The complexity of governance: Validating a pragmatic systems model

Abstract

Background: Governance quality is an ever-changing phenomenon that is complex, emergent and dynamic. The requirement to assess the quality of governance is prescribed by many regulators and other authorities; however, evidence suggests that the methods used to observe the performance and development of governance do little to mitigate corporate failure. There needs to be a more performance and human-oriented model and assessment framework that observes and measures governance complexity, acknowledging and approaching governance as foundational in all organisational systems.
Objectives: This paper validated a pragmatic Complexity Governance Model proposed by Carey and Mahendran, 2025, so that governance assessments and reviews can move beyond compliance towards performance.
Method: The methodology followed a quantitative-based approach and used a combination of Opportunity and Non-Probability Sampling methods. Data were collected by way of a structured, internally validated survey instrument. Analysis was conducted using correlational and linear regression to determine if power law relationships existed within the data.
Results: Governance is appearing as a complex system through power law relationships and R-squared values across many of the 27 indices measured. There was an observable hierarchy across the indices of governance, indicating that some are more influential than others in effecting ‘good’ governance.
Conclusion: The Complexity Governance Model (GOVIndicia^®) showed early signs of being able to observe and measure governance quality through the lens of complexity and withstood internal validation.
Contribution: The Complexity Governance Model and assessment framework can be used to support boards, organisations and regulators to measure, design and monitor governance, governance performance and the effectiveness of development programmes.