Abstract
The growing availability of information and data analysis capabilities of recent years provides new opportunities for improving the performance of mining operations. By using real-time measurements and artificial intelligence, it is possible to respond faster to changing conditions, while accurate and timely information permits rapid evaluation of changes and fast business improvement decisions. This article presents a blueprint for alignment of systems, organizational design, and management practices to leverage these developments in performance-driven operations management in mining and mineral processing. The first component of the blueprint is a performance framework with a system of key performance indicators for production control that can be used across organizational levels. This system places improvement at the core of management activities, giving greater importance to improvement skills at lower organizational levels, so companies can leverage available information for improving operational control. Secondly, the blueprint defines an organizational structure that strengthens performance improvement with technological and change management capabilities. Finally, the blueprint proposes alignment of management practices, covering the optimization of short-interval controls, the application of an improvement project portfolio management system that determines the ownership of improvement projects, and the coordination of controls across the organization. This combination of systems, organizational design, and management alignment supports rapid decision-making at the right organizational level. Introduction of the presented blueprint for operations management enables mines to leverage the developments in information and analysis capabilities to improve the performance of operations.
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I thank Terry Briggs and Johan van Huyssteen for their insights and useful discussions on the topic of operations management.
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Visser, W.F. A Blueprint for Performance-Driven Operations Management. Mining, Metallurgy & Exploration 37, 823–831 (2020). https://doi.org/10.1007/s42461-020-00199-5
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DOI: https://doi.org/10.1007/s42461-020-00199-5