Everyone acknowledges that Digital is a big opportunity for the mining industry. However, people disagree on what form the opportunity takes. Although Digital has driven Business Model Disruption across multiple industries, we don’t see an opportunity like Uber or AirBnB to reinvent the mining industry. The act of extracting ores from the earth and refining them into useful metals demands a certain scale that makes it hard for new entrants to completely reinvent the industry. While portions of the business system may be reinvented, we see the biggest opportunities for Digital in streamlining the operational model that already exists. In the future, there could be huge value in an unmanned mine, but for the moment there are real gains to be made by enabling the people in the mine to work smarter and faster, in better alignment with the whole operation. There is a long list of technologies that fit the bill-- automation, new analytic capabilities, digital workers, remote and autonomous operation, et al.—and we’re working with clients on many of them. But they have one thing in common—they are in some degree of conflict with the traditional working norms of the industry, particularly the norms of Supervisors.
Historically, Supervisors were promoted to their jobs because of a blend of experience, skill, leadership, local knowledge, pattern recognition, and ability to act quickly to resolve emerging issues (a/k/a firefighting). They tended to be men with some grey hair who had spent their career in the mine and forgotten more about the mine then most of the other folks ever knew. In a world where information came in from underground once every 12 hours at the end of shift, the sort of tacit knowledge they had was invaluable. Data and analysis were hard to come by, so the most valuable management asset was intimate knowledge and vast experience.
In the new world, data and analysis are cheap and ubiquitous. A Supervisor no longer has to depend on experience-based pattern recognition, he has access to reams of data and real-time analytics. Experience and know-how are still a valuable commodity, but Digital technologies have made the ability to quickly digest, understand, and react to incoming data a key differentiator between ‘the good’ and ‘the great’ supervisor.
Does that mean we can replace Supervisors with algorithms? Of course not. At the moment, automation does not appear to be infinite. It is constrained by what economists call Polanyi’s paradox. Named after Karl Polanyi, who in 1966 observed “We know more than we can tell,” the paradox refers to the difficulty in automating an activity that we only understand tacitly: Painting a picture, writing a persuasive argument, or dancing are all tasks that even people who are highly proficient in them are not fully able to describe. We cannot program what we cannot understand. True, there is evidence that machine learning capable of “understanding” such tasks tacitly might eliminate this hurdle, but for the time being, professions that require flexibility and creativity are quite resistant to obsolescence.
A lot of the debate around automation ignores the fact that most of it is partial—that not all of the work is taken over by machines. In fact, only one of the 270 occupations listed in the 1950 census has been eliminated thanks to automation: elevator operators.
Fewer than 5% of jobs in the US could be completely automated using current technology. This is an important distinction. If a job is completely automated, then jobs will indeed ultimately be eliminated. We all are getting comfortable with that. But if the process is only partial, employment for that job may in fact increase because of the efficiency gains and possible effects on demand. It’s also worth noting that fewer than 5% of jobs in the US could be completely automated using current technology.
David Autor, professor of economics at MIT, adds that the remaining tasks “tend to become more valuable.” Automation usually takes over repetitive, tedious tasks, leaving professionals more time to do the things that really require their skills. For instance, automation will help mortgage-loan officers spend less time processing paperwork and free them up to issue more mortgages. Similarly, automated diagnostics in health care would allow emergency rooms could combine triage and diagnosis, letting doctors focus on special cases, increasing the number of patients being treated overall.
So what does that mean for Supervisors? We find that there are 4 main categories of decisions that mining organizations need to make to bring the emerging digitally enabled Supervisor role into focus--
• Who makes the decisions – the Supervisor on the ground, or the leader of the remote operating center? Knitting the mine together digitally is a process, not an event, and depends on getting four building blocks in place—Hardware, Software, Systems, and Behaviors. As the mine gets more integrated, the locus of decision-making will inevitably shift to the location with the best set of information. In the early stages of integration, that means the decision is made in the same place. However, as systems and hardware allow better information flow to more places, that locus may change.
• What behaviors should a miner and a Supervisor follow when their handheld rather than their eyes are identifying the problem areas in the mine? One of the most exciting, but most disruptive elements of digital technology in the mine is the ability for people not at the headings to deliver insights in real-time. The Supervisor still is the closest person to the heading, but other people may know more than him about a specific opportunity or problem. However, this is nothing new— Geologists, Engineers, and Metallurgists have always been part of the team, and know more about their disciplines than a Supervisor does. Teamwork has always been critical to the mine. Digital has two principal effects here—it simultaneously enlarges the team, and gives everyone the same data set in real-time. Teamwork is hardly a new concept at a mine, but the way the team interacts will change—the team will be bigger, there will be more data to analyze, and faster ways of analyzing it. How the team chooses to do that depends on the makeup of the team and the tools, but the dynamics of the team are changing.
• What skill set do you want from your Supervisors? Mining experience or data analytics? The answer of course, is not binary. The proportions depend on the specific situation, but the key skills we see in the most successful Supervisors in the new era include two familiar skills and one new one. No one will score perfectly on all three, but all three will be required.
– Mining Experience and Judgement: Mining is hard, technical, and dangerous. A Supervisor needs to deeply understand the forces at work underground.
– Leadership and Teamwork: A Supervisor is leader of a team and must inspire a team to do hard, dangerous things.
– Not Digital Expertise, but Digital Openness— No one thinks a Mining Supervisor should be writing code. But he does need a willingness to accept insights from the data analysis, even though it may be in conflict with established norms. There is an element of humility, and of accepting that he is not the only smart one in the mine.
• Why will it be different this time? The industry has a poor track record getting benefits from stable technologies such as oil and vibration analysis. However, these technologies were usually isolated in one area of the business system. Digital Transformation means transitioning to a system that offers benefits to specific departments (e.g., Collision Avoidance underground) as well as new opportunities that cut across multiple departments (e.g., Remote Operating Centres). Digital enables a long list of options, and not all of them have to pay off in order to create value. And the set of solutions is only going to get richer. Some mines, particularly those near end-of-life, will not get the digital investment (and that may be a rational choice). Another set will get significant digital investment, while others will get more constrained investment. The requirements for a Supervisor need to be tailored to the specific mine and the specific degree of digitalization.
Digital will drive changes in most mines’ operating models. And that means the Supervisor’s job is going to change significantly. Leading a team to achieve stretch results in dangerous conditions is hard enough without changing the operating model. Organisations who have a clear-eyed view of how specifically the job is changing will have a big advantage in attracting and retaining the talent they need to drive results every shift, every day.