IT Incident Management via User Activity Mining
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Solution Overview
Problem
Incident management systems in IT operations face challenges in quickly returning IT services to users due to overwhelming amounts of information, which divert operator attention from addressing issues, leading to time-consuming searches for relevant diagnostic information.
Innovation Solution
A computer-implemented method for an operations management system that obtains user activity information, represents it as an itemset, processes it with a mining algorithm to identify frequently accessed information, and associates it with incident categories, providing enriched and relevant information for future incidents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a large amount of information is made available to operators for incident management, then the completeness of information increases, but the time required to search for relevant information increases
Solution Approach 1:
The system extracts only the most relevant information items from the large body of available information based on frequency analysis of operator interactions. By identifying and extracting frequently accessed information items, the system presents a filtered subset that maintains completeness of essential information while eliminating unnecessary search time.
Solution Approach 2:
The system changes the parameter of information presentation by dynamically adjusting which information items are displayed based on their frequency of access. Information items are ranked and prioritized according to their frequency metrics, transforming the static information presentation into a dynamic, adaptive display that optimizes for both completeness and efficiency.
2Adaptability or versatility
If multiple information sources and tools are provided in operations management systems, then the capability to manage incidents improves, but the complexity of the system increases
Solution Approach 1:
The system performs self-service by automatically analyzing operator interaction patterns and autonomously determining which information items are most relevant. This self-organizing mechanism eliminates the need for manual configuration of information prioritization, reducing system complexity while maintaining high adaptability to different incident scenarios.
Solution Approach 2:
The system performs preliminary analysis of information relevance by continuously monitoring and analyzing operator interactions before incidents occur. This pre-computed frequency data is stored and readily available during incident management, eliminating the need for complex real-time analysis and reducing system complexity during critical incident response.
3Measurement precision
If operators manually search through all available information, then comprehensive incident analysis is achieved, but incident resolution time increases
Solution Approach 1:
The system performs preliminary organization and prioritization of information based on historical interaction patterns before operators need to access it. By pre-computing and storing frequency rankings of information items, the system ensures that the most relevant information is immediately accessible, maintaining analysis accuracy while dramatically improving resolution speed.
Solution Approach 2:
The system incorporates feedback from actual operator interactions to continuously refine and update the prioritization of information items. This feedback loop ensures that the information presentation remains aligned with actual incident resolution needs, maintaining high analysis accuracy while optimizing for speed through empirically validated information ranking.
Data Source
AI summary
An operations management system and related method obtains user activity information representing user interactions with the operations management system responsive to an incident, the incident belonging to a category of incidents. The method represents the user activity information as an itemset. The method further processes the itemset with a mining algorithm to identify one or more items of information frequently accessed for the incident. The method yet further associates the identified one or more items of information with the category of incidents.