Sharing thoughts on Analytics

Andries Loubser, Director for Enterprise Solutions at MineRP shares his view on Mining Optimization and Analytics in the light of the 2015 SAIMM conference.

I recently had the opportunity to speak at the SAIMM Optimisation Conference on opportunities for improvement in mining operations using MineRP and IBM technology. The conference attracted representatives from top companies within the mining industry from precious metals to base metals, consultants, technology providers as well as owner operators. I believe the South African mining industry has great potential to benefit from optimisation principles and tools to bring about stability, improvement and associated confidence to the market. Mines seek confidence in the choices they make in long and medium term planning. There are better decision processes than to guess at capital scenarios, such as prioritised and scientifically calculated options to lead them towards the correct choice of execution plan and investment to increase the value of their mining projects.

Organisations function at different levels of maturity, and as such would not all benefit from the same approach to optimization. Approaches to optimization and analytics can be based on three distinct levels of maturity:

Descriptive analytics focus on performance monitoring and describing what has happened in your business. This type of analytics is invaluable as a management tool and therefore will always form the first step of any optimization process.
Predictive analytics look into the future and tell us what scenario is most likely to play out based on past experiences, or mathematical models, or a combination thereof.
Prescriptive analytics address the most appropriate plan of action to achieve a certain desired state, or avoid a predicted negative outcome. MineRP’s approach to optimization encompasses all of three these levels of optimization, yet allows mines to only implement that level which is appropriate to their need and readiness.

Go ahead and look at MineRP's and IBM's web material on the subjects for more information.