The unprecedented demand for natural resources drives mining companies to strive for a step-change in optimizing their business processes. Advanced analytics techniques are being applied in other industries to enable significant improvements in strategic and operational business processes by optimizing decision-making. This chapter looks at how these advanced analytics techniques can be used to the mining industry’s fundamental challenges. Today, decisions are usually locally optimized but do not achieve optimum capability for the mine value chain. Although mining operations now collect more information than ever before, it is difficult to bring all this information to bear to make better decisions. For example, plant history, maintenance, mine planning, logistics, and engineering data are rarely all bought together, in real-time, to make better operational decisions. Complex analysis of data is time-consuming and requires specialist skills and knowledge, and is often neglected in the decision-making process. By contrast, advanced analytics will close the loop between analyzing data and taking action. Using analytics to make better decisions will not require specialist skills or be time-consuming, and analytics will become embedded in the business and routinely applied to improve decision making across all organization levels, from senior management to operations and maintenance workers. Embedding analytics in the business processes drives better decisions supported by data, integrated in real-time from many sources. Ultimately, predictive tools will help suggest, or even in some cases automate, courses of action. The main opportunities for analytics exist where the enterprise requires supporting
technology to continue evolving to a higher maturity level. This will be in asset management, rapid reconciliation and adaptive planning, and the inbound and outbound supply chains. Advanced analytics is also a key enabler for increasing the effectiveness and realizing Remote Operations Centers’ actual value to safely and efficiently support operations in remote locations with smaller workforces. This chapter focuses on using advanced analytics to develop prediction, optimization, and decision technics through the mine value chain.