Supply Chain Risk Analytics Framework
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Solution Overview
Problem
Current supply chain management lacks comprehensive analytics and decision support tools for analyzing security risks and optimizing investment in mitigation options, leading to suboptimal return on investment in terms of cost, efficiency, and security.
Innovation Solution
A computer-implemented framework for supply chain analytics that generates a representation of the supply chain as a graph, allowing for risk assessment, attack simulation, and mitigation strategy development, using algorithms to rank nodes and edges based on attack susceptibility and consequence, and visualizing potential attacks to facilitate decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive security analytics and decision support tools are implemented, then security investment optimization improves, but system complexity and implementation cost increase
Solution Approach 1:
The supply chain is segmented into discrete nodes (facilities, locations) and edges (supply flows, information flows) that can be individually assessed for security risks. This segmentation allows the analytics system to focus on specific high-risk areas rather than analyzing the entire supply chain uniformly, reducing overall system complexity while maintaining comprehensive security coverage.
Solution Approach 2:
The patent introduces a visual dimension through the relative risk chart that plots attack consequence against attack difficulty. This graphical representation transforms complex multi-dimensional security data into an intuitive two-dimensional visualization, enabling decision-makers to quickly identify high-risk areas without being overwhelmed by data complexity.
2Reliability
If detailed risk assessment of all supply chain locations is performed, then security coverage improves, but analysis time and computational resources increase
Solution Approach 1:
The system applies local quality assessment by evaluating security risks at individual nodes and edges specific to their characteristics and roles in the supply chain. Each location receives tailored risk assessment based on its specific vulnerabilities, attack surface, and importance to the overall supply chain, rather than applying a uniform assessment approach everywhere.
Solution Approach 2:
The relative risk chart enables partial action by allowing decision-makers to focus security resources on the most critical high-consequence, low-difficulty attack vectors identified in the visualization. This selective focus on partial areas of highest risk reduces the time and resources needed compared to comprehensive analysis of all possible attack vectors across the entire supply chain.
3Reliability
If mitigation strategies are applied to all identified risks, then security effectiveness improves, but implementation cost and time increase
Solution Approach 1:
The system changes the parameter of risk prioritization by using the relative risk chart to identify which risks should be addressed first based on their consequence and difficulty characteristics. This parameter-based prioritization allows organizations to modify their risk treatment approach dynamically, focusing on high-impact, low-effort mitigations before tackling more complex or lower-priority risks.
Solution Approach 2:
The framework performs preliminary action by identifying and visualizing the most critical risk areas before mitigation resources are committed. The relative risk chart provides advance guidance on which mitigation strategies will yield the highest security improvement per unit of investment, allowing organizations to plan and sequence mitigation activities optimally rather than implementing them haphazardly.
Data Source
AI summary
The various technologies presented herein relate to pertaining to identifying and mitigating risks and attacks on a supply chain. A computer-implemented representation of a supply chain is generated comprising nodes (locations) and edges (objects, information). Risk to attack and different attack vectors can be defined for the various nodes and edges, and further, based upon the risks and attacks, (difficulty, consequence) pairs can be determined. One or more mitigations can be generated to increase a difficulty of attack and/or reduce consequence of an attack. The one or more mitigations can be constrained, e.g., by cost, time, etc., to facilitate determination of how feasible a respective mitigation is to implement with regard to finances available, duration to implement, etc. A context-free grammar can be utilized to identify one or more attacks in the supply chain. Further, the risks can undergo a ranking to enable mitigation priority to be determined.