Automated Incident Classifier for ITSM to RPA Routing
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Solution Overview
Problem
Current IT service management systems require human intervention to transfer incidents to RPA systems, which is time-consuming and prone to errors.
Innovation Solution
A system that uses machine learning and natural language processing to classify and parse free-text incidents into RPA-compatible information, enabling automated resolution without human intervention by classifying incidents into automation flows and generating RPA-compatible data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human intervention is used to transfer incidents to RPA systems, then transfer accuracy is improved, but resolution time increases and productivity decreases
Solution Approach 1:
The system enables self-service by implementing an automated incident transfer mechanism where the ITSM system automatically classifies and transfers incidents to RPA systems without requiring human intervention. The automated classifier analyzes incident data and determines the appropriate RPA system autonomously, eliminating manual transfer steps while maintaining accuracy through systematic classification rules.
Solution Approach 2:
An automated incident classifier is introduced as an intermediary component between the ITSM system and RPA systems. This mediator automatically processes incident data, applies classification rules, and routes incidents to the appropriate RPA system, replacing human operators in the transfer process while maintaining or improving transfer accuracy through consistent rule-based decision-making.
2Measurement precision
If human intervention is used to transfer incidents, then classification accuracy is improved, but device complexity and operational effort increase
Solution Approach 1:
The classification process is segmented into distinct automated components: data extraction from ITSM systems, application of classification rules, determination of target RPA systems, and execution of transfers. Each segment is handled by specific automated functions within the classifier, reducing the need for complex human decision-making processes while maintaining classification accuracy through systematic rule application.
Solution Approach 2:
The system transforms unstructured or semi-structured incident data into structured classification parameters that can be automatically processed. By converting incident descriptions into standardized parameters and attributes, the system enables automated classification with high accuracy while reducing the complexity of manual analysis through parameter-based decision rules.
3Adaptability or versatility
If manual incident transfer is performed, then flexibility in handling diverse incidents is maintained, but loss of time and operational efficiency worsen
Solution Approach 1:
The automated incident classifier implements dynamic routing capabilities that adapt to different incident types, priorities, and characteristics in real-time. The system dynamically determines the appropriate RPA system for each incident based on current classification rules and incident attributes, maintaining flexibility to handle diverse incidents while executing transfers automatically without manual intervention delays.
Solution Approach 2:
The system establishes continuous automated incident transfer operations where incidents are classified and routed immediately upon generation in the ITSM system. This continuous automated process eliminates interruptions and waiting periods associated with manual transfer, maintaining operational flexibility while ensuring uninterrupted incident flow to appropriate RPA systems for resolution.
Data Source
AI summary
A system, method, and computer program product are provided for automated resolution of free-text incidents, based on machine learning. In operation, a system receives incident information from at least one IT service management (ITSM) system. The system reads the incident information including free text and classifies an incident associated with the incident information to at least one automation flow. The system generates robotic process automation (RPA) compatible information from the incident information by parsing parameters associated with the incident from text into required fields based on the at least one automation flow. Further, the system sends the generated RPA compatible information to the at least one ITSM system or at least one RPA system.