First published in the Digitalist by Ruediger Schroedter
The increase in digital technologies is playing a critical role in mining operations. Smart products are guiding this revolution in how mining firms think about business models.
The mining industry faces several hurdles today, according to IDC. Commodity prices have dropped almost 50% from recent highs. Capital needs and a shortage of talent are driving up operating costs. Productivity has fallen by 3.5% annually over the past decade.
A new frontier
The transformation in mining has begun. (If you’re not sure what exactly that means, see What is Digital Transformation?) Big Data propels faster decision-making. Robotics improve safety and yield. Smart products transmit loads of data. Backroom procedures and reporting are completed in real time.
The new mining business models embrace these changes. The potential improvements and productivity gains are expansive. These models rely on real-time information and collaboration like never before.
As a result, new models are grounded in three areas. For one, mining is becoming more predictable. Second, the industry is more collaborative across the supply chain. Third, automation opens up new markets and yield.
What’s driving change?
The digital drivers of these new models fall into two main categories. The first is the rise of the Internet of Things. (Learn more about the meaning – and opportunity – behind the Internet of Things.) These smart devices are equipped with sensors, software, and wireless tech. The devices can connect with each other and detect, store, share, and send data.
The second is the rise of Big Data. Collection and storage of massive amounts of data is manageable with cloud systems and lower storage costs.
Integrated systems can analyze and report on this data in real time. Data from varied processes are tied together like never before. Decisions are better informed and made faster.
Let’s examine the three core ways mining business models are shifting.
1. Predictable production
In a digitally connected mining environment, the components are deeply integrated.
Imagine a firm where internal departments, shippers, customers, and vendors collaborate from a shared set of data. Documents are exchanged easily and are shared centrally. Some connected machines share data with robust databases. Data from other internal systems combine with production data to create new models. Competitors’ demand and supply data is overlaid.
All this data helps your mining company predict sales and production with more accuracy. Variable factors are included or removed as the situation requires. Production becomes driven far more by demand than in the past. The firm can respond to change and market volatility with greater agility.
2. Collaborative ventures and solutions expand
Collaboration strengthens relationships critical for maintaining high levels of customer satisfaction and retention. These new collaborations can occur within a firm, with customers, and even among competing companies.
Internal systems and analytics will benefit greatly from shared data. Take asset management as an example. Real-time financial data, including customer demand, production and exploration costs, and commodity pricing, can be correlated. Investment decisions, bullish or bearish, can be managed in a far more comprehensible way. Both short- and long-term risks are mitigated. Profitability grows.
Data analysis allows mining companies to buy and sell projects to maximize revenue while maintaining a focus on strategic priorities and core competencies.
Digitized information opens up brand-new service opportunities. Today, individual customer needs can be addressed. Customer-specific solutions, whether in transportation, tracking, inventory control, or safety monitoring are possible. These new services can be sold as separate packages or bundled with product sales. The gathered and analyzed information becomes a new revenue stream for mining firms.
Collaboration with other mining companies is also easier. For example, customers wanting blended grades of product can be served by shared information among competitors. Firms that could not deliver desired blends on their own can still gain market share.
3. Boldly going to new frontiers
The increased use of robots and automation open up new pockets of opportunity. Mining companies can access submerged material. Underwater mining and Arctic exploration are viable and profitable options.
Those pockets of opportunity will be become clearer in traditional mining spaces, too. Answering the question “What’s in the ground?” is getting easier. Automation and analytics are making what had been disjointed processes seamless.
Decisions in resource intelligence improve with collaborative data. The days are numbered for the old ways. Information and processes do not need to be scattered across company departments. Data source and geological model variances can be collected, corrected, and stored quickly.
Miners will have much better insights throughout the production cycle. Ore-body model data, blast-hole drill data, and online sampling are combined in new platforms. Statistical programs allow for better predictive modeling.
The cost reductions and profit opportunities are considerable. Discovery probability leaps higher. Drilling targets are more precise. A central repository for geological information leads to optimal blast and drill patterns. Mine plans are more accurate. Mining operations have less downtime and produce more expected product.
These improvements allow for less or no reliance on older methods such as manual plant assays, core logging, and face inspections.
Preparing to change
New business models require new ways of approaching the work. Companies wanting to reach digital maturity should consider the following actions.
First, be open to experimentation. Work within your organization to identify insights. Share them with stakeholders. Find examples of approaches to digital innovation that worked within mining or in other industries.
Second, prepare for change. A culture of change must be in place for data-driven processes, robotics, and automation to succeed. Leaders need to be willing to change and rethink long-held beliefs and assumptions.
Finally, be bold. Granted, most mining firms have significant sunk legacy capital and data costs. There will need to be an acceptance that innovation requires measured, informed, and acceptable investment and risk.
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