1689 Figure 1 – ICMM Member Total Fatalities and Fatality Frequency data (source from https://www.icmm.com/en-gb/research/health-safety/benchmarking-2024-safety-data ) Clearly more needs to be done to reduce and eliminate fatalities in mining. The ICMM are providing an updated version of the Critical Control Management: Good Practice Guide that aims to capture some of knowledge gained from member organisations’ lessons learned implementing the critical control approach over the past decade. It aims to clarify roles and responsibilities, the decision making associated with selecting what is and isn’t a control and informational requirements for performance specification. Despite industry and regulator guidance (such as QGN35 published by the Coal Inspectorate of RSHQ, 2025), challenges remain around the selection of critical controls. The predominant approach is to rely on subjective and consultative processes to assess how “crucial” the control is at preventing or mitigating a fatality event. Sometimes guidance includes a sub note that evidence should be used in decision making but there is a scarcity of information on how to do this. Other high-risk industries have quantitative, evidencebased measures on control effectiveness or conversely the probability of the control to failure on demand. Such evidence-based approaches provide understanding on the reliability of different controls as well as their effectiveness at reducing fatalities and contribution to achieving ALARP levels of risk reduction. These approaches have been in place for decades. As evidenced with the ICMM data, the mining industry collects and publishes incident data. Further examples can be found on the Queensland’s RSHQ website (https://www.rshq.qld.gov.au/safety-notices), New South Wales Resources regulator website (https://www.resources.nsw.gov.au/resourcesregulator/safety/safety-resources/safety-alerts-and-bulletins), Western Australian LGIRS website (https://www.worksafe.wa.gov.au/health-and-safety-alerts) and the USA MSHA website (https://www.msha.gov/data-and-reports/fatality-reports/search). This raises two questions: ● Can incident data be analysed to produce and evidence based understand of the criticality of controls? ● Can the same quantitative approach be extended to track performance of critical controls over time? The remainder of this paper will demonstrate a methodology for analysing incidents to produce quantified evidence of control effectiveness (or probability of failure under demand). It will conclude with commentary about extending the approach to real-time tracking of critical controls performance and the use of artificial intelligence to inform the analysis. 2. METHODOLOGY The following method can be used to analyse incidents in a manner that delivers an understanding of
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