Measuring the effectiveness of a near-miss management system: An application in an automotive firm supplier

A near-miss management system architecture for the forensic investigation of software failures

“…Initially limited to the nuclear (Phimister et al, 2004) and aviation industries (NASA, 2006), research on the design of effective NMSs has received much attention in a wide range of industries over the last couple of years (Wu et al, 2010;Gnoni et al, 2013;Andriulo & Gnoni, 2014;Goode et al, 2014), especially in the healthcare industry for improved patient safety (Barach & Small, 2000;Callum et al, 2001;Aspden et al, 2004;Fried, 2009). Most NMSs in use today are proprietary systems designed specifically for the organisation that uses them.…”

“…As near misses and accidents have common causes, identifying the cause of a near miss is a valid method to identify the cause of the ensuing or potential accident (Andriulo & Gnoni, 2014). Root-cause analysis of near misses can be performed with investigation techniques taken from engineering disciplines, such as fishbone diagrams, event and causal factor diagrams, and failure mode and effects analysis (Phimister et al, 2003;Jucan, 2005;Hecht, 2007 Identifying near misses through observed physical events and conditions, as is done in many industries, is especially challenging in the software industry.…”

Learning from text-based close call data

“…The GB railways maintain the Close Call database to describe hazardous situations where an event sequence could lead to an accident if it had not been detected, interrupted by a planned intervention or by random event (Gnoni, Andriulo et al 2013, Andriulo andGnoni 2014). Workers within the GB railway industry are able to voluntarily report such events on the railway by submitting data to the Close Call database.…”

“…There are different definitions amongst researchers about close calls, near-misses and/or weak signals (Dillon and Tinsley 2008). This work uses a definition by Gnomi and Anndriulo which fits the railway industry: a close call is a hazardous situation where the event sequence could have led to an accident if it had not been detected, interrupted by a planned intervention or by random event (Gnoni, Andriulo et al 2013, Andriulo andGnoni 2014). …”

“…Given the larger body of data, close calls therefore potentially provide a richer source of safety-relevant data than accident data alone, and analysis of close call data may be used to assist in the development of safety management system more efficiently than by considering only records of accidents. In fact close call event data can be used to detect and prevent the precursors of accidents (Clarke 1998, Jones, Kirchsteiger et al 1999 and can therefore assist an organisation in improving their safety management practices even where there has been no history of accidents (Andriulo and Gnoni 2014). In this way, close call data can be used to manage the precursors to events that have a low likelihood of occurring but that have potentially very large consequences.…”