Slow build can enhance mining's digital future

When it comes to digitisation, forward-thinking mining companies have already made their first steps, learned lessons and achieved impressive results. Outcomes have included improvements in project net present value, equipment utilisation and availability, and plant productivity.
Slow build can enhance mining's digital future Slow build can enhance mining's digital future Slow build can enhance mining's digital future Slow build can enhance mining's digital future Slow build can enhance mining's digital future

Andrej Timofeev, Mikhail Volkov and Mikhail Moguchev*

Indeed, digital tools and technologies can be - and are being - deployed in a range of mining operations (see figure 1, below).

These solutions are aimed at not just addressing key pain points but also seizing value-extraction opportunities. Even if a company chooses to focus its digital efforts on only a few select areas, it can see tremendous impacts on performance.

Spotlight on AI/AA expert systems

Expert systems using artificial intelligence (AI) and advanced analytics (AA) are an especially notable example of how digital tools can help enhance recovery and productivity in processing plants. These solutions have been actively developed in many industries, including mining. Moreover, many tools are now available on the market to implement AI and AA across all elements of the mining value chain. In particular, these technologies can be used to boost the efficiency of geological exploration work, which delivers cost reductions and improves forecasting accuracy; to optimise blasting patterns, further decreasing costs and improving fragmentation management; and to improve performance at processing plants and metallurgical production sites.

Boston Consulting's experience with clients in the mining industry indicates AI/AA expert systems can deliver benefits on several important fronts. Specifically, such systems can:

  • Improve decision-making and process management as well as foster constant upskilling by incorporating experiences amassed by all operators in the system's recommendations.
  • Standardise approaches to managing processes that may vary greatly among operators of individual installations and that depend on personal experience.
  • Foster transparency and accountability in process management, because operators know that their actions are recorded and can be compared with the expert system's recommendations.

Expert systems don't replace human beings; rather they empower people to manage processes and operations more effectively and efficiently. To get the most from such solutions, companies may have to build new internal competencies centred on designing, developing and maintaining AI/AA tools.

Prompter systems to improve process management

BCG worked with a large Russian company to define a digital transformation vision emphasising use of advanced analytics. The company launched six pilot projects, selected based on criteria such as their expected economic impact, availability and quality of data, and level of support from shop managers. Most of the pilot projects are expert systems or prompter systems (figure 2, below). They generate real-time prompts for operators and process engineers on how to properly steer the production process and get better outcomes.

The projects have already delivered impressive results, including a 3%-5% increase in output and 1%-3% decreases in baseline costs.

Importantly, the company knew it also needed to build internal capabilities for in-house development and support of these solutions. To that end, it set up a major training programme centred on disciplines including data science and agile product development.

 

Avoiding common pitfalls

Despite individual examples of successful digital initiatives, the mining industry overall is still in a relatively early stage of digitisation, compared with industries like telecommunications and financial services. Therefore, leaders have a chance to reap more benefits from digital innovations. We believe they can best seize this opportunity by learning from each other's experiences and avoiding mistakes made by their predecessors. Common pitfalls include the following:

Being blinded by technology hype. The digital world offers many exciting solutions—drones, exoskeletons, robotic equipment, digital twins, image recognition systems and more. To avoid getting caught up in (and possibly blinded by) the hype, remember that these solutions are meant to unlock new value. In discussions with vendors, make sure every solution is backed by a specific business case and clearly identifies the ‘pain point' or new value-creation opportunities the tool is meant to address.

Letting the IT department drive digitisation without involving the business customer. If production managers are skeptical of digital solutions' value, explain the benefits of using the systems. Launch pilot projects to demonstrate the solutions' value, and involve production employees in these projects.

Neglecting to ‘hardwire' new processes or train personnel. Digital solutions may be successfully implemented in technical terms, but they won't deliver the hoped-for value if you don't also adjust business processes affected by the solutions or train people to use them correctly. Indeed, successful implementation of digital solutions depends far less on technology than on the quality of process and change management efforts a company makes (figure 3, below).

Overcoming obstacles to scaling

Even companies successfully piloting digital tools now must find ways to consistently scale them across their operations. Otherwise, they may get mediocre returns on their investments in these solutions. To support such scaling, the following is recommended:

Focus on value creation. AI and AA is a tool for improving process efficiency, and should be tailored to address value losses that production personnel experience every day. It's impossible to identify, develop and sustain successful AI/AA and other digital solutions without first gaining production personnel's buy-in. The lesson? Make business-owner onboarding a priority in all digital initiatives.

Think and act like a startup. With every digital project, strive to overcome traditional corporate principles that can hinder innovation--such as overly complex approval processes and a too-narrow focus on achieving specific predefined results. Balance the effects of these principles by applying principles more commonly practiced in startups--such as fast decision-making and a willingness to learn from failures. 

Put the right talent in place. Finding data scientists willing to work in far-flung locations under harsh conditions can be a daunting task. In addition to bringing in digital talent from outside, miners must build internal competencies in unfamiliar disciplines and train a wide range of employees if they hope to overcome ‘digital skepticism' in their organisation. To meet these imperatives, consider creating centralised hubs in big cities with broad access to job seekers who have needed skills and expertise. Provide training for current employees on how to work with digital tools. Additionally, keep workers informed about the digital projects the company is implementing and the results those projects are generating, to further foster an organisational culture that's comfortable with digital.

Rethink ‘patchwork' IT architecture. In many mining companies, automation and other digital approaches are fragmented and ‘patchy'--not always based on state-of-the-art integrated solutions. This patchiness can erode data quality, rendering solutions heavily reliant on data (such as AI/AA) less effective. To blunt this impact, start experimenting with digital technologies for which the company has a minimum sufficient level of automation and digitised data. Take on more ambitious tasks later, when they can be synchronised with the automation steps already taken.

Collaborate effectively with the digital ecosystem. To use digital tools at scale, proactively partner with participants in the digital ecosystem--including vendors, startups and relevant higher-education institutions. Most advanced technology solutions have a short lifecycle from idea to product, followed by iterative development of more sophisticated functionality and features. To stay abreast of advances in technology, consider developing your own venture capital funds by forging strategic partnerships with universities and centres of innovation.

Mining's relatively slow pace in adopting digital tools and technologies presents an opportunity to learn from mistakes made in other industries that moved more quickly on the digital front. By understanding digital's potential benefits as well as common pitfalls and scaling challenges, mining companies can sweeten the odds of extracting maximum business value from digital solutions - not just today but also far into the future.

*Andrej Timofeev (Timofeev.andrej@bcg.com) is a managing director and senior partner at BCG; Mikhail Volkov (Volkov.mikhail@bcg.com) is a managing director and partner at BCG; Mikhail Moguchev (moguchev.mikhail@bcg.com) is a managing director and partner at BCG.