Why Most Innovation Programs in Mining Fail—And What to Do Instead

Discusses innovation as a organizational capability and looks at how a capability program might be designed.

Every major mining company now has something it calls an innovation program. Some have innovation labs. Others have venture funds, digital transformation offices, or partnerships with technology accelerators. A few have all of the above. And yet the results, in aggregate, are disappointing. Most digital investments generate less than one-third of their anticipated impact, according to McKinsey research. Only about 5 percent of companies across industries attribute at least 10 percent of their EBIT to generative AI. The pattern is familiar: ambitious launch, early enthusiasm, a handful of promising pilots, and then a slow fade as attention shifts to the next priority and the organization reverts to its default behaviors.

This is not a technology problem. It is a capability problem. And until mining companies treat it as such, they will continue to cycle through innovation initiatives that deliver temporary excitement but not lasting value.

The pattern of failure

The failure modes of innovation programs in mining are remarkably consistent. Understanding them is the first step toward designing something better.

Isolated pilots that never scale. The most common pattern. A team identifies a promising use case, predictive maintenance, grade optimization, autonomous drilling, and runs a successful pilot at a single site. The results are encouraging. But translating that pilot into standard practice across multiple sites, with different equipment, different data systems, and different operational cultures, proves far harder than anyone anticipated. The pilot becomes a permanent experiment, celebrated in annual reports but never integrated into how the company actually operates.

Innovation functions disconnected from the core business. Many companies establish dedicated innovation teams or labs, often physically separated from operations. These teams may do genuinely interesting work, but they operate at the margins of the organization. They lack the authority to change operational processes, the credibility with frontline workers to drive adoption, and the integration with business planning cycles to ensure their work aligns with strategic priorities. As BCG has observed, a company in a process-heavy industry like mining might find it reasonably easy to develop lean capabilities for existing processes, but struggle to implement new digital capabilities that require fundamental changes in skills, technology, and daily behaviors.

Technology-first thinking. A vendor presents a compelling demonstration. An executive is impressed. A purchase order is signed. But the organization has not assessed whether it has the data architecture, the process maturity, or the human capability to absorb the new technology. The result is an expensive system that sits underutilized because the organizational context was never prepared for it.

Short-termism in measurement. Innovation, by its nature, involves uncertainty and long time horizons. But mining companies accustomed to measuring performance against quarterly production targets often apply the same evaluation frameworks to innovation initiatives. When a project does not show clear ROI within a year, funding is cut, the team is reassigned, and the organization concludes that "innovation doesn't work here."

Leadership turnover and attention drift. Innovation programs depend heavily on executive sponsorship. When the sponsoring executive moves to a new role, the program loses its organizational protection. Without sustained leadership commitment, innovation becomes one more initiative competing for attention in an organization that is already stretched thin.

What a capabilities approach looks like

The alternative to episodic innovation programs is building innovation as an organizational capability—a durable, systematic capacity to identify, develop, and scale new ways of operating, rather than a series of disconnected projects.

This distinction matters. A capability is embedded in how an organization works: its processes, its decision-making structures, its talent, and its culture. A program is an overlay that can be added and removed. The difference is the difference between an organization that occasionally innovates and one that innovates reliably.

Research on innovation capability building, including longitudinal studies of mature firms in the automotive industry, identifies several consistent elements of organizations that successfully develop this capacity.

A clear strategic link

Innovation capability starts with strategic clarity. What specific problems is innovation meant to solve? What competitive advantages is it meant to create? What time horizons matter?

In mining, these questions have distinct answers depending on the company's position. A company facing declining ore grades needs innovation that improves recovery and processing efficiency. A company expanding into new geographies needs innovation in remote operations and community engagement. A company positioning itself for the energy transition needs innovation in electrification, emissions reduction, and materials supply. Without this strategic anchor, innovation efforts diffuse across too many priorities and deliver against none of them.

McKinsey's research on mining operational excellence underscores this point: the outperforming organizations share a clear sense of purpose that connects daily work to broader strategic objectives. When employees understand why innovation matter, not as an abstract corporate aspiration but as a concrete response to specific business challenges, engagement and adoption follow.

Dedicated but connected organizational structures

The research consistently shows that breakthrough innovation requires dedicated teams with the mandate and autonomy to explore beyond the constraints of the existing business model. But—and this is where many mining companies go wrong—those teams must also be deeply connected to the core business. They need access to operational data, relationships with frontline workers, and integration with capital planning processes.

The effective model is neither a fully autonomous innovation lab nor innovation as "everyone's job." It is a dedicated function that operates with different governance, timelines, and risk tolerances than the core business, but is structurally linked to operational leadership and strategic planning. Think of it as a bridge between the organization's current operations and its future possibilities, firmly anchored on both sides.

Capability building at multiple levels

Innovation capability is not just about having skilled innovation professionals. It requires capability building at three levels:

Executive capability. Leaders need the ability to evaluate innovation portfolios, make resource allocation decisions under uncertainty, and protect long-term investments from short-term pressures. This includes developing fluency with emerging technologies, not the technical details, but enough understanding to ask the right questions and make informed strategic choices.

Middle management capability. This is often the most critical and most neglected layer. Middle managers are the primary mechanism through which organizational change either happens or stalls. They need the skills to support innovation within their teams, translate strategic innovation priorities into operational plans, and manage the tension between current performance demands and future capability development. McKinsey's operational excellence research specifically highlights the role of leaders who ensure management practices build people's capabilities.

Frontline capability. The people closest to the work often have the deepest insight into operational problems and improvement opportunities. Building their capability to identify, test, and implement improvements, supported by appropriate tools and governance, is what distinguishes organizations that achieve sustained performance improvement from those that plateau after initial gains.

Portfolio management, not project management

A capabilities approach treats innovation as a portfolio, not a series of individual projects. This means maintaining a deliberate mix of initiatives across different time horizons, risk levels, and strategic objectives, some focused on near-term operational improvement, others on medium-term capability development, and a few on longer-term transformational opportunities.

Portfolio management requires different evaluation criteria at different stages. Early-stage exploration should be assessed on learning and strategic alignment, not financial return. Later-stage development should demonstrate clear pathways to operational integration and value creation. The mistake many mining companies make is applying a single evaluation framework, typically one designed for capital projects with well-defined parameters, to all innovation activities, regardless of their maturity or strategic intent.

Governance that enables rather than constrains

Innovation governance in mining often defaults to the same approval processes used for capital expenditure or operational changes. These processes are designed to manage risk in well-understood contexts - exactly the opposite of what innovation involves. The result is that genuinely novel ideas are either killed by requirements for certainty that cannot yet exist, or distorted to fit evaluation templates designed for a different purpose.

Effective innovation governance creates distinct pathways with appropriate oversight at each stage. It establishes clear decision rights, so teams know who can approve what and under what conditions. It builds in structured checkpoints without requiring premature precision. And it creates mechanisms for escalating promising ideas and, equally importantly, for stopping work that is not progressing.

Measurement that matches the reality of innovation

The measurement challenge deserves particular attention. Standard business metrics, (cost savings, production increases, ROI), are important but insufficient for evaluating innovation programs, especially in their early stages.

A more complete measurement framework includes:

Input metrics: Are we investing sufficient resources? Do we have the right talent? Are we generating enough ideas from diverse sources?
Process metrics: Are ideas moving through the pipeline at an appropriate rate? Are we making timely decisions? Are we learning from failures?
Output metrics: What has been implemented? What operational changes have resulted? What value has been created?
Capability metrics: Are our people developing new skills? Are our processes improving? Is our organizational culture becoming more supportive of experimentation?

The discipline of measuring innovation capability, not just innovation output, is what distinguishes organizations that build sustainable advantage from those that achieve temporary results.

The mining-specific context

Several characteristics of the mining industry make capability building both more challenging and more important.

Physical constraints. Mining operates in physical environments that limit the pace and scope of experimentation. You cannot A/B test a blast pattern the way you A/B test a marketing email. This means innovation must be more carefully designed, more thoroughly simulated, and more deliberately staged than in less physically constrained industries.

Long capital cycles. Mining investments have 20- to 50-year horizons. This creates both a challenge, the inertia of existing assets and processes, and an opportunity. Companies that build strong innovation capabilities today will have decades to compound the benefits. Those that do not will be locked into increasingly outdated operating models.

Workforce dynamics. Mining faces persistent and compounding talent challenges. The number of universities offering specialized programs in areas like geotechnical engineering and mining engineering has declined, driven in part by a younger generation that prioritizes meaningful and flexible work over traditional remunerative benefits. A Mining Industry Human Resources Council survey found that 42 percent of respondents aged 15 to 30 said they would "definitely not" consider working in mining—the highest rejection rate of any sector surveyed. Meanwhile, a significant proportion of the existing mining workforce is approaching retirement, creating a loss of institutional knowledge that has not been adequately transferred. As Hossack et al. (2025) document, these factors are compounded by increasingly stringent regulatory frameworks and the growing technical demands of new monitoring and analysis technologies, which require larger and more skilled teams than many organizations currently have. Deloitte (2022) research cited in their work reinforces the business case: organizations that prioritize skills investment are 98 percent more likely to retain high performers and 52 percent more likely to innovate. An innovation capability program that gives people meaningful opportunities to develop new skills and work on consequential problems is not just a nice-to-have. It is a talent strategy and a risk management strategy simultaneously.

Distributed operations. Most mining companies operate across multiple sites in different geographies. Scaling innovation across this footprint requires deliberate knowledge transfer mechanisms, standardized platforms where appropriate, and local adaptation where necessary.

A case study in doing it right: ground control capabilities at Vale Base Metals

The principles outlined above are not theoretical. A recent example from Vale Base Metals (VBM) illustrates what a disciplined, strategically grounded capabilities program looks like in practice, and offers a useful blueprint for other disciplines and mining organizations.

Facing a widening geotechnical skills gap across its seven underground and four surface mines in Canada, Brazil, and Indonesia, VBM developed its Ground Control Capabilities Advancement Program (GCCAP) as part of a broader ground control management system. What makes this initiative instructive is not just its scope but its methodology (Hossack et al. 2025).

The program began with community mapping, understanding the full ecosystem of roles, titles, and responsibilities across a dispersed global operation. From there, rather than starting with available training courses and working backward, the team worked forward from deliverables: what must a geotechnical professional actually produce to manage risk effectively? Those deliverables were then mapped to the specific technical, business, and soft skills required to produce them. This deliverable-first approach ensured that the program was anchored in operational reality rather than in generic competency frameworks.

Crucially, the program addressed the full breadth of what capability means in context. The skills mapping included not only core geotechnical competencies - characterization, modelling, monitoring design, hazard management - but also business skills such as cost estimation, business case development, and technology roadmapping, alongside soft skills including leadership, change management, and cross-functional collaboration. This reflects an important insight: in modern mining, a technically excellent geotechnical engineer who cannot communicate risk to non-technical stakeholders or evaluate trade-offs within a business context is only partially capable.

The program also incorporated forward-looking analysis, anticipating shifts such as the move from in-field to remote operations, the expansion of data-driven decision-making, and the growing importance of scenario-based modelling under uncertainty. Skills were then prioritized through a severity-and-scarcity matrix, ensuring that development resources were directed toward the capabilities that mattered most to the business, not spread across an overwhelming encyclopedic inventory.

The resulting framework includes a multi-level proficiency model (foundational, intermediate, advanced), a self-assessment tool that enables individuals to identify gaps against role expectations, an upskilling toolbox balancing passive learning (courses, modules) with active learning (mentorship, job rotation, secondment), and a curated course catalogue. The self-assessment data, aggregated across the organization, also gave VBM leadership a clear picture of where collective capability was strong and where it was thin, revealing, for instance, that safety-related skills were well-developed but future-facing capabilities in areas like coding and AI were significantly underdeveloped.

Several design principles from this example are worth highlighting for any organization building a capabilities program. Start from the work, not from the curriculum. Include business and interpersonal skills alongside technical ones. Prioritize ruthlessly so the program empowers rather than overwhelms. Build self-assessment into the system so individuals own their development. And embed the people framework within a broader management system rather than treating it as a standalone HR initiative.

The leadership imperative

Building an innovation capability is, at its core, a leadership challenge. It requires executives who are willing to protect long-term investments under short-term pressure, who can tolerate uncertainty without demanding premature certainty, and who understand that organizational capability building is slower and harder than technology deployment, but ultimately more valuable.

McKinsey's analysis found that nearly half of respondents in high-performing firms strongly agreed that senior leaders show clear ownership and long-term commitment to AI, compared with only about 16 percent in other organizations. The differentiator is not strategy documents or innovation budgets. It is visible, sustained, executive commitment to building the organizational capacity to innovate.

For mining companies, the competitive advantage of the coming decades will not be defined by who deploys the most algorithms or who adopts the latest technology first. It will be defined by who builds the organizational capability to continuously absorb, adapt, and create value from a rapidly changing technological landscape. That is not a program. It is a capability. And building it requires the same discipline, patience, and long-term thinking that the industry applies to developing its physical assets.

Sources:

McKinsey, "Mining for Operational Excellence," February 2025
McKinsey, "The State of AI in 2025: Agents, Innovation, and Transformation," November 2025
McKinsey, "How Mining Companies Reach the Operational Excellence Gold Standard," August 2022
McKinsey, "The Mining Value Chain: A Hidden Gem," October 2020
Hossack, A, Domergue-Schmidt, I, Thomas, L & Hemingway, G 2025, "Bridging the Skills Gap: A Blueprint for Enhancing Ground Control Capabilities," SSIM 2025, Vancouver, Australian Centre for Geomechanics
BCG, "Building Capabilities for Transformation That Lasts," 2016
Börjesson & Elmquist, "The Challenges of Innovation Capability Building," Journal of Engineering and Technology Management, 2014
Huron Consulting Group, "Strengthen Your Innovation Capabilities to Drive Performance," 2025
Prophet, "Building a Sustainable Business Innovation Capability," January 2025
Innov8rs, "Building Capacity for Breakthrough Innovation," April 2024
Deloitte, "The Skills-Based Organization: A New Operating Model for Work and the Workforce," 2022
Mining Industry Human Resources Council, "Mining Year In Review National Outlook," 2021

Every major mining company now has something it calls an innovation program. Some have innovation labs. Others have venture funds, digital transformation offices, or partnerships with technology accelerators. A few have all of the above. And yet the results, in aggregate, are disappointing. Most digital investments generate less than one-third of their anticipated impact, according to McKinsey research. Only about 5 percent of companies across industries attribute at least 10 percent of their EBIT to generative AI. The pattern is familiar: ambitious launch, early enthusiasm, a handful of promising pilots, and then a slow fade as attention shifts to the next priority and the organization reverts to its default behaviors.

This is not a technology problem. It is a capability problem. And until mining companies treat it as such, they will continue to cycle through innovation initiatives that deliver temporary excitement but not lasting value.

The pattern of failure

The failure modes of innovation programs in mining are remarkably consistent. Understanding them is the first step toward designing something better.

Isolated pilots that never scale. The most common pattern. A team identifies a promising use case, predictive maintenance, grade optimization, autonomous drilling, and runs a successful pilot at a single site. The results are encouraging. But translating that pilot into standard practice across multiple sites, with different equipment, different data systems, and different operational cultures, proves far harder than anyone anticipated. The pilot becomes a permanent experiment, celebrated in annual reports but never integrated into how the company actually operates.

Innovation functions disconnected from the core business. Many companies establish dedicated innovation teams or labs, often physically separated from operations. These teams may do genuinely interesting work, but they operate at the margins of the organization. They lack the authority to change operational processes, the credibility with frontline workers to drive adoption, and the integration with business planning cycles to ensure their work aligns with strategic priorities. As BCG has observed, a company in a process-heavy industry like mining might find it reasonably easy to develop lean capabilities for existing processes, but struggle to implement new digital capabilities that require fundamental changes in skills, technology, and daily behaviors.

Technology-first thinking. A vendor presents a compelling demonstration. An executive is impressed. A purchase order is signed. But the organization has not assessed whether it has the data architecture, the process maturity, or the human capability to absorb the new technology. The result is an expensive system that sits underutilized because the organizational context was never prepared for it.

Short-termism in measurement. Innovation, by its nature, involves uncertainty and long time horizons. But mining companies accustomed to measuring performance against quarterly production targets often apply the same evaluation frameworks to innovation initiatives. When a project does not show clear ROI within a year, funding is cut, the team is reassigned, and the organization concludes that "innovation doesn't work here."

Leadership turnover and attention drift. Innovation programs depend heavily on executive sponsorship. When the sponsoring executive moves to a new role, the program loses its organizational protection. Without sustained leadership commitment, innovation becomes one more initiative competing for attention in an organization that is already stretched thin.

What a capabilities approach looks like

The alternative to episodic innovation programs is building innovation as an organizational capability—a durable, systematic capacity to identify, develop, and scale new ways of operating, rather than a series of disconnected projects.

This distinction matters. A capability is embedded in how an organization works: its processes, its decision-making structures, its talent, and its culture. A program is an overlay that can be added and removed. The difference is the difference between an organization that occasionally innovates and one that innovates reliably.

Research on innovation capability building, including longitudinal studies of mature firms in the automotive industry, identifies several consistent elements of organizations that successfully develop this capacity.

A clear strategic link

Innovation capability starts with strategic clarity. What specific problems is innovation meant to solve? What competitive advantages is it meant to create? What time horizons matter?

In mining, these questions have distinct answers depending on the company's position. A company facing declining ore grades needs innovation that improves recovery and processing efficiency. A company expanding into new geographies needs innovation in remote operations and community engagement. A company positioning itself for the energy transition needs innovation in electrification, emissions reduction, and materials supply. Without this strategic anchor, innovation efforts diffuse across too many priorities and deliver against none of them.

McKinsey's research on mining operational excellence underscores this point: the outperforming organizations share a clear sense of purpose that connects daily work to broader strategic objectives. When employees understand why innovation matter, not as an abstract corporate aspiration but as a concrete response to specific business challenges, engagement and adoption follow.

Dedicated but connected organizational structures

The research consistently shows that breakthrough innovation requires dedicated teams with the mandate and autonomy to explore beyond the constraints of the existing business model. But—and this is where many mining companies go wrong—those teams must also be deeply connected to the core business. They need access to operational data, relationships with frontline workers, and integration with capital planning processes.

The effective model is neither a fully autonomous innovation lab nor innovation as "everyone's job." It is a dedicated function that operates with different governance, timelines, and risk tolerances than the core business, but is structurally linked to operational leadership and strategic planning. Think of it as a bridge between the organization's current operations and its future possibilities, firmly anchored on both sides.

Capability building at multiple levels

Innovation capability is not just about having skilled innovation professionals. It requires capability building at three levels:

Executive capability. Leaders need the ability to evaluate innovation portfolios, make resource allocation decisions under uncertainty, and protect long-term investments from short-term pressures. This includes developing fluency with emerging technologies, not the technical details, but enough understanding to ask the right questions and make informed strategic choices.

Middle management capability. This is often the most critical and most neglected layer. Middle managers are the primary mechanism through which organizational change either happens or stalls. They need the skills to support innovation within their teams, translate strategic innovation priorities into operational plans, and manage the tension between current performance demands and future capability development. McKinsey's operational excellence research specifically highlights the role of leaders who ensure management practices build people's capabilities.

Frontline capability. The people closest to the work often have the deepest insight into operational problems and improvement opportunities. Building their capability to identify, test, and implement improvements, supported by appropriate tools and governance, is what distinguishes organizations that achieve sustained performance improvement from those that plateau after initial gains.

Portfolio management, not project management

A capabilities approach treats innovation as a portfolio, not a series of individual projects. This means maintaining a deliberate mix of initiatives across different time horizons, risk levels, and strategic objectives, some focused on near-term operational improvement, others on medium-term capability development, and a few on longer-term transformational opportunities.

Portfolio management requires different evaluation criteria at different stages. Early-stage exploration should be assessed on learning and strategic alignment, not financial return. Later-stage development should demonstrate clear pathways to operational integration and value creation. The mistake many mining companies make is applying a single evaluation framework, typically one designed for capital projects with well-defined parameters, to all innovation activities, regardless of their maturity or strategic intent.

Governance that enables rather than constrains

Innovation governance in mining often defaults to the same approval processes used for capital expenditure or operational changes. These processes are designed to manage risk in well-understood contexts - exactly the opposite of what innovation involves. The result is that genuinely novel ideas are either killed by requirements for certainty that cannot yet exist, or distorted to fit evaluation templates designed for a different purpose.

Effective innovation governance creates distinct pathways with appropriate oversight at each stage. It establishes clear decision rights, so teams know who can approve what and under what conditions. It builds in structured checkpoints without requiring premature precision. And it creates mechanisms for escalating promising ideas and, equally importantly, for stopping work that is not progressing.

Measurement that matches the reality of innovation

The measurement challenge deserves particular attention. Standard business metrics, (cost savings, production increases, ROI), are important but insufficient for evaluating innovation programs, especially in their early stages.

A more complete measurement framework includes:

Input metrics: Are we investing sufficient resources? Do we have the right talent? Are we generating enough ideas from diverse sources?
Process metrics: Are ideas moving through the pipeline at an appropriate rate? Are we making timely decisions? Are we learning from failures?
Output metrics: What has been implemented? What operational changes have resulted? What value has been created?
Capability metrics: Are our people developing new skills? Are our processes improving? Is our organizational culture becoming more supportive of experimentation?

The discipline of measuring innovation capability, not just innovation output, is what distinguishes organizations that build sustainable advantage from those that achieve temporary results.

The mining-specific context

Several characteristics of the mining industry make capability building both more challenging and more important.

Physical constraints. Mining operates in physical environments that limit the pace and scope of experimentation. You cannot A/B test a blast pattern the way you A/B test a marketing email. This means innovation must be more carefully designed, more thoroughly simulated, and more deliberately staged than in less physically constrained industries.

Long capital cycles. Mining investments have 20- to 50-year horizons. This creates both a challenge, the inertia of existing assets and processes, and an opportunity. Companies that build strong innovation capabilities today will have decades to compound the benefits. Those that do not will be locked into increasingly outdated operating models.

Workforce dynamics. Mining faces persistent and compounding talent challenges. The number of universities offering specialized programs in areas like geotechnical engineering and mining engineering has declined, driven in part by a younger generation that prioritizes meaningful and flexible work over traditional remunerative benefits. A Mining Industry Human Resources Council survey found that 42 percent of respondents aged 15 to 30 said they would "definitely not" consider working in mining—the highest rejection rate of any sector surveyed. Meanwhile, a significant proportion of the existing mining workforce is approaching retirement, creating a loss of institutional knowledge that has not been adequately transferred. As Hossack et al. (2025) document, these factors are compounded by increasingly stringent regulatory frameworks and the growing technical demands of new monitoring and analysis technologies, which require larger and more skilled teams than many organizations currently have. Deloitte (2022) research cited in their work reinforces the business case: organizations that prioritize skills investment are 98 percent more likely to retain high performers and 52 percent more likely to innovate. An innovation capability program that gives people meaningful opportunities to develop new skills and work on consequential problems is not just a nice-to-have. It is a talent strategy and a risk management strategy simultaneously.

Distributed operations. Most mining companies operate across multiple sites in different geographies. Scaling innovation across this footprint requires deliberate knowledge transfer mechanisms, standardized platforms where appropriate, and local adaptation where necessary.

A case study in doing it right: ground control capabilities at Vale Base Metals

The principles outlined above are not theoretical. A recent example from Vale Base Metals (VBM) illustrates what a disciplined, strategically grounded capabilities program looks like in practice, and offers a useful blueprint for other disciplines and mining organizations.

Facing a widening geotechnical skills gap across its seven underground and four surface mines in Canada, Brazil, and Indonesia, VBM developed its Ground Control Capabilities Advancement Program (GCCAP) as part of a broader ground control management system. What makes this initiative instructive is not just its scope but its methodology (Hossack et al. 2025).

The program began with community mapping, understanding the full ecosystem of roles, titles, and responsibilities across a dispersed global operation. From there, rather than starting with available training courses and working backward, the team worked forward from deliverables: what must a geotechnical professional actually produce to manage risk effectively? Those deliverables were then mapped to the specific technical, business, and soft skills required to produce them. This deliverable-first approach ensured that the program was anchored in operational reality rather than in generic competency frameworks.

Crucially, the program addressed the full breadth of what capability means in context. The skills mapping included not only core geotechnical competencies - characterization, modelling, monitoring design, hazard management - but also business skills such as cost estimation, business case development, and technology roadmapping, alongside soft skills including leadership, change management, and cross-functional collaboration. This reflects an important insight: in modern mining, a technically excellent geotechnical engineer who cannot communicate risk to non-technical stakeholders or evaluate trade-offs within a business context is only partially capable.

The program also incorporated forward-looking analysis, anticipating shifts such as the move from in-field to remote operations, the expansion of data-driven decision-making, and the growing importance of scenario-based modelling under uncertainty. Skills were then prioritized through a severity-and-scarcity matrix, ensuring that development resources were directed toward the capabilities that mattered most to the business, not spread across an overwhelming encyclopedic inventory.

The resulting framework includes a multi-level proficiency model (foundational, intermediate, advanced), a self-assessment tool that enables individuals to identify gaps against role expectations, an upskilling toolbox balancing passive learning (courses, modules) with active learning (mentorship, job rotation, secondment), and a curated course catalogue. The self-assessment data, aggregated across the organization, also gave VBM leadership a clear picture of where collective capability was strong and where it was thin, revealing, for instance, that safety-related skills were well-developed but future-facing capabilities in areas like coding and AI were significantly underdeveloped.

Several design principles from this example are worth highlighting for any organization building a capabilities program. Start from the work, not from the curriculum. Include business and interpersonal skills alongside technical ones. Prioritize ruthlessly so the program empowers rather than overwhelms. Build self-assessment into the system so individuals own their development. And embed the people framework within a broader management system rather than treating it as a standalone HR initiative.

The leadership imperative

Building an innovation capability is, at its core, a leadership challenge. It requires executives who are willing to protect long-term investments under short-term pressure, who can tolerate uncertainty without demanding premature certainty, and who understand that organizational capability building is slower and harder than technology deployment, but ultimately more valuable.

McKinsey's analysis found that nearly half of respondents in high-performing firms strongly agreed that senior leaders show clear ownership and long-term commitment to AI, compared with only about 16 percent in other organizations. The differentiator is not strategy documents or innovation budgets. It is visible, sustained, executive commitment to building the organizational capacity to innovate.

For mining companies, the competitive advantage of the coming decades will not be defined by who deploys the most algorithms or who adopts the latest technology first. It will be defined by who builds the organizational capability to continuously absorb, adapt, and create value from a rapidly changing technological landscape. That is not a program. It is a capability. And building it requires the same discipline, patience, and long-term thinking that the industry applies to developing its physical assets.

Sources:

McKinsey, "Mining for Operational Excellence," February 2025
McKinsey, "The State of AI in 2025: Agents, Innovation, and Transformation," November 2025
McKinsey, "How Mining Companies Reach the Operational Excellence Gold Standard," August 2022
McKinsey, "The Mining Value Chain: A Hidden Gem," October 2020
Hossack, A, Domergue-Schmidt, I, Thomas, L & Hemingway, G 2025, "Bridging the Skills Gap: A Blueprint for Enhancing Ground Control Capabilities," SSIM 2025, Vancouver, Australian Centre for Geomechanics
BCG, "Building Capabilities for Transformation That Lasts," 2016
Börjesson & Elmquist, "The Challenges of Innovation Capability Building," Journal of Engineering and Technology Management, 2014
Huron Consulting Group, "Strengthen Your Innovation Capabilities to Drive Performance," 2025
Prophet, "Building a Sustainable Business Innovation Capability," January 2025
Innov8rs, "Building Capacity for Breakthrough Innovation," April 2024
Deloitte, "The Skills-Based Organization: A New Operating Model for Work and the Workforce," 2022
Mining Industry Human Resources Council, "Mining Year In Review National Outlook," 2021

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