At the peak of the commodity-price cycle in 2010-2012, when most global miners invested in digital technologies such as autonomous haulage or remote operations centres, much of the savings came from reductions in labour costs.

In emerging economies, labour constitutes a relatively small share of total costs, and labour laws put constraints on headcount reductions. So miners in these economies would get relatively low returns on investments in digital tools aimed at reducing the need for manpower.

For this reason, throughput gains have become the primary justification for investing in digital.

But challenges unique in emerging economies limit the efficacy of digital solutions. To illustrate, many Indian miners have to grapple with overly lengthy processes to get land or environmental clearances. And because their mines are relatively small, they have difficulty capturing scale efficiencies and deploying technologies.

Reliable technology vendors and digital talent can also be in short supply in emerging economies - adding to mining executives' scepticism about whether digital could work for them.

Under these conditions, executives must wrestle with questions such as:

• Do we invest in a new dumper to increase capacity and hence throughput? Or should we invest in a fleet management system that uses the same number of dumpers more efficiently?
• Will digital really help unearth costly complexities hidden in our operations so we can eradicate them?
• Will these digital solutions be reliable? What if the algorithm behind a solution is less useful than my years of experience in the job?

Given the challenging circumstances facing mining executives in these economies, many have concluded that material digital benefits are out of reach. This viewpoint is understandable, but also dangerous.

Why? It's a matter of time before digital disrupts mining in emerging economies. To remain relevant, miners must adapt to this reality. We believe they can extract major value from digital, provided they take the right approach. Drawing on our work with mining clients in India and other emerging economies, we've identified three imperatives miners must meet to get the most from digital.

Use digital to complement, not replace, human capabilities

Digital tools are not substitutes for human beings. Rather, they complement them in ways that help miners solve problems of varying complexity. Consider these examples:

• Basic complexity. You are aware of a problem and know how to solve it, but you don't have the data or technology needed to implement the solution. For instance, you've seen workers show up late by as much as 30 minutes during a shift start, and you know you need to track lateness to address it. But you have no means to do so. A biometric-based attendance recording system can help you generate data on trends in arrival times. You can then use the data to incentivise good behaviour (for example, through rewards and recognition) and to take corrective action with those who show up late (such as fines or counselling). A simple, low-cost solution like this can save valuable shift hours, enhancing workforce productivity.
• Intermediate complexity. You have data on a particular problem, but opinions on how to solve the problem vary. To illustrate, crushing-machine operators may have different views on how fast the equipment should be run to optimise yield. Here, machine learning algorithms like random forest or gradient boost methods can churn large volumes of historical operations data, mesh it with data on operator behaviour and input feed characteristics to reveal the right operating regime for your crushing plant.
• Advanced complexity. You have data related to a problem or question, but the solution is too difficult for the human mind to grasp. For example, your mine has numerous dumpers and shovels that keep moving in real time. You want to optimise the allocation of these pieces of equipment to minimise queuing time. A digital twin helps you model this physical system using software and to explore scenarios showing possible throughput gains, so you can select the optimal scenario.

In all of these examples, digital technologies can be seen to be helping people make the right decisions, not replacing them. Once executives understand this and communicate it to the workforce, the company overall will likely become much more open to adopting digital. People can begin identifying business problems using the above complexity levels and select the right combinations of digital and human capabilities to solve them.

Adopt a start-up mindset to digital

To execute chosen solutions, companies should think and act like a start-up, applying these practices:

• Start small and scale up. Large IT implementations can take as long as 12-24 months to show results. So take a different approach that centres on scoring a few early, quick wins. You'll build digital's credibility plus generate measurable business value (such as cost savings) that you can use to fund additional digital initiatives. In one client project we worked on, data analysts came up with new insights in just 4-5 weeks for running the mine's processing plant more efficiently by setting smarter process parameters.
• Put multidisciplinary teams in charge of rapid solution development. To develop robust digital solutions to problems, assemble teams comprising diverse skills—in domains like mining operations, geology, data science, IT and business management. In our experience, the best solutions have emerged when there is a healthy tension between the data scientists challenging conventional operating practices and the operating teams questioning the practicality of insights from analytics. Once both sides are convinced and the business value is proven, all parties take ownership of the solution—which extends its longevity.
• Fail fast, fail often—and learn from every stumble. Not every digital solution will prove robust enough to see the light of day. But those that stumble or fail outright can present important learning opportunities. For example, while trying to improve product yield for a client, we understood that input feed characteristics varied immensely with every new seam mined. Therefore, the machine learning algorithm was constrained by the inability to see sufficient past data to make recommendations. So the team in charge of the solution concluded that physical yield-improvement measures would be more appropriate for this problem than digital, and pivoted to find new physical methods. Smart miners also strive to discover which solutions have worked in other companies and why. They then use the resulting insights to quickly narrow down digital options to what is right for them.

Win the workforce

In all too many mining companies based in emerging economies, the people leading digital projects are restricted to conducting team-building sessions or workshops on how to become a digital culture. These efforts are proving increasingly ineffective, because companies don't track or test application of concepts learned through these sessions.

To extract maximum value from digital, mines must win both the hearts and minds of their workforce. The following tips, drawn from our work with clients, can help:

• Augment classroom learning with action learning. With one client, we identified 20 young people who completed a course on data analytics while also applying their new knowledge to building digital solutions for their company. Participants mastered core concepts of digital technology, such as visualisation and machine learning; tested their knowledge through assessments; and then applied their learning to solve day-to-day business problems.
• See digital, to believe digital. Help executives gain exposure to the latest developments in digital mining, startups operating in this space and recent innovations (such as asset-health monitoring or connected HEMM) led by mining original equipment manufacturers. Immersion visits where executives can witness these technologies in action firsthand are especially valuable.
• Provide on-the-job training. For one client, we trained the user team in data-analytics concepts required to build the digital solution. Armed with this knowledge and their plant-operations experience, team members were able to deploy the solution at another plant—on their own. Result? Members felt a strong sense of ownership of and commitment to the technology. This enhanced the odds that the solution they created would live on in the company instead of getting abandoned on a shelf to gather dust.

Miners in emerging economies have understandable reasons for questioning whether digital technologies and tools can pay dividends for them. But it's inevitable that digital will transform their industry.

To ease their qualms, these miners should take a practical approach to deploying digital to generate measurable business value.

Using digital to complement human capabilities, adopting a startup mindset to digital and winning over the workforce can all help miners stay ahead of the digital transformation curve - versus getting left behind.

Amit Ganeriwalla (Ganeriwalla.Amit@bcg.com) is a managing director and senior partner at BCG, based in Mumbai. Saibal Chakraborty (Chakraborty.Saibal@bcg.com) is a managing director and partner at BCG, based in New Delhi. Saurabh Harnathka (Harnathka.Saurabh@bcg.com) is a project leader at BCG, also based in Mumbai.