Operationalizing normal accident theory for safety-related computer systems

Computer-related accidents have caused injuries and fatalities in mining as well as other indus­ tries. Normal accident theory (NAT) explains that some accidents are inevitable because of system complexity. NAT is a classic argument in organizational sociology although it has been criticized as having imprecise deWnitions and lacking criteria for quantifying complexity. These limitations are addressed by a unique approach that recasts this organizational theory into an engineering-based methodology to quantify NAT complexities of computer-based systems. In this approach complexity is categorized as external or internal. External complexity is deWned by the external behavior of a system, and is quantiWed by these dependent variables: system predictability, observability, and usability. Dependent variable data contain the perceptions of 32 subjects running simulations of a system. The system’s internal complexity is characterized by modeling system-level requirements with the software cost reduction (SCR) formal method. Model attributes are quantiWed using 15 graph-theoretical metrics—the independent variables. Five of 15 metrics are correlated with the dependent variables as evidenced by structure correlations exceeding 0.25, with standard errors <0.10 and a 95% conWdence interval. The results also show that the system predictability, observabil­ ity, and usability decreased as NAT complexities increased. This research takes a step forward in oper­ ationalizing NAT for computerized systems. The research beneWts mining and other industries as well.