Resilience in emergency management: Learning from COVID-19 in oil and gas platforms.

R Cantelmi, R Steen, G Di Gravio, R Patriarca
Author Information
  1. R Cantelmi: Dept. of Mechanical and Aerospace Engineering, Sapienza University of Rome, Rome, Italy.
  2. R Steen: BI Norwegian Business School, Stavanger, Norway.
  3. G Di Gravio: Dept. of Mechanical and Aerospace Engineering, Sapienza University of Rome, Rome, Italy.
  4. R Patriarca: Dept. of Mechanical and Aerospace Engineering, Sapienza University of Rome, Rome, Italy.

Abstract

Emergency management, both in civilian and military context, is regarded as a complex socio-technical system, whose dynamic nature and complexity require a holistic approach. Over time, scholars developed diverse strategies and methods to capture such complexity and effectively design emergency plans for more or less severe disasters scenarios. Nonetheless, planning is not always an omni-comprehensive task, pushing organizations to stretch their adaptive capacities in dynamic and challenging settings. This manuscript explores such adaptive capacity as put in place by a leading Norwegian organization in providing emergency management solutions, facing unexpected challenges (at the time of the event): handling of Covid-19 infection episodes on offshore oil platforms. The study, conducted through the Functional Resonance Analysis Method (FRAM) highlights the relevance of organizational learning which allows to handle emergencies by adapting plans to the specific context and by renewing new emergency management procedures derived from lessons learned. The study focuses on three different Covid-19 infection management cases to understand the nuances of actions and emerging adaptations that led to the development of a revised emergency plan, seen again through the lens of FRAM. While the methodological approach refers to Covid-19 infection management, we believe it can be extended into larger crisis management, providing a use case for the applicability of FRAM into emergency management scenarios.

Keywords

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