Incident Profile Aggregation System for IT Data Consolidation
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Solution Overview
Problem
Existing technologies face challenges in efficiently aggregating and analyzing incident data across complex IT systems, leading to inefficiencies in incident resolution and increased risk of system outages.
Innovation Solution
A method and system for aggregating and mapping incident characteristics into daily profiles, involving the receipt of historical data objects, determination of single incident profiles, consolidation of profiles, aggregation at a day level, and outputting consolidated profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If incident data is aggregated and analyzed across complex IT systems, then incident resolution efficiency is improved, but system complexity and data processing burden increase
Solution Approach 1:
The patent segments incident data into distinct types (incidents, changes, problems) and processes each type separately through specialized analysis modules. This segmentation allows the system to handle complex data aggregates by breaking them into manageable, type-specific components that can be processed independently and then integrated for comprehensive incident profiling.
Solution Approach 2:
The patent introduces an intermediary incident profile generation system that acts as a mediator between raw incident data and resolution actions. This intermediary layer consolidates multi-source data (incidents, changes, problems) into unified incident profiles, reducing the complexity burden on downstream resolution processes while maintaining comprehensive analysis capabilities.
2Adaptability or versatility
If decentralized personnel and systems are used to resolve incidents, then system adaptability and coverage are improved, but coordination efficiency and resolution time increase
Solution Approach 1:
The patent merges data from decentralized sources (multiple incident records, change requests, problem logs) into unified incident profiles that consolidate information across the distributed system. This merging allows decentralized personnel to access comprehensive, pre-integrated information, maintaining broad coverage while reducing the time needed to gather and coordinate data across distributed teams.
Solution Approach 2:
The patent implements feedback mechanisms where incident profiles are continuously updated and refined based on resolved incidents and associated changes. This feedback loop allows decentralized systems to learn from past incidents, improving coordination efficiency over time while maintaining the adaptability benefits of distributed personnel and systems.
3Ease of manufacture
If individual ticket resolutions are processed separately, then processing simplicity is maintained, but overall incident resolution efficiency decreases
Solution Approach 1:
The patent merges individual ticket resolutions with related incidents and changes to create comprehensive incident profiles. While individual tickets can still be processed separately for simplicity, the system combines them with associated data from other sources to provide holistic incident understanding, thereby improving overall resolution efficiency without sacrificing the processing simplicity of individual tickets.
Solution Approach 2:
The patent creates incident profiles that serve multiple functions simultaneously: they consolidate individual ticket information, track associated changes, identify recurring problems, and support both individual and coordinated resolution efforts. This multi-functionality allows the system to maintain processing simplicity for individual tickets while achieving improved overall efficiency through unified incident management.
Data Source
AI summary
A computer implemented method for aggregating and mapping incident characteristics into a daily profile. The method includes: receiving a set of historical data objects indicating an occurrences of a set of incidents each associated with a set of configurable items; determining a single incident profile for each of the historical data objects; determining a consolidated single incident profile for each of the historical data objects; aggregating the consolidated single incident profiles at a day level; and outputting the consolidated single incident profiles at the day level.