Gone are the days in mining when assessments of potential dig sites meant lots of waiting for results. Gone, too, is the uncertainty on a mine job about where to go next.
For mining executives, recent advances in digital technology allow companies to make decisions at a rapid pace. Decisions that used to take days and weeks now can be done in minutes and hours.
With more information available faster, mining leaders reduce both short- and long-term financial risk. Data from across the enterprise inform decisions about buying and selling assets. Profitability should increase, driven by key technology advances.
Digging in to the data
There are two key drivers to this digital revolution. The first is the rise of the Internet of Things (IoT). The IoT consists of devices that are equipped with sensors, software, and wireless capabilities. These devices are connected to each other and can detect, store, and send data.
The second is the rise of Big Data, mobile, and cloud computing. Today’s mobile devices can track, send, and receive data from remote sites worldwide. Cloud computing stores billions of bytes of data at low cost. Big Data analytics programs take data coming from many different locations and systems and synthesize it. Those programs then better inform decisions by offering dashboards, metrics, and predictive modeling.
Robots are able to venture into hazardous areas and move material with remote human oversight. On-site mining data is sent via mobile phone to a cloud-based platform. For mining, the convergence of these technologies provides extraordinary possibilities.
Technology at play
The potential impact is significant. A recent report by McKinsey & Co. showed the use of advanced analytics in mining and related industries had a major impact. Firms using these programs to assess production areas increased their profit margins by 2-3 percentage points.
One mining company used so-called Monte Carlo simulations to reduce certain capital expenses. Monte Carlo simulations use complex algorithms and repeated random sampling to model possible outcomes. They’re frequently used in finance, biology, and insurance. The Mining Journal reported how the company challenged assumptions about a project’s capital needs. It took historical data on certain disruptions such as rainfall patterns. Then models of its mines were made showing the impact of flooding and rainwater. The data led to a new strategy that maximized storage capacity and handling across all its mines. Capital costs dropped by 20 percent.
Buy or sell?
With so many variables at play, mining valuation is not for the faint of heart. Integrated data streams available at the discovery stage make for better informed purchase decisions.
Software programs today can take data to build and validate exploration models. These programs use 3D visualization and validated geophysical, analytical, and drill hole data. In turn, detailed 3D topographical models are possible.
Other programs assess historical, assay, and drilling data. This information creates viable scenarios for determining whether to buy or sell a site.
These tools use data consistently from one potential site to the next, allowing for forecasting of economic risk that is consistent across the organization. The firm today can use “real options valuation” to develop models of outcomes given changing economic conditions. With clearer information about potential risks, firms can decide whether to stage, sell, abandon, expand, or buy.
Anticipating, not reacting
Mining companies realize today that these analytic platforms and dashboards offer many advantages. Users have a clearer interpretation of the aggregated and analyzed data points from multiple areas. Using predictive analytics, mining decisions are made based on smart assumptions, not past historical information.
Robust software programs can generate reports almost instantaneously. Supervisors have on-site access to the analysis through a web browser or app. This data has many uses. Drilling managers save time and can make quicker decisions on next moves. Supplies can be ordered faster. Needed data for accreditation and compliance is immediately accessible.
Selecting the right sites
One example is assay analysis. Today, geologists do not wait weeks or months for assay results. Instead of off-site analysis, web-based applications deliver information much faster to inform decisions.
Robots are sending information about field operations, safety, needed maintenance, and drilling performance. Some devices send the information themselves. In other cases, staff use mobile phones, tablets, or laptops. This information and analytics in turn help with site selection. Integrating data from mine planning, ventilation, safety, rock engineering, and mineral resources improves overall forecasting.