At R&O ANALYTICS we understand the importance of mine project evaluation for mining firms (and other companies) investing in mineral assets when making final go/no-go investment decisions. Every mining business/project faces unique and complex problems arising throughout the project life; one of these being the uncertainty in future operational and economic variables, such as prices, grades, qualities, and costs.
We also understand that mining organisations that don’t cope with chance and uncertainty, and don’t use analytics and optimisation techniques within the evaluation process are relying more heavily on instinct to make critical final decisions. The result of this practice tends to be more subjective, spurious, lack rigor and producing poorer outcomes.
Data analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information. Data analytics is used in the mining industry to allow companies and organisation to make better business decisions based on verified information. Data analytics is distinguished from data mining by the scope, purpose and focus of the analysis. Data miners sort through huge data sets using sophisticated software to identify undiscovered patterns and establish hidden relationships. Data analytics focuses on inference, the process of deriving a conclusion based solely on what is already known by the researcher.