Automated Change-incident Pairing for IT Incident Reduction
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Solution Overview
Problem
Current systems face challenges in linking information technology service incident tickets to relevant change tickets due to lack of documented historical data, making it difficult to discover and visualize complex trends and implicit relationships between incidents and changes, which hinders proactive incident prevention and retrospective analysis.
Innovation Solution
A method that involves obtaining change and incident tickets, defining change-incident pairs, identifying dimensions affecting change outcomes, generating recommendations for altering change implementations, applying these recommendations, and monitoring their effectiveness, using a service management system coupled with a service management database and configuration management database to automate and dynamically update recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual linking of incident tickets to change tickets is performed, then some historical change-incident pairs can be documented, but the process is time-consuming and incomplete due to lack of automated methods
Solution Approach 1:
The patent replaces manual mechanical processes of linking incidents to changes with automated computer-based systems that use machine learning algorithms and data processing to automatically create change-incident pairs from service management databases
Solution Approach 2:
The system enables self-service by automatically performing the linking function without human intervention, using automated data extraction, matching algorithms, and pattern recognition to create change-incident pairs independently
2Quantity of substance
If comprehensive change and incident data is collected, then more complete historical records are available, but the complexity and high dimensionality of data makes it difficult to discover trends and relationships
Solution Approach 1:
The patent segments the complex high-dimensional data into structured components including change tickets, incident tickets, and change-incident pairs, organizing them in a service management database with defined relationships and attributes that can be systematically analyzed
Solution Approach 2:
The patent introduces an intermediary processing layer that includes automated linking mechanisms, data normalization processes, and analytical tools that mediate between the raw comprehensive data and the trends/relationships that need to be discovered, making the data manageable and analyzable
3Ease of operation
If simple summarizing statistics are used, then data is easy to visualize, but complex trends and implicit relationships between incidents and changes cannot be discovered
Solution Approach 1:
The patent adds another dimension to data analysis by moving from simple summarizing statistics to multi-dimensional analytical views that include temporal patterns, causal relationships, and implicit connections between changes and incidents, enabling discovery of complex trends while maintaining visualizability through structured presentation
Data Source
AI summary
A method includes obtaining, from a service management database, one or more change tickets and one or more incident tickets relating to an information technology infrastructure, defining one or more change-incident pairs based on linkages between the incident tickets and the change tickets, identifying, from the change-incident pairs, one or more dimensions affecting outcomes of implementation of one or more change types, generating at least one recommendation for altering implementation of subsequent changes of a given change type to the information technology infrastructure based on the identified dimensions, applying the at least one recommendation to the implementation of one or more subsequent changes of the given change type to configuration items in the information technology infrastructure, monitoring the information technology infrastructure to determine outcomes of the subsequent changes of the given change type, and modifying the at least one recommendation responsive to the monitoring.