Automated Issue Ticket Analysis for Underlying Problem Detection
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Solution Overview
Problem
Current IT ticketing systems lack the capability to analyze issues across multiple computing devices to identify possible underlying problems, leading to repetitive resource consumption and downtime, which affects organizational productivity and revenue.
Innovation Solution
A problem detection platform that processes millions of electronic issue tickets using text processing techniques to classify issues, monitor thresholds, and generate electronic problem tickets, automating the detection and resolution process to identify and address underlying issues proactively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis of issue tickets is performed, then detailed examination of each issue is possible, but resource consumption increases and underlying problems are not identified
Solution Approach 1:
The patent replaces manual mechanical analysis of issue tickets with automated text processing techniques including natural language processing, pattern recognition, and machine learning algorithms. This substitution enables systematic analysis of millions of tickets while identifying underlying problems that would be impossible to detect through manual review, thereby reducing resource consumption while maintaining or improving analysis depth.
Solution Approach 2:
The system creates standardized issue categories and patterns by analyzing representative tickets, then uses these copies/templates to automatically classify and analyze similar tickets. This approach allows the system to handle vast volumes of tickets efficiently by matching them against established patterns rather than analyzing each ticket individually from scratch.
2Productivity
If reactive ticket resolution is used, then individual issues are addressed, but underlying problems persist leading to repetitive incidents
Solution Approach 1:
The patent implements proactive problem detection by analyzing issue ticket patterns before they manifest as widespread system failures. The system identifies emerging trends and underlying problems through text processing of tickets, enabling preventive actions to be taken before reliability issues affect multiple systems. This preliminary detection and response capability transforms the organization from reactive to proactive problem management.
Solution Approach 2:
The system establishes continuous feedback loops where analyzed issue tickets and identified patterns feed back into the monitoring and detection processes. This feedback mechanism enables the system to learn from resolved issues, refine pattern recognition, and improve future detection accuracy, creating a self-improving system that enhances both productivity and reliability over time.
3Measurement precision
If comprehensive text processing is applied to all tickets, then accurate classification is achieved, but processing time increases
Solution Approach 1:
The patent applies text processing techniques selectively rather than uniformly to all tickets. The system uses lightweight initial processing to identify obvious patterns and route tickets to appropriate analysis depths, applying comprehensive text processing only when necessary to achieve accurate classification. This partial action approach maintains high classification accuracy while minimizing unnecessary processing time for straightforward cases.
Solution Approach 2:
The patent segments the text processing workflow into multiple stages: initial filtering, pattern matching, detailed analysis, and verification. Each stage processes tickets at an appropriate level of depth, with early segments handling routine classification quickly and later segments providing more sophisticated analysis only when needed. This segmented approach balances classification accuracy with processing efficiency across different ticket types.
Data Source
AI summary
A device may process text included in an electronic issue ticket to identify a set of terms or a pattern of terms included in the text. The electronic issue ticket may be related to an issue associated with a computing device. The device may classify the electronic issue ticket into an issue category of a set of issue categories. The set of issue categories may be related to various issues associated with various computing devices. The device may monitor a counter for a set of thresholds associated with the issue category. The device may detect a possible underlying problem among the various computing devices. The device may generate an electronic problem ticket for the possible underlying problem. The device may append the electronic problem ticket with information related to the electronic issue ticket or one or more other electronic issue tickets. The device may perform one or more actions.