; and

instructions for producing an indication of risk associated with the proposed change to the configuration of the information technology resources in the enterprise based on the likelihood of success.

24. The computer program product of claim 23 wherein the indication of impact produced by the neural network is a probability of success or failure of the configuration change.

25. The computer program product of claim 24 further comprising:

instructions for storing configuration change data about the proposed change, wherein the configuration change data is the configuration change being implemented, the date of the configuration change being implemented, and the pass or failure of the configuration change;

instructions for training the neural network with the configuration change data to improve the effectiveness of the neural network in evaluating the likelihood of success of future configuration changes.

26. The computer program product of claim 25 wherein the historical data is related to at least one configuration item (CI) of a plurality of configuration items that can be stored in at least one of a configuration database and a change database.

27. The computer program product of claim 26 wherein the at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a midrange computer CI, a midrange partition CI, a mainframe computer CI, a logical partition (LPAR) CI, a software CI, a software component CI, and combinations of the foregoing.

28. The computer program product of claim 24 wherein the historical data is related to at least one configuration item (CI) of a plurality of configuration items that can be stored in at least one of a configuration database and a change database.

29. The computer program product of claim 28 wherein the at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a midrange computer CI, a midrange partition CI, a mainframe computer CI, a logical partition (LPAR) CI, a software CI, a software component CI, and combinations of the foregoing.

30. The computer program product of claim 28 wherein the at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a service CI, a delivery channel CI, an application CI, a sub-system CI, a hardware CI, a physical location CI, and combinations of the foregoing.

31. The computer program product of claim 23 wherein the computer program code further comprises instructions for accessing a success history within the enterprise.

32. The computer program product of claim 31 wherein the historical data is related to at least one configuration item (CI) of a plurality of configuration items that can be stored in at least one of a configuration database and a change database.

33. The computer program product of claim 32 wherein the at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a midrange computer CI, a midrange partition CI, a mainframe computer CI, a logical partition (LPAR) CI, a software CI, a software component CI, and combinations of the foregoing.

34. The computer program product of claim 32 wherein the at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a service CI, a delivery channel CI, an application CI, a sub-system CI, a hardware CI, a physical location CI, and combinations of the foregoing.

35. The computer program product of claim 31 wherein the computer program code further comprises:

instructions for assigning relative weights to a success factor based on the success history and a plurality of risk factors to produce a plurality of factors; and

instructions for combining the plurality of factors to produce a risk value.

36. The computer program product of claim 23 wherein the historical data is related to at least one configuration item (CI) of a plurality of configuration items that can be stored in at least one of a configuration database and a change database.

37. The computer program product of claim 36 wherein the at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a midrange computer CI, a midrange partition CI, a mainframe computer CI, a logical partition (LPAR) CI, a software CI, a software component CI, and combinations of the foregoing.

38. The computer program product of claim 36 wherein the at least one configuration item (CI) of the plurality of configuration items is selected from a group consisting of a service CI, a delivery channel CI, an application CI, a sub-system CI, a hardware CI, a physical location CI, and combinations of the foregoing.

39. The computer program product of claim 23 wherein the computer program code further comprises:

instructions for evaluating an impact for the proposed change to the configuration of the information technology resources; and

instructions for producing an indication of the impact of the proposed change.

40. The computer program product of claim 23 wherein the computer program code further comprises:

instructions for approving the proposed change if the indication of risk associated with the proposed change meets a percentage threshold risk set by a user.

41. A system for evaluating a proposed change to a configuration of information technology resources in an enterprise, the system comprising:

a memory device having computer program instructions store thereon; and

a processing device operatively coupled to the memory device, wherein the processing device is configured to execute the computer program instructions for;

obtaining information about the proposed change, wherein the proposed change can be a past configuration, a current configuration, or a new configuration;

searching for historical data about the information technology resources in the enterprise pertaining to at least one past configuration of the information technology resources, wherein the at least one past configuration is related to the proposed change, and wherein the historical data comprises patterns that correlate to configuration changes that were a success or a failure;

searching for current data about the information technology resources in the enterprise pertaining to at least one current configuration of the information technology resources in the enterprise, wherein the at least one current configuration is related to the proposed change, and wherein the current data comprises configuration changes that are currently working;

searching for pending data about the information technology resources in the enterprise pertaining to at least one pending configuration of the information technology resources in the enterprise, wherein the at least one pending configuration is related to the proposed change; and

wherein the pending data comprises configuration changes that are pending implementation;

identifying a date on which the proposed change may be implemented;

accessing change calendar data pertaining to sensitivity dates for implementing configuration changes, wherein the sensitivity dates indicate dates on which implementing configuration changes may decrease or increase a successful implementation of the configuration changes;

evaluating a likelihood of success of the proposed change using a neural network for analyzing the information about the proposed change, the historical data, the current data, the pending data, the date on which the proposed change may be implemented, and the change calendar data, wherein the neural network detects recognizable patterns in the likelihood of success of the proposed change; and

producing based on the likelihood of success an indication of risk associated with the proposed change to the configuration of the information technology resources in the enterprise based on the likelihood of success.

42. The system of claim 41 wherein the processing device is further configured for producing an indication of an impact of the proposed change.

43. The system of claim 42 wherein the processing device is further configured for accessing a success history for the enterprise.

44. The system of claim 42 further comprising at least one of a configuration database and a change database.

45. The system of claim 41 wherein the processing device is further configured for accessing a success history within the enterprise.

46. The system of claim 45 further comprising at least one of a configuration database and a change database.

47. The system of claim 41, wherein the indication of risk produced by the neural network is a probability of success or failure of the configuration change.

48. The system of claim 47 wherein the processing device is further configured for:

storing configuration change data about the proposed change, wherein the configuration change data is the configuration change being implemented, the date of the configuration change being implemented, and the pass or failure of the configuration change;

training the neural network with the configuration change data to improve the effectiveness of the neural network in evaluating the likelihood of success of future configuration changes.

49. The system of claim 41 further comprising at least one of a configuration database and a change database.

50. The system of claim 41 wherein the processing device is further configured for approving the proposed change if the indication of risk associated with the proposed change meets a percentage threshold risk set by a user.