Development of a Maturity Scale for Mining Performance and Maintenance Data Analytics

Abstract

Data analytics is the science of examining raw data with the goal of discovering useful information, reaching conclusions about the meaning of the data and supporting decision-making. The main opportunity that data analytics presents for mining is its potential to identify, understand and then guide the correction of complex root causes of high costs, poor process performance and adverse maintenance practices. These root causes may be invisible to simple analysis or reporting methods. Data analytics can, therefore, reduce costs and accelerate better decision-making, which ultimately enables new products and services to be developed and delivered, creating added value for all.
The purpose of a maturity model is to provide a guided benchmarking tool for a mining company to assess the development and progression of its own data analytics programs. A self-assessment allows a mine manager, for example, to determine at what level of maturity their organization is operating – and in what areas and by how much they should progress and improve.
Ultimately, this enables mining companies to improve their data analytics capabilities, and to develop intelligence-led operations and maintenance processes, which will improve their bottom line performance.

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