Operations planning and decision-making research for emergency management have increased in both academia and industry due to catastrophic events that have occurred in the past two decades. Recovery and reconstruction are intrinsically dependent on events’ characteristics and how planning, preparation and response are performed. Numerous transportation research have already focused on mathematical optimization, network reliability, risk management, and decision-making. Findings are still to be combined into common frameworks so better understanding of decision-making during emergency events can be achieved by the transportation community. This paper presents an academic approach to analyze extreme event decision-making within roading organizations using data from practical experiences. An emergency exercise observation and game simulation data collection method as well as a data analysis framework are proposed to study extreme event decision-making. A series of case studies were conducted by rigorously observing seven emergency exercises and simulating twelve game-based scenarios at several New Zealand roading organizations. Data collected during such experiences have proven the applicability of the framework, supporting two major findings: i) Extreme event decision-making is dependent on previous planning and experiences, confirming Naturalistic Decision-making models; and ii) Emergency response and recovery can be associated with two time frames (short and long terms objectives).