Modelling the root causes of complexity in the South African sawmilling industry

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Abstract

The sawmilling industry in South Africa has faced many obstacles that have severely impacted its competitiveness and sustainability. The complexity of the industry presents challenges for decision-making due to its dynamic nature. It has become more crucial than ever for decision-makers to incorporate expert facts and research into their choices. This study aimed to understand the operating environment of the sawmilling industry and model its complexity. A mixed-methods research approach was employed, involving the gathering of primary data through interviews with personnel in the sawmilling industry, as well as root-cause analysis and system dynamics modelling. Fishbone and causal loop diagrams were used to present and analyse the data. The study generated insights critical for modelling the sector's complexity, enabling an understanding of how the factors influence each other and impact decision-making in the sawmills. The industry has the potential to gain and sustain its competitiveness by focusing on the key factors affecting the complexity of operating a mill and those faced by the industry. Sawmillers can use the findings to examine their processes, identify areas for improvement, and assess potential implications. Other industry stakeholders can also utilise the results to identify ways to enhance the industry's competitiveness and inform the government's industrial policy on sawmilling in South Africa. A limitation of the study was the lack of input from representatives of informal sawmills. Future research will focus on understanding the issues affecting small-scale and informal sawmills to determine how they can be supported in contributing to the industry's sustainability.

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