In its latest insights article, McKinsey & Company makes the case for using AI to stage cross-functional interventions and bring down the total cost baseline at pulp and paper packaging mills.
The global outlook
McKinsey notes that factors such as the COVID-19 pandemic, the war in Ukraine, the conflict in Iran, and the growing application of tariffs have led to slowing demand and limited growth in the paper and pulp industry. Fibre markets have tightened in response to reduced access to Russian tinder, for example.
Overcapacity has persisted across grades, the article continues. Input costs also remain volatile across the globe; fibre has become more expensive in Europe and large parts of North America – partially in response to the mountain pine beetle epidemic in Canada.
Companies in Latin America and Southeast Asia have access to lower-cost short fibres and have reportedly gained a structural advantage; in turn, they have branched out to Western markets and increased the cost pressure on European and North American competitors.
Yet land cost inflation, rapid pulp capacity expansion, and the resultant competition for raw materials have also driven up eucalyptus prices for Latin American customers. At the same time, Indian producers have experienced a spike in prices for old corrugated containers.
Generally speaking, some companies have expanded their capacity and converted legacy assets, such as reconfiguring newsprint machines to produce containerboard – and this has created oversupply in certain segments.
At the same time, post-pandemic demand has normalized, e-commerce growth has stabilized, and consumer demand has weakened, which has resulted in flat or declining volvumes across several end markets. This has led to imbalanced supply and demand, which has driven market compression across the paper and packaging value chain.
Demand patterns are also changing, as market players in consumer packaged goods are lowering inventory levels, increasing order volatility, and adjusting prices more frequently. These conditions have led to more variability in mill operations and emphasized the importance of utilization, planning, and cost efficiency.
McKinsey goes on to explain that companies can no longer bridge the cost gap through optimized procurement, lean manufacturing or energy efficiency.
“For decades, the pulp and paper packaging industry operated on a stable economic model: high asset intensity, strong variable margins, and a focus on maximizing throughput to absorb fixed costs,” the article reads. “That model is now under sustained pressure.”
The ‘site sprints’ approach
Fibre is thought to be the largest cost component across most pulp and paper packaging operations, comprising 25-70% depending on vertical integration and geography. Energy generally accounts for 10-25% of costs; McKinsey suggests that integrated mills can generate their own energy and partially offset these expenses, but this will not entirely negate their reliance on external energy markets.
Other expenses include chemicals (8-25%) and logistics (10-15%). Fixed costs like labour, maintenance, and depreciation are also considered to range from 15-25% as utilization declines.
McKinsey argues that successful companies are transitioning from siloed cost programmes into integrated approaches that cover the full production system – using advanced data capabilities and generative AI to coordinate operations, procurement, energy, and analytics.
McKinsey refers to this approach as ‘site sprints’. Fast and cross-functional interventions target the total cost baseline of a mill, with companies identifying the cost-optimal operating point of their production systems through optimized fibre use, machine performance, energy systems, and indirect spending; this information can be used to plan their next steps.
Through the site sprints model, companies are expected to achieve ‘substantial’ cost reductions and increase capabilities for sustained performance improvement. These results are thought to be a ‘critical’ factor for competitiveness in lower-growth and volatile environments.
The paper and pulp industry has previously been slow to catch up with digital progress, McKinsey suggests, but points to the increasing deployment of the site sprint approach. Early use cases in procurement, supply chain, and manufacturing applications are already said to have improved decision-making, lessened manual effort, and enabled cost optimization across the supply chain.
The article recommends that companies undertake site sprints within a single team that integrates operations, procurement, energy management, and data science.
How it can help
To demonstrate its approach, McKinsey raises the example of a global pulp and paper company that undertook site sprints across its global plant network in under two years. This was said to unlock cost savings ranging from 8% to 20% at individual mills, totalling several hundred million dollars’ worth of impact. Now the company is said to independently conduct multiple site sprints annually.
The article highlights gen AI as a helpful tool for making fast, consistent decisions at scale – especially for supplier analysis, demand planning, production optimization, and other information-intensive processes. Alongside traditional AI, it is recommended as a means of launching advanced recipe management across fibres, energy, and other variable costs.
Analytical models could help identify opportunities to lower cost inputs without compromising product specifications – helping market players achieve cost-efficient optimization across grades in production and development. Improving wood fibre yield has apparently helped the pulp and paper company capture additional percentage points of valuable output and reduce spending.
Another complementary area is lean operations and manufacturing. Customers could optimize fibre yield from the source to the web through improved chip quality management, cooking control, web break prevention, and more.
McKinsey’s partner has mapped fibre losses across the value stream and targeted root-cause interventions; the article says that this undertaking has lowered fibre spend by several percentage points across both virgin and recycled mills. Undertaking comprehensive improvements in yield, runnability, and chemical dosing is expected to reduce waste, downtime, and variability while improving throughput.
Integrating the optimization of steam, power and utility systems alongside production planning and energy price signals could also bring down total energy costs, according to McKinsey. For instance, the pulp and paper company has optimized the energy system at one of its largest integrated mills, and it now reports improvements in its dynamic steering of steam and power generation in line with electricity market conditions and operational constraints.
As a result, the company is said to have reduced its energy consumption by several hundred gigawatt-hours every year. McKinsey says that the site has turned from a net fuel consumer into a net exporter.
To overcome fragmentation and improve optimization in indirect spend, the article recommends that companies look at category redesign, local sourcing, supplier consolidation, and bundled service models. McKinsey states that a cross-functional approach, including dynamic recipe optimization based on market conditions, has helped the pulp and paper company lower variable production costs by up to 5% without compromising consistent product quality.
Companies should consider any trade-offs when making changes across multiple areas, the article advises. For instance, making a fibre substitution may require companies to refine their energy and chemicals mix to maintain the final product’s ideal properties.
According to the article, AI could help understand interdependencies and trade-offs across the full system. It could also intelligently combine and offset negative effects, thus reducing costs – potentially by up to 20%, depending on the company’s starting point and asset configuration – and arriving at a better product.
McKinsey adds that new technologies could take mill operations further. Robots could unlock agentic capabilities and create opportunities for large-scale mill automation based on physical AI.
In a previous article, McKinsey suggested that paper and packaging companies should pursue multiple smaller deals throughout the year, rather than large acquisitions; this approach would achieve growth, increase returns, and overcome industry disruption.
Meanwhile, The Consumer Goods Forum’s Plastic Waste Coalition of Action has published a report indicating that AI can help companies generate and optimize packaging design, sort waste effectively, and trace materials throughout the supply chain.
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