Automated Risk Management Platform for IT Asset Relationships
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Solution Overview
Problem
Conventional risk management systems are inadequate for modern enterprises using digital business tools, as they rely on unsustainable manual processes and are not equipped to handle the increased complexity and data-driven risks associated with digital transformation, agile software development, and DevOps environments.
Innovation Solution
An information processing system comprising a processing platform that receives usage data from operational management systems, identifies asset and user-asset relationships, applies parameters to determine designations, and triggers risk management workflows to address these complexities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual risk assessment processes are used, then risk management can be performed with simple systems, but productivity and reliability deteriorate due to unsustainable manual processes
Solution Approach 1:
The patent replaces manual mechanical risk assessment processes with an automated computational system that uses processing platforms, algorithms, and data analytics to perform risk assessments, thereby eliminating the limitations of manual processes while maintaining reliability
Solution Approach 2:
The system enables self-service risk management by automatically collecting data from operational management systems, performing assessments, and generating reports without requiring manual intervention, thus improving both productivity and reliability
2Adaptability or versatility
If conventional risk management systems are used, then device complexity remains low, but adaptability deteriorates due to inability to handle digital transformation complexities
Solution Approach 1:
The processing platform is designed to perform multiple risk management functions including data collection, relationship identification, risk assessment, and reporting within a single unified system, enabling it to adapt to various digital transformation scenarios while managing complexity through integration
Solution Approach 2:
The system dynamically adapts to changing risk landscapes by continuously collecting usage data from operational management systems and adjusting risk assessments based on real-time data, enabling it to handle evolving digital transformation complexities
3Measurement precision
If automated relationship identification is implemented, then measurement precision improves for risk characterization, but device complexity increases due to data processing requirements
Solution Approach 1:
The system extracts only the essential usage data and relationship information needed for risk characterization from operational management systems, applying parameters selectively to identify key asset relationships without processing unnecessary data, thus improving precision while managing complexity through targeted data extraction
Data Source
AI summary
A method in one embodiment includes receiving usage data from a first operational management system, the first operational management system utilizing a plurality of assets of an information technology infrastructure. The method also includes identifying, based at least in part on the received usage data, one or more asset relationships between at least two assets of the plurality of assets, and one or more user-asset relationships between one or more users and one or more of the plurality of assets. In the method, one or more parameters of a plurality of parameters are applied to the identified asset and user-asset relationships to determine one or more designations associated with the identified asset and user-asset relationships. The one or more designations are transmitted to a second operational management system to trigger a risk management workflow based at least in part on the one or more designations.