The global mining industry is at a crossroads. As we face rising costs, toughening environmental scrutiny and shifting workforce dynamics, the question on every leader’s mind should not just be about how to survive, but how to thrive, and what their operation needs in order to do that.
The answer? Data. Harnessing and leveraging data effectively – and rapidly, when it is needed the most - will determine who leads and who lags in this evolving landscape. The real time insights you need, to deal with increasingly difficult real world challenges.
The Cost of Inefficiency in Mining
Drilling inefficiencies are one of the largest and most overlooked drains on a mining company’s budget. Not only do these inefficiencies strain budgets, but they also disrupt planned drill programs, reducing the total meters companies can achieve. Depending on the operation, the financial loss from inefficiencies can range from $20,000 to $250,000 monthly per rig. Globally, this adds up to billions in wasted revenue every year—a staggering number that highlights a fundamental issue: most mining companies simply don’t know what to do with the data they already have.
Mining operations today generate an incredible amount of data from IoT devices, sensors, and digital systems. Yet, much of this data sits unused, trapped in outdated processes and misunderstood by teams unprepared to make data-driven decisions. Or becomes available so slowly or sporadically that is it all but useless. The opportunity cost of this untapped potential is enormous, both financially and strategically. We see it as the role of Krux to bring these missed opportunities to the forefront and offer actionable solutions.
The ‘Lightbulb Moment’: Unlocking Profit Hidden in Data
I’ve seen firsthand the transformation that occurs when a company embraces data. That “lightbulb moment” happens when leaders realize the millions of dollars sitting untapped in their systems. It’s not just about understanding the numbers; it’s about reviewing the data and asking yourself the right questions.
For example, an enterprise mining company we worked with improved their operational efficiency by 40% simply by integrating real-time analytics into their workflows. They were able to identify standby issues caused by their operations and realized that one of the drills within the blast area took too long to move, often getting caught. By switching that rig to different holes and assigning a faster rig to drill the ones closer to the blast, they significantly improved efficiency. This meant faster decisions, optimized resource allocation, and achieving the required drilling program meters more consistently. These stories are not rare—they are the new standard for companies willing to adapt.
Overcoming Resistance to Innovation
Despite these benefits, many mining companies remain hesitant to adopt new technologies. Why? Because the problems seem “not big enough” to demand immediate attention. Leaders tell themselves there will always be time to adapt later. But by the time “later” arrives, competitors will already have taken the lead.
It’s time to break the cycle of doubt and hesitation, along with the misunderstandings that hold companies back from innovation. We have demonstrated, time and again, that even marginal changes to data utilization can lead to significant gains in productivity and profitability.
Data-driven Mining Can Break With Tradition to Bring New Levels of Excellence
Across the mining industry I have seen how traditional methods, while familiar, have limited growth and efficiency. With even minor adjustments in data collection and analysis, mining operations can revolutionize their output and profitability.
Imagine eliminating standby time for rigs, improving resource allocation, and reducing environmental impact through better planning? These are not distant dreams but achievable realities. By leading the charge in adopting data-driven approaches, mining companies can redefine the industry’s benchmarks for sustainability, efficiency, and profitability on a global scale.
Sustainability and Data: A Perfect Match
Data doesn’t just optimize operations; it also improves drilling energy efficiency. By analyzing engine outputs and emissions, companies can measure and reduce the energy required to drill a hole. Real-time data can highlight inefficiencies in rig performance, allowing adjustments that lower fuel consumption and emissions while maximizing productivity.
Additionally, tracking water usage through data analytics has become an essential practice for modern mining companies. By monitoring water use in real time, companies can identify wasteful practices, implement recycling processes, and ensure compliance with sustainability regulations. Together, these data-driven approaches not only enhance operational efficiency but also position mining companies as responsible leaders in their field.
Preparing for the Next Generation of Miners
The current generation of miners and geologists, seasoned by years of on-site experience, is nearing retirement. Their successors will rely more heavily on technology than ever before, spending less time in the field and more time analyzing data to drive decisions. For this new workforce, embracing data-driven tools is not optional—it’s essential.
This generational shift is an opportunity for the industry to redefine itself. By equipping younger workers with advanced analytics and real-time insights, mining companies can ensure continuity of expertise and maintain competitiveness in a demanding global market.
What We Do at Krux
I firmly believe that Krux Analytics is helping companies revolutionize their drilling operations. Our software allows drillers to capture and analyze field data in real time, optimize performance, and improve client communication. The results? Faster invoicing, more accurate budgeting, and sustainable operations that maximize returns.
But this conversation is bigger than any one product. It’s about a mindset shift—a commitment to innovation, efficiency, and growth. Let’s make 2025 the year we stopped wasting potential and started mining smarter.