Causal network topology analysis: Characterizing causal context for risk management.

Area of Science:

• Risk Management
• Network Science
• Decision Analysis

Background:

• Traditional risk assessments often fail to integrate the causal context of individual risk events.
• This limitation hinders effective decision-making processes in organizations.
• Previous applications of network topology analysis have lacked consistent terminology and methodology.

Purpose of the Study:

• To formalize causal network topology analysis as a robust methodology.
• To characterize the causal context of risk events for improved management.
• To provide a clear framework for repeatable network analysis and metric selection.

Main Methods:

• Development of a formalized causal network topology analysis methodology.
• Articulation of ontological concepts for network analysis.
• Justification of network metrics for risk assessment applications.

Main Results:

• A formalized methodology for causal network topology analysis is presented.
• The approach provides a structured way to understand causal interactions of risk events.
• An exemplar application in a mining project feasibility study demonstrates practical utility.

Conclusions:

• Causal network topology analysis offers a more integrated approach to risk assessment.
• The formalized methodology enhances clarity, consistency, and interpretability.
• This approach improves the quality of risk management and decision-making.