Optimising Mine Closure through the Integration of Stakeholder Voices: an application of Causal Network Topology Analysis

Speaker:  Dr Ben Seligmann, Research Fellow - Risk Management, Minerals Industry Safety & Health Centre, Sustainable Minerals Institute

Abstract:  Mine closure is complex. One reason for this is that all the different stakeholders speak different languages – they have a different voice. This is a metaphor, but it does speak to this reality: each stakeholder, such as mining company executives, closure team, regulator and local community, has different problem-framing questions, entailing different methods for addressing those problems to achieve their goals. And because stakeholders have different goals, they see different risks. Optimising mine closure means optimising the management of all closure risks for all stakeholders, to maximise the likelihood of a successful closure. Therefore, an approach is needed that translates each stakeholder’s problem-framing questions, methods and goals into a common vocabulary, a common framework, to be able to integrate how all risks are described, connected and managed. This seminar will present a relatively new risk analysis method called Causal Network Topology Analysis (CaNeTA) intended to enable the processes of translating and integrating described above. Through allowing us to see and analyse all closure risks in their causal context, a number of illustrative examples will be shown to demonstrate how CaNeTA can play a key role in optimising mine closure.

Bio:  Ben Seligmann is a risk specialist, systems thinker and teacher. Over the last 10 years he has worked in academia, engineering consulting, HSE and risk and compliance, across mining, infrastructure, healthcare and the education and industries. He currently focuses on risk management research at the Minerals Industry Safety and Health Centre (MISCH) within the Sustainable Minerals Institute. Ben's research interests are new frontiers of risk management, risk assessment in practice, modelling of accident scenarios and trying to engage with the complexity of socio-technical industrial systems.