The mining industry’s $59 billion blind spot

In brief

• Mining companies missed production targets by 3.1% annually, resulting in a $59 billion revenue loss over the last four years.
  
  
• There are two sets of root causes, one related to target setting and the other to actual performance. And both can be addressed.
  
  
• These root causes can be addressed with an intentional, analytics-based, action-focused intervention. 
  
  
• By addressing the root causes and implementing recommended strategies, mining companies can improve production predictability, minimize revenue misses and contribute to a successful net-zero transition.

Improving production predictability contributes to the net-zero transition

The mining industry plays a crucial role in the global net-zero transition, providing essential minerals and resources for renewable energy technologies. However, our research revealed a significant production predictability issue within the industry. In the past four years, top mining companies have missed production targets, meaning they have missed out on $59 billion in revenue and have typically performed 3.1% worse than forecasted by themselves 12 months earlier. In the same four-year period, 62% of mines reported results at or below the lower half of the guidance range.ⁱ

The stark reality is that missing forecasted production is not an exception; many mining companies miss their targets, with very few cases of overachievement. In an environment where annual demand for rare earth minerals is projected to grow by 2.5x, by 2030¹, these production misses pose problem in that they are missed profits, but also from a broader view as a threat to an effective net-zero transition.

What are the root causes of this issue? And what can be done to address it?

Our research shows a long list of root causes, starting with outside factors, such as COVID-related shutdowns, flooding and the energy crisis. Including in this list are planning gaps, such as not having enough information or understanding, or being too confident when calculating reserves. But they also include operative issues, such as geological variability, lower ore quality, unplanned downtime, a shortage in skilled labor and logistics constraints, which can also contribute to the problem. 

Whatever the cause, every leading mining company missed production estimates at some stage during the four-year period leading up to 2023.ⁱⁱ In total, the missed production volumes amount to 199 million tons over the same period.ⁱⁱⁱ

Understanding and addressing the production predictability issue

Fortunately, there are several critical areas in which mining companies can address and mitigate the production predictability issue. There are two sets of root causes, one related to target setting and the other to actual performance. And both can be addressed: 

1. Target communicated: In many instances, the wrong target was set and the following interventions can help to address the root causes. 

• Adverse external factors: Address by putting in place better predictive analytics of external factors.
  
  ¹Could Africa replace China as the world’s source of rare earth elements?
  
  
• Overconfidence in target setting: Address by leveraging learning cycles and analytics to reduce overconfidence in human judgment.
  
  
• Insufficient resolution or level of detail in plan: Address by implementing more detailed and more integrated planning, from “top floor to shop floor."
  
  
• Lack of data or insights for target setting: Address by implementing data-driven decision-making processes.
  
  
• Insufficient forecasting ability: Address by implementing better predictive analytics of internal processes and factors.
  
  
• Overconfident reserve calculations: Re-evaluate planning and operative data to understand root-cause errors.
  
  
• And many more

2.   Actual performance: In this case, production targets were accurate, but were not met. This can be due to several factors, such as:

• Geological variability or lower ore quality:Address by implementing better analytics, machine learning and forecasting.
  
  
• Unplanned downtime: Address by ensuring maintenance excellence is in place based on traditional, digital and AI interventions.
  
  
• Shortage in skilled labor: Address by investing in further automation or by tapping into new talent pools (though this approach typically requires additional training and onboarding efforts.)
  
  
• Capacity bottlenecks or capacity constraints: Address by implementing more detailed and more integrated planning, from “top floor to shop floor."
  
  
• Insufficient scheduling: Address by adopting data-driven decision-making processes and leveraging AI and analytics.
  
  
• Yield losses, quality issues or off-specs and logistical constraints: Address by implementing better predictive analytics of internal processes and factors.
  
  
• And many more 

Addressing the root causes

These root causes can be addressed with an intentional, analytics-based, action-focused intervention.

The first step is to analyze data and operations to understand how well the planning system and operations are working together. This includes looking at how different parts of the company, like IT and OT, are integrated, as well as how well the company is able to forecast and manage its supply chain. By doing this forensic analysis, we can identify the root-causes and opportunities for improvement. A joint understanding of high-impact areas for solutioning can then follow.

Based on a fact-based view on the root causes, a solution sprint then defines a list of implementation-ready solutions, as well as the investment cases. Each outlines the benefits, capex and required efforts over a period of 6–10 weeks. A value and impact-focused implementation and change management can create measurable improvements within 3 to 12 months. The effort includes addressing (and developing) new ways of working based on new technologies, new mindsets and behaviors, new tasks, potential roles and responsibilities and continuous value and progress tracking. From our experience, the typical 3.1% miss of the production target can be reduced within 12 months by 1–2%.

The challenges—and benefits—of addressing production predictability 

The production predictability issue in the mining industry poses significant challenges: it compromises investor confidence, is a major discussion point in most investor Q&As and means lost output and profit year-on-year, resulting in lower cashflows and valuations.

Improving production predictability requires programmatic change and a reinvention in planning, asset operations and end-to-end supply chains. It requires building new capabilities, adapting ways of working and organizational roles and investing in new analytics and technology.

For leading mining companies, the “size of the prize” is in the billion US dollars range, so it is clearly worth the investment and change required. By addressing the root causes and implementing the recommended strategies, mining companies can improve their production predictability and minimize revenue misses and pave the way for a successful net-zero transition and a greener and more profitable future.

ⁱ _{Accenture research analysis based on company announcements. Announcements tracked are from 2020-2023.}

ⁱⁱ _{Accenture research analysis based on company announcements and average annual metal prices. Revenue missed here only accounts for the missed production and not for overproduction.}

_{ⁱⁱⁱ Accenture research analysis based on company announcements. Volume missed here only accounts for the missed production and not for overproduction.}