Automated Critical Resource Identification in Business Continuity
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Solution Overview
Problem
Current business-continuity planning methods require manual and complex processes to identify critical resources, which can be inefficient and prone to errors in assessing disruptions and resumption costs across multiple resource types and projects.
Innovation Solution
A method and system for automatically identifying critical resources by analyzing dependency relationships and capacity thresholds, using a processor to determine the impact of disruptions on resource types and projects, and categorizing resources based on their criticality and resumption costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processes are used to identify critical resources, then flexibility and adaptability are maintained, but efficiency and accuracy deteriorate
Solution Approach 1:
The patent replaces manual mechanical processes with an automated computer-based system that uses processors to execute algorithms for identifying critical resources. The system automatically analyzes resource dependencies, calculates capacities, and determines criticality without human intervention, thereby improving efficiency while managing complexity through software automation.
Solution Approach 2:
The system enables self-service by allowing the computer to autonomously perform the entire critical resource identification process. The processor automatically receives dependency relationships, determines capacities, and categorizes critical resources without requiring manual analysis, making the system serve itself in identifying business-critical assets.
2Measurement precision
If comprehensive dependency analysis is performed across all resource types, then identification accuracy is improved, but processing time and computational complexity increase
Solution Approach 1:
The system performs preliminary action by pre-establishing the framework for dependency analysis and capacity determination. The processor is configured to automatically receive and process dependency relationships in advance, and to calculate capacities based on predefined functions, enabling rapid identification of critical resources when disruptions occur without time-consuming manual analysis.
Solution Approach 2:
The patent applies parameter changes by using mathematical functions to determine capacity based on disruption scenarios. The system transforms raw dependency data into meaningful capacity metrics through computational parameters, allowing accurate identification of critical resources while maintaining efficient processing through algorithmic parameter transformation rather than exhaustive analysis.
3Productivity
If automated systems are implemented for identifying critical resources, then efficiency and accuracy are improved, but system complexity and implementation difficulty increase
Solution Approach 1:
The patent applies universality by designing a multi-functional computer-based system that can handle various resource types, dependency relationships, and disruption scenarios through a single integrated platform. The processor executes multiple functions including receiving dependency data, determining capacities, categorizing critical resources, and supporting business-continuity planning, thereby achieving high automation efficiency while managing complexity through functional integration.
Data Source
AI summary
A method and associated systems for ensuring resilience of a business function manages resource availability for projects that perform mission-critical tasks for the business function. The method and systems create a model that reveals dependencies among types of resources needed by a project, such that the model describes how the unavailability of one instance of a resource propagates disruptions to other instances of the same type of resource. This model automatically identifies a resource type as being critical if a disruption of an instance of the resource type would render a project task infeasible, and if restoring that task would incur unacceptable cost. The model may also automatically identify a first resource type as being critical for a second resource type when disruption of the first resource type reduces the available capacity of the second resource type to an unacceptable level.