Khan, SumayaAuret, Marius2025-07-242025-07-2400052411-97172225-6253https://doi.org/10.17159/2411-9717/3239/2025http://hdl.handle.net/10204/14325Due to the modernisation of mines, traditional training methods may be supplemented to support the upskilling of supervisors in mines. A project was initiated by the SAMERDI SATCAP programme to demonstrate the “art of possibility” through a modern training methodology. Two exemplar digital supervisory leadership development modules for underground gold and platinum-group metal conventional and modernising mines, were developed for potential uptake by the mining industry. These exemplar modules were exhibited on a digital platform, towards leading and driving mining modernisation. The research adopted a mixed method approach that included a literature review, a review of an existing supervisory leadership development programme, data gathering, a pilot study, and stakeholder validation workshops. The research supported the development of exemplar digitised modules. The two digitised modules were showcased to the industry for potential adoption. Training slides, a facilitator guide, and a training video were developed for ease of use by industry. The training modules are generic and not specific to a particular mine. They may be used by multi-commodity mines, including gold and platinum-group metals, as ‘stand-alone’ modules. They are customisable, through consultation with relevant service providers for specific working environments. The findings indicated that both the traditional classroom training and the new digitised online learning solution offer advantages for supervisory leadership development. Digital learning is not a new concept for supervisors at mines and modern training methods are well-supported by supervisors in the industry. A ‘modernised’ training solution may consider a ‘blended’ learning approach that combines traditional training with digital methods.AbstractenMining digital trainingMining leadership developmentMining modernisationMining supervisorsArticleN/A