Analysing Accidents and Lessons Learned: You Can’t Improve What You Don’t Measure
Wood Maureen, Heraty
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How to Cite

Wood Maureen H., 2018, Analysing Accidents and Lessons Learned: You Can’t Improve What You Don’t Measure, Chemical Engineering Transactions, 67, 391-396.
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Abstract

For a long time now, accident analysis theory has evolved from a study of mechanical and emergency response failure to the study of the wider influences that may have made the accident more likely, particularly safety management systems. This trend is very positive, but there is still considerable room for improvement especially since frameworks to drive analysis of these causal factors are not widely available for routine accident analyses. Indeed, there is growing evidence that incident reporting remains insufficient for yielding feedback on many topics that are at the centre of process safety discussions today, such as systemic risk and emerging risks associated with new technologies. It can be argued that safety experts have limited tools for capturing warning signs of complex or new causal factors, such as ageing of sites, process automation, management of organizational change, and safety culture. Given increasing consensus on the value of safety performance monitoring, and the role of incident analysis in this process, it would seem that there should be greater attention to this limitation. To a large extent, complex and new causal factors belong to a third dimension of causality, beyond safety management systems and technical factors, that may require development of a third generation of user-friendly tools or frameworks to identify them. This paper describes the findings from a study that aimed to confirm the hypothesis that the practice of lessons learned analysis is not sufficiently capturing new and complex risk factors. To do so, the European Commission’s Joint Research Centre (JRC) conducted a study of lessons learned reported for 108 accidents occurring between 2010 – 2017. The study aimed to understand to what extent safety experts were actively seeking evidence of systemic and emerging risks in their analyses. This paper describes the findings from that study, presenting the state of practice with the eMARS database in regard to analysis of underlying causes and identification of precursors. The outcomes also suggest that many practitioners are already trying to apply a third level of analysis and in some cases point towards possible solutions.
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