Exploring knowledge management strategies to sustain high-performing teams in the mining industry

Abstract

Operations success and competitive advantage in the high-stakes mining trade depend on teams with outstanding performance. Although high-performance teams offer great value, their effectiveness over time may be difficult, especially with knowledge management challenges. The study works towards exploring knowledge management techniques that can support the mining industry’s high-performance teams in staying financially sustainable. This paper addresses certain aspects of knowledge management, including creativity, retention, and information sharing, that promote adaptability and resilience in the area of mining highly performing teams. Using a qualitative research approach, semi-structured interviews helped to collect information about well-performing teams of Impala Rustenburg Operations. Using the thematic analysis method, repeating themes and patterns in the answers showed what particular obstacles these teams face and the impact effective knowledge management makes in beating these obstacles. The results reveal that safeguarding team performance in the face of high turnover and irregular employment conditions, as well as technological advances change, requires the use of organised knowledge handling techniques, such as the development of a sharing information culture and effective expertise retention. The research contributes to a small amount of material on knowledge management in the mining industry and gives important suggestions for mining organisations seeking techniques to sustain the high performance of teams and productivity over time. This paper emphasises the advantages of establishing robust knowledge management systems specifically for the mining sector, which provide an outlet allowing businesses to not only preserve but significantly raise the value of top-performing teams. This study also points to future research issues, especially on how current technologies like artificial intelligence and data analytics may perhaps improve methods for managing knowledge in the mining industry.