IT Change Request Risk Classification via Decision Tree
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Solution Overview
Problem
Users submitting IT change requests often lack the expertise to evaluate the associated risks, such as system downtime or impact on customer service agreements, especially when dealing with new IT technologies, leading to changes being made without proper risk awareness.
Innovation Solution
A change management system that uses a decision tree model trained on historical data to classify risks and generate a graphical user interface allowing users to interactively modify request features, providing real-time risk assessments and suggestions for reducing risks, enabling users to evaluate and complete IT change requests with risk awareness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users submit IT change requests without specialized knowledge, then the ease of operation is improved, but the reliability deteriorates due to inability to evaluate risks
Solution Approach 1:
The patent introduces an automated risk assessment system that acts as an intermediary between users and change request processing. This system includes a risk assessment module that automatically evaluates change requests against predefined risk criteria, historical data, and compliance rules. The intermediary system generates risk scores and recommendations without requiring users to have specialized knowledge, thus maintaining ease of operation while improving reliability through expert-level automated analysis.
2Reliability
If manual risk assessment by experts is implemented, then the reliability is improved, but the productivity deteriorates due to time-consuming evaluation process
Solution Approach 1:
The patent implements a self-service automated risk assessment system that processes change requests independently without requiring expert intervention for each evaluation. The system automatically retrieves historical data, applies risk assessment algorithms, generates risk scores, and provides recommendations. This self-service approach maintains high reliability through consistent application of expert-defined criteria while dramatically improving productivity by eliminating manual review bottlenecks and enabling parallel processing of multiple requests.
3Measurement precision
If comprehensive risk evaluation criteria are applied, then the measurement precision is improved, but the device complexity increases due to multiple evaluation dimensions
Solution Approach 1:
The patent segments the comprehensive risk evaluation into multiple independent modular components. Each module assesses a specific risk dimension (technical risk, business risk, compliance risk, operational risk) using dedicated algorithms and criteria. The modular architecture allows each segment to be developed, maintained, and configured independently. The system integrates results from all segments to produce an overall risk score, maintaining high measurement precision while reducing system complexity through organized modularity and independent validation of each segment.
Data Source
AI summary
A computing device includes a processor and a machine-readable storage medium storing instructions. The instructions are executable by the processor to: receive input data defining an information technology (IT) change request; in response to a receipt of the input data, perform a first risk classification of the IT change request using a decision tree model; generate a graphical user interface based on the first risk classification, the graphical user interface indicating risk impacts for each of a plurality of request features, and the graphical user interface including a graphic representation of the decision tree model; in response to a user modification to a first request feature of the plurality of request features in the graphical user interface, automatically perform a second request analysis using the decision tree model; and automatically update the graphical user interface based on the second request analysis.