A Model of Adaptive Error Management Practices Addressing the Higher-Order Factors of the Dirty Dozen Error Classification—Implications for Organizational Resilience in Sociotechnical Systems

Abstract

Within the dynamic, complex, and often safety-critical operations of many process industries, the integration of technology and human elements has given rise to sociotechnical systems (STSs), where the interaction between people and technology plays a pivotal role. To thrive in this complex environment, organizations must adopt adaptive error management strategies and cultivate organizational resilience. This approach involves managing the unexpected and designing systems to embrace disorder by organizational learning from errors in STSs. The main objective of this article was to present empirical data of error-causing elements in STSs based on the Dirty Dozen concept, their underlying structure, and implications for error causation screening and adaptive error management systems. A sample of 544 workers employed in seven process industries, such as automotive, chemicals, defense, metal, and timber, participated in this study. The results revealed a three-factor model of human error causation in STSs. Based on these results, an adaptive error management system (AEMS), which includes evidence-based interventions to manage causes of human errors and mitigate their risky consequences, was presented. Finally, implications for organizational resilience and safety culture in STSs were discussed.