Advancing metals and mining in Southeast Asia with digital and analytics

Southeast Asia’s downstream-processing industry has recently seen rapid growth and expansion. Much of this industry is concentrated in Indonesia, with a smaller but significant presence in other Southeast Asian countries. Our research shows that since 2021, commodity prices for base metals such as nickel and copper have increased by 80 to 120 percent. In response, Indonesia and other countries are investing in the downstream-processing industry to capture increased value across sectors and drive domestic industry growth.

Although these efforts to encourage growth have proved effective, players in the downstream-processing industry in Southeast Asia can go further by pursuing digital and analytics (DnA) opportunities. By imple­menting DnA-enabled practices, processing plants can capture the value of data across the value chain, optimize their operations, and subsequently achieve better results. In fact, our estimates show there is potential to achieve 8 to 10 percent in through­put improvement as well as an uptick of one to three percentage points in recovery performance. Ultimately, these increases could unlock approxi­mately $4 billion to $5 billion in value.

Current market conditions present a pivotal moment for Southeast Asia’s downstream-processing indus­try to build plants for the future. To leapfrog toward it, leaders in the downstream-processing industry can focus on implementing “triple transformations” in business, organization, and technology functions, all geared toward harnessing the true potential of DnA.

Industry snapshot: Downstream processing in Indonesia

The cascading effects of the COVID-19 pandemic and the war in Ukraine have affected a range of commodities, from crude oil to nickel, copper, coal, and palm oil. For example, in March 2022, the price of aluminum almost doubled from the 2020 average, reaching a record high of $3,496.1 Similarly, the price of copper doubled, peaking at about $4.90 per pound in March 2022.2 Commodity supply chains have been forced to react to this volatility and have subsequently started to tighten, with companies anticipating a further rise in costs and transportation- and shipping-related risks.

In Southeast Asia, where many raw materials are produced, industry leaders have identified an oppor­tunity to move down the value chain to capture more value from semifinished or finished goods. This has spurred a booming processing industry, particularly in Indonesia, the largest economy in the region.

In the past, Indonesia’s mining and minerals industry focused on exporting raw ore directly rather than participating in the rest of the production value chain. But the industry has since transformed and expanded as the government has made active, continuous efforts to develop downstream industries.3 These new industrial policies were set in motion even before the COVID-19 pandemic struck; for example, in 2019, the Indonesian government publicly announced a policy promoting investment in nickel-ore-processing facilities.4 Such policies have led to a new focus on processing commodities into ready-to-use products, which has boosted the economy and enabled the country to produce higher-quality products that can be used directly in manufacturing. Further plans are also under way to increase Indonesia’s processing capabilities. For example, in 2022, there was a significant push for the processing of bauxite—a raw material used in aluminum production—and copper concentrate processing and tin processing are set to increase from 2023 onward.5

The new focus on downstream-processing industries has had an outsize effect on the commodity market, given that Indonesia is the world’s largest producer of nickel, the second-largest producer of tin, the third-largest producer of coal, the fourth-largest producer of bauxite, and one of the largest producers of copper and gold (Exhibit 1).

1
Indonesia is one of the world’s largest producers of commodities such as nickel, tin, coal, and bauxite.

The new priority on developing the domestic pro­cessing industry has pushed Indonesian companies to reconsider their supply chain strategies. The Indo­nesian smelter industry, for example, has ramped up production thanks to several development pro­grams. Before 2014, Indonesia had only two nickel smelters. This figure jumped to 13 in 2020 and is expected to more than double to a total of 30 by 2023.6 The increase in smelters for nickel and other commodities means that Indonesia can now smelt up to 12.3 million metric tons of nickel, 6.0 million metric tons of aluminum, 3.2 million metric tons of copper, and 19.0 million metric tons of steel per year.7 The number of smelting companies is also booming, with 69 companies currently in operation, totaling an investment value of $51.4 billion.8

As Indonesia has ramped up its production of metals and other minerals, industry leaders around the world have responded by assessing investment opportunities to set up downstream-processing plants in the region. For example, many countries are jumping at the opportunity posed by Indonesia’s increased nickel production to set up electric-vehicle (EV) battery value chains, of which nickel is a core component—which could make nickel a strategic resource in the energy transition. Prominent Chinese players have announced rotary kiln-electric furnace (RKEF) and high-pressure acid-leaching (HPAL) projects to process nickel ore domestically. Similarly, European chemical and mining companies have announced studies to set up HPAL and refining plants in Indonesia.9 As for copper, American and Indonesian mining organizations have started construction on what will be the world’s largest copper smelter in Gresik.10

Numerous new processing projects are planned for the next few years in Indonesia, mainly focused on the nickel and copper industries (Exhibit 2). When these megaprojects go online, they could materially increase the processing capacity of metal derivatives in Indonesia and position the country as an emerging and vital player in the processing industry. Other Southeast Asian countries are not far behind and are experiencing similar developments. In the Philippines, for example, a change in policy on mining techniques is set to increase the production of commodities such as copper, gold, and silver.

2
Several new processing plants in Indonesia are planned to be completed in the next three years.

A vision of the processing plant of the future

Although new factories are emerging in Indonesia and other parts of Southeast Asia, the region’s downstream-processing industry still has significant room for efficiency improvements. One source of efficiency that companies in the region have not yet fully harnessed is DnA technology, which could make all the difference in building the successful processing plant of the future.

Around the world, tech-enabled process optimi­zation has been at the core of improvements in efficiency for all major front-runners in the mining industry.11Inside a mining company’s AI transformation,” McKinsey, February 5, 2020. Traditionally, companies in the mining industry have relied heavily on individual experience combined with first principles to drive productivity. However, due to a surge in data creation and computing power along with the plunging cost of data storage and Internet of Things (IoT) nodes, there has recently been a paradigm shift across the industry, leading operators to supplement traditional methods with more sophisticated technologies to make data-driven decisions.

Tech-enabled process optimization has been at the core of improvements in efficiency for all major front-runners in the mining industry.

In the past decade, Southeast Asian companies have undertaken a similar proliferation of sensors and data in both frontline and factory operations. For example, to boost its productivity, one mining company in Southeast Asia leveraged multiple digital solutions, including real-time crew management, DnA-driven maintenance, and digital control towers. These tech­nologies were combined with a gamified training app to increase adoption by employees, which helped the company become an Industry 4.0 leader. Likewise, an energy company made factories smarter with communication portals, Industrial IoT (IIoT) system monitors, and a tracking system that uses QR codes. These technologies improved productivity and efficiency by collecting and leveraging useful data across operations.

Most metal and mining players in Southeast Asia already own a trove of valuable data but have yet to experience the truly transformational impact of this data on the bottom line. Many companies in the region are exploring ways to realize the value of the data through tech-enabled innovation across the value chain (Exhibit 3). The overall goal is to improve operational efficiency while helping companies achieve their sustainability targets—that is, maintaining their productivity while consuming less fuel. In fact, nearly half of tech-enabled impact is driven by the application of advanced analytics in processing plants to propel end-to-end process optimization.

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Digital and analytics–enabled innovations are emerging across the mining value chain.

One of the challenges with processing-plant opti­mization is its sheer complexity, with thousands of operation parameters. Today, decisions are typically made by operators who combine their individual experience with small sets of process control data, which can result in varying degrees of success.12The potential of advanced process controls in energy and materials,” McKinsey, November 23, 2020. A broader set of data, state-of-the-art AI, and metallurgy principles can be combined in proprietary optimization algorithms to give operators advice that encompasses more variables and historical data than a human can process.

For example, process optimizations for grinding operations in a mineral-processing plant are often complex and challenging. A control room operator needs to consider multiple decisions simultaneously across hundreds of process vari­ables, many of which are often not transparent and require various trade-offs. Optimizing trade-offs between throughput, recovery, and product quality is not straightforward, even for operators with years of experience. Moreover, the existing process-control solutions often optimize only a single unit process without considering the effect on downstream or upstream operations. For example, an advanced process-control tool for a grinding mill can optimize the feed rate to the mill, but during the process, it can also neglect the effect the initial feed rate has on downstream recovery. As a result, grinding mills usually operate well below their end-to-end optimal set points, thus yielding daily production losses.

DnA has revolutionized processing-plant optimization, enabling users to analyze significantly larger sets of operation data—for example, across multiple years—and receive advice on optimal set points in near-real time, pushing data-driven decision making into daily operations. With tools such as fully automated data pipelines and interactive dashboards, operators can easily understand the full impact of process param­eter changes. Through customizable user interfaces, such as digital control towers, operators can even gain the ability to con­duct scenario-based operation tests prior to fully implementing them. As a result, operators can learn and understand the operational tweaks needed for individual assets, achieving significant reductions in process variability and enhancing throughput.

The value of DnA technology goes far beyond ease of use: across Southeast Asia, the adoption of advanced analytics–driven technology can improve the productivity of processing plants and potentially create $4 billion to $5 billion in value across key metal industries (Table 1). This proven recipe has been deployed across more than 100 assets across industries and product commodities globally, achieving an 8 to 10 percent increase in throughput with an approximate 1 to 3 percent uptick in recovery performance.

Table 1. Improving copper, gold, nickel, iron ore, and zinc processing could create as much as $5 billion in value across Southeast Asia.

CountryPotential mining processing value in Southeast Asia, $ millions
Indonesia$2,900–$3,700
Philippines$700–$900
Laos$150–$190
Vietnam$140–$180
Malaysia$50–$70
Myanmar$40–$50
Thailand$16–$20
$4 billion–$5 billion total potential value across Southeast Asia
Source: McKinsey MineLens

The proven global success of DnA

DnA’s potential to unlock value has already been demonstrated in processing plants around the world. Across all heavy-industry sectors, companies have seen improved performance, resilience, and flexibility by harnessing the power of data in sustained, significant transformations.

In mining, Freeport-McMoRan leveraged advanced analytics to drive a distinctive sitewide transformation at its mill in Bagdad, Arizona.13Inside a mining company’s AI transformation,” February 5, 2020. To improve perfor­mance, managers fundamentally changed how the mill works and implemented data science and agile ways of working that enabled easier, faster, and better-informed decisions. Better decision making led to better results: using digital-informed approaches allowed the mine to increase both throughput and recovery and to produce up to 5 percent more copper annually.14

In the metals industry, a similar scenario played out at Tata Steel’s plant in Kalinganagar, India. Using historical data, plant managers were able to tap into the value of data by building an analytics model of the plant’s processes. By using the model to analyze their superheating process, operators successfully increased their “strike rate” (the percentage of molten steel batches heated to the optimal range) by up to 85 percent, increasing throughput by 8 to 12 percent.15How a steel plant in India tapped the value of data—and won global acclaim,” McKinsey, March 8, 2021. Managers supplemented this increased productivity with a strong upskilling and capability-building program to empower the team to work with digital technologies.

DnA also holds great potential in the energy sector. For example, an energy company achieved lasting financial and sustainability improvements by leveraging AI in its power plant operations. After successfully deploying a heat rate optimization program, the energy company went on to tackle scaling, which is frequently the more challenging step. By adding to the core functionality of the program and training employees in its use, the company efficiently scaled its new AI tools across more than 50 generators to unlock more than $50 million in savings while abating a significant amount of carbon annually.

These successful transformations are only the beginning. Spurred by the COVID-19 pandemic and geopolitics, industrial companies have been scaling up DnA even faster to ensure value chain resilience.16Building value-chain resilience with AI,” McKinsey, November 26, 2021. By applying AI, companies in Southeast Asia can break out of pilot purgatory, unlock significant value for their organizations, and build resilience in a rapidly changing world—if they can transform successfully to support the new technology.17

What it takes to deliver a DnA-enabled operation

The best way to implement DnA-enabled operation implementation is to adopt a comprehensive “triple transformation” of business, organization, and technology functions to ensure end-to-end adoption and to capture the full value of new technologies.

On the business side, companies should have a clear vision of business value—including a road map with impact use cases—when it comes to choosing which DnA solutions to implement. The best use cases drive value and have appropriate payback periods. Companies with successful transformations typi­cally establish internal processes that help link digitalization to business value and create clear lines of sight to desired benefits, whether bottom-line impact, carbon-footprint reductions, or improved safety performance. With greater overall clarity, businesses can also focus resources on what matters most and ensure a consistent and transparent organization-wide communication.

As for the organization, a full-scale transformation of culture and change management can help employees fully embrace DnA and can create a clear path of adoption by lines of business. Leaders should focus on changing mindsets and behaviors from the board­room to the front line to capture value at scale and achieve sustainable impact. Paying attention to the hearts and minds of employees can drive last-mile adoption of new technologies and techniques. A suite of interventions, including leadership role modeling, awareness-building campaigns, and early engagement of end users, can be useful tools for achieving greater buy-in. In addition to changing company culture, the processing industry as a whole needs to prepare for shifting talent needs in the future. To accelerate the pace of digitalization in the industry, companies could consider upskilling their organization internally and attracting top talent from external sources. For example, within the existing organization, field engineers could be retrained to become analytics translators who bring a strong domain-backed understanding to the application of data analytics. Other digital capabilities, such as product ownership, data science and engineering, solution architecture, and cybersecurity, may need to be hired from outside the traditional processing-industry talent pool.

Finally, to transform technology, companies need to establish a scalable infrastructure, thoughtful data governance systems, and a dynamic partner ecosystem. One way to achieve a scalable infor­mation technology and operational technology (IT/OT) infrastructure is to adopt a two-speed architecture. In this system, faster front-end technology and middleware (such as IoT platforms) are built to be adaptable and scalable. These technologies then interface with existing back-end enterprise systems, which are often slower and could be outdated. Using this approach allows for agile, high-speed developments with extensive rapid prototyping to develop use case–based functionality. Meanwhile, making slower changes to core legacy systems such as enterprise resource planning (ERP) and manufacturing execution systems (MES) enables them to evolve over time. At the same time, it is important to maintain rigorous data governance across all domains, particularly in key dimensions such as security, controls, and prioritization. With well-governed data, companies can build consolidated data sources to enable data-driven decision making. In all these efforts, traditional processing-industry players should consider building and leading a focused, dynamic ecosystem of partners such as cloud providers and start-ups to accelerate their technology capabilities.


As Southeast Asia’s mining and minerals industry expands, DnA-enabled operations have the potential to deliver the next step change in value creation for downstream processing. The region is now at a pivotal moment to build an ecosystem of DnA-powered capabilities that could help the industry leapfrog toward supporting next-generation processing plants. But the way DnA is implemented—if it is implemented at all—will make the difference in Southeast Asia’s future.

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