System and method for analyzing processes

• US 7,467,145 B1
• Filed: 04/15/2005
• Issued: 12/16/2008
• Est. Priority Date: 04/15/2005
• Status: Active Grant

• Current Assignee: Micro Focus LLC (Open Text Corporation)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Casati, Fabio, Shan, Ming-Chien, Castellanos, Maria Guadalupe
• Primary Examiner(s): MIZRAHI, DIANE D
• Application Number:
  US11/107,285
• Time in Patent Office: 1,341 Days
• Field of Search: 707 1- 10, 707100-103 Z, 707200-206, 707/103.X, 707/103.Y, 707/104.1, 709/239, 709/240, 709/216, 709/217, 709/218, 709/238, 705/7
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: Y10S 707/99944 Object-oriented database structure

Abstract

Embodiments of the present invention relate to a system and method for analyzing processes. Specifically, embodiments of the present invention relate to identifying a node of a process that is potentially affected by an affected resource using information relating to a link between the node and the affected resource, the process having a related process instance that has an execution stage, and applying an interval prediction model corresponding to the execution stage of the process instance and the node, the interval prediction model determining a probability that the process instance will reach the node before a designated occurrence.

Claims

1. A method for analyzing processes using a processor, comprising:

identifying a node of a process that is potentially affected by an affected resource using information relating to a link between the node and the affected resource, the process having a related process instance that has an execution stage; and

applying an interval prediction model corresponding to the execution stage of the process instance and the node, the interval prediction model determining a probability that the process instance will reach the node within an interval of time occurring before a designated occurrence and adjusting the process being analyzed based on the probability.

2. The method of claim 1, further comprising applying an outcome prediction model corresponding to the execution stage of the process instance and the node, the outcome prediction model determining a probability that the node will be executed by the process instance.

3. The method of claim 2, further comprising predicting that the process instance will be impacted if the outcome prediction model and the interval prediction model indicate that the process instance will execute the node before the resource is restored with a confidence level above a threshold value.

4. The method of claim 2, wherein applying the outcome prediction model includes applying a classification model.

5. The method of claim 1, wherein applying the interval prediction model includes applying a classification model to determine whether the process instance will reach the node within a defined period.

6. The method of claim 1, wherein applying the interval prediction model includes utilizing time series forecasting to determine whether the process instance will reach the node within a defined period.

7. The method of claim 1, further comprising installing an information technology resource monitoring system in a managed process to facilitate identification of the affected resource.

8. The method of claim 1, further comprising:

identifying the process instance as a likely impacted instance; and

adjusting the process instance to avoid the likely impact.

9. The method of claim 1, further comprising installing probes to monitor a status of a set of resources.

10. The method of claim 1, wherein the interval prediction model predicts a time interval for the process instance to reach the node.

11. The method of claim 10, further comprising comparing the time interval for the process instance to reach the node to a time interval statistic to restore the affected resource.

12. A method for analyzing processes using a processor, comprising:

identifying an at-risk instance using an established forward path through a node being affected by a status change of a system resource;

determining whether the at-risk instance will execute the node with a confidence level above a certain threshold value; and

determining and providing an indication to a user as to whether the at-risk instance will reach the node prior to returning the status to an original condition.

13. The method of claim 12, wherein determining whether the at-risk instance will execute the node comprises using an outcome prediction model.

14. The method of claim 12, wherein determining whether the at-risk instance will reach the node comprises using an interval prediction model.

15. The method of claim 14, wherein the interval prediction model includes time series forecasting to determine whether the at-risk instance will reach the node within a defined period.

16. The method of claim 14, wherein the interval prediction model predicts a time for the at-risk instances to reach the node.

17. The method of claim 16, further comprising comparing the time for the at-risk instance to reach the node to a restoration time interval statistic.

18. The method of claim 12, further comprising predicting that the at-risk instance will be impacted when an outcome prediction model used to determine whether the at-risk instance will execute the node and an interval prediction model used to determine whether the at-risk instance will reach the node indicate that the at-risk instance will be affected with a confidence level above a threshold value.

19. The method of claim 12, further comprising identifying a blocked instance that is being impacted by the status change of the system resource using an established relationship between the blocked instance and the system resource.

20. The method of claim 12, further comprising:

identifying the at-risk instance as an impacted instance; and

adjusting the process to accommodate the impacted instance.

21. A system for analyzing processes, comprising:

a processor-based identification module adapted to identify a node of a process that is potentially affected by an affected resource using information relating to a link between the node and the affected resource, the process having a related process instance that has an execution stage;

a processor-based outcome prediction model corresponding to the execution stage of the process instance and the node, the processor-based outcome prediction model adapted to determine a probability that the node will be executed by the process instance; and

a processor-based interval prediction model corresponding to the execution stage of the process instance and the node, the processor-based interval prediction model adapted to determine a probability that the process instance will reach the node within an interval of time occurring before a designated occurrence and provide an indication of the probability to a user.

22. The system of claim 21, wherein the processor-based interval prediction model is adapted to predict a time interval for the process instance to reach the node.

23. The system of claim 21, further comprising a processor-based comparison module adapted to compare the time interval for the process instance to reach the node to a time interval statistic to restore the affected resource.

24. The system of claim 21, further comprising a processor-based impact module adapted to develop a prediction that the process instance will be impacted when the processor-based outcome prediction model and the processor-based interval prediction model indicate that the process instance will be affected with a confidence level above a threshold value.

25. The system of claim 21, wherein the processor-based interval prediction model includes a classification model.

26. Application instructions that when executed by a computer comprising a processor, comprise:

instructions adapted to identify a node of a process that is potentially affected by an affected resource using information relating to a link between the node and the affected resource, the process having a related process instance that has an execution stage;

instructions adapted to utilize an outcome prediction model corresponding to the execution stage of the process instance and the node, the outcome prediction model adapted to determine a probability that the node will be executed by the process instance; and

instructions adapted to utilize an interval prediction model corresponding to the execution stage of the process instance and the node, the interval prediction model adapted to determine a probability that the process instance will reach the node in an interval of time occurring before a designated occurrence.

27. The application instructions of claim 26, further comprising instructions adapted to compare the time interval for the process instance to reach the node to a time interval statistic to restore the affected resource.

28. The application instructions of claim 26, further comprising instructions adapted to develop a prediction that the process instance will be impacted when the outcome prediction model and the interval prediction model indicate that the process instance will be affected with a confidence level above a threshold value.

29. A system for analyzing processes, comprising:

processor-based means for identifying a node of a process that is potentially affected by an affected resource using information relating to a link between the node and the affected resource, the process having a related process instance that has an execution stage;

processor-based means for applying an outcome prediction model corresponding to the execution stage of the process instance and the node, the outcome prediction model determining a probability that the node will be executed by the process instance; and

processor-based means for applying an interval prediction model corresponding to the execution stage of the process instance and the node, the interval prediction model determining a probability that the process instance will reach the node before a designated occurrence.

30. A method for analyzing processes, comprising:

installing probes to monitor a status of a set of resources;

identifying a node of a process that is potentially affected by an affected resource in the set of resources using information relating to a link between the node and the affected resource, the process having a related process instance that has an execution stage;

applying an outcome prediction model corresponding to the execution stage of the process instance and the node, the outcome prediction model determining a probability that the node will be executed by the process instance; and

applying an interval prediction model corresponding to the execution stage of the process instance and the node, the interval prediction model predicting a time interval for the process instance to reach the node and determining a probability that the process instance will reach the node before a designated occurrence;

comparing the time interval for the process instance to reach the node to a time interval statistic to restore the affected resource;

predicting that the process instance will be impacted when the outcome prediction model and the interval prediction model indicate that the process instance will be affected with a confidence level above a threshold value.