MANAGING ENTERPRISE RISK UNDER PANDEMIC UNCERTAINTY: A TRANSCENDENTAL PHENOMENOLOGICAL STUDY

Abstract

This dissertation examines how organizational leaders experienced managing the risk management process during the COVID-19 pandemic, a period marked by sustained uncertainty, compressed decision cycles, and volatile operational conditions. The study sought to understand what it was like to lead and execute risk work in this context and how risk management practices were maintained, adapted, or reconfigured over time. Using a transcendental phenomenological approach, the study drew on in-depth, semi-structured interviews with twenty participants in the Canadian oil and gas industry who were responsible for enterprise risk, finance, operations, or executive decision-making. Data were analyzed using systematic phenomenological procedures, progressing from horizontalization and clustering of significant statements to textural and structural descriptions, culminating in an integrated synthesis of essence. Findings indicate that risk management during the pandemic was experienced as a dynamic balancing act between stabilizing controls and adaptive learning. Participants described (a) the enabling and constraining role of governance and decision architecture, (b) the importance of communication cadence and cross-functional channels for coordination and trust, (c) reliance on information artifacts and deliberate signal management to support sensemaking, and (d) persistent agency-constraint tensions, including workload strain and morale risks, that shaped what was feasible in practice. The dissertation offers a conceptual framework that links formal systems and lived practice to continuity-oriented controls and adaptation-oriented learning, clarifying how crisis conditions reveal both strengths and fragilities in risk processes. Practical implications are provided for leaders seeking to design resilient risk governance, improve information quality and escalation pathways, and sustain organizational capacity during prolonged uncertainty.