The Operational Resilience Paradox: Socio-Technical Decoupling and Failover Invariance in Systemic Infrastructure: A Formal Empirical Evaluation
Abstract
Interdisciplinary Doctoral Research Working Paper & Candidacy Prospectus Prepared for Doctoral Supervision Evaluation, Academic Research Review, and IP Prior Art Registration. Abstract: Supervisory oversight frameworks for systemic financial infrastructure—notably Canada's Office of the Superintendent of Financial Institutions (OSFI) Guideline E-21 on Operational Risk and Resilience (published August 2024; industry adherence expected September 2026), the European Union's Digital Operational Resilience Act (DORA, Regulation EU 2022/2554, Articles 11 & 24), and the Monetary Authority of Singapore's (MAS) Technology Risk Management (TRM) Guidelines (published January 18, 2021)—mandate deterministic proofs of operational recoverability. In response, global financial institutions have heavily deployed software-defined multi-region redundancy, public cloud containerized orchestrations on hyper-scale infrastructure (specifically Azure Kubernetes Service / AKS), and active-active failover topologies. Despite these investments, catastrophic failovers persist during unscripted operational shocks. This paper provides an empirical and mathematical treatment of the Operational Resilience Paradox: technical failovers fail not due to binary hardware flaws, but due to Socio-Technical Decoupling between organizational governance structures and automated infrastructure layers. Integrating Socio-Technical Systems (STS) Theory with high-availability distributed systems principles, this study models the non-linear boundaries of Recovery Time Achieved (RTA) versus Recovery Time Objective (RTO). The framework evaluates empirical, anonymized enterprise operational paradigms: (1) First-Line Control Testing Methodologies; (2) Global IT Disaster Recovery Standard Operating Procedures; (3) Cross-border Asia-Pacific production topologies; and (4) Governance, Risk, and Compliance (GRC) schema decoupling across risk registers, architecture configuration platforms, and continuity management engines. We model human-in-the-loop decision stalls (Δt_decision), formalize the conditions under which manual attestations mask latent failure, examine high-profile industry collapses, and define an empirically validated Four-Pillar Deterministic Resilience Architecture. Cross-Disciplinary Doctoral Classifications: Systems Architecture & Engineering | Management & Strategic Governance | Financial Economics | Science, Technology & Society (STS) | Technology Law & Policy Affiliation & Group: Systems Architecture & Operational Resilience Research Group, MIR LABS LLC / Mirceos, Singapore Correspondence: https://www.linkedin.com/in/joe-alan
