Automated Incident Resolution Estimation System
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Solution Overview
Problem
In complex enterprise environments, resolving incidents is hindered by the difficulty in identifying and distributing critical information effectively among numerous resources, leading to inefficiencies and potential duplication of efforts, despite the urgency to resolve issues quickly.
Innovation Solution
An automated system and method that utilize historical incident data through machine learning to estimate the time required for incident resolution by processing incident information, critical action data, and previous action outcomes, providing real-time updates and graphical timelines to incident managers and team members.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple technological and human resources are brought to bear on an incident to resolve it quickly, then the urgency to resolve the problem is addressed, but duplicative or inappropriate resource allocation occurs leading to inefficiency
Solution Approach 1:
The system continuously monitors incident status and resource allocation, providing real-time feedback to incident managers about which resources are appropriately assigned and which are duplicative. This enables dynamic adjustment of resource allocation to maintain both speed and efficiency.
Solution Approach 2:
The system automatically identifies and assigns appropriate resources based on incident characteristics and historical data, reducing the need for manual resource coordination and minimizing duplicative assignments while maintaining rapid response capability.
2Ease of operation
If comprehensive monitoring and management of disparate operatives is implemented to improve coordination, then resource distribution improves, but system complexity increases
Solution Approach 1:
The system provides multiple functions including automated resource assignment, real-time status tracking, historical analysis, and predictive modeling within a single integrated platform, improving coordination without requiring multiple separate complex systems.
Solution Approach 2:
The system acts as an intermediary layer between incident managers and disparate operatives, standardizing communication and coordination protocols while maintaining simplicity for end users through automated processes.
3Productivity
If historical incident data and machine learning models are deployed to improve decision-making, then resource allocation efficiency improves, but information processing requirements increase
Solution Approach 1:
The system pre-processes and structures historical incident data in advance, creating ready-to-use models and patterns that can be quickly applied to current incidents, reducing real-time processing requirements while maintaining high decision-making efficiency.
Solution Approach 2:
The system extracts only the most relevant features and patterns from historical data that are applicable to current incidents, avoiding processing of redundant information while maintaining accurate predictive capabilities.
Data Source
AI summary
An automated system is provided for facilitating resolution of an incident. An incident information data processor is configured to receive incident information and an action estimation data processor is configured to receive critical action information that includes a description of an action and an action initiation time. The action information data processor obtains previous action information on actions taken to resolve previous incidents and determines an estimated action outcome and an estimated critical action time interval for resolution of the critical action using the critical action information and the previous action information. An incident estimation data processor is configured to determine an overall estimated time interval for incident resolution and an estimated incident resolution time. An incident display data processor is configured to transmit, to a user data processing system for display to a user, at least the estimated incident resolution time.