Geopolitical Instability Has Made Material Variability the New Normal
As many manufacturers have experienced lately, global geopolitical instability introduces constant volatility that compromises supply chain stability and makes sourcing high-quality, consistent raw materials a constant struggle. Geopolitical tensions can force industries to change raw material suppliers, increasing material variability which can lead to higher rates of rework, down-grading, off-grading and scrap.
And with quality requirements increasing every year, making production that was acceptable five years ago obsolete today. The primary challenge is to significantly reduce scrap, rework, and waste while complying with a changing market and increasingly stringent regulations.
These factors require continuous, vigilant attention to both production processes and raw materials, pushing industries to pursue ever higher levels of control and precision. To remain major players in the market, these industries must constantly adapt their strategies to new regulations and geopolitical developments.
Valorizing Raw Materials: The Fastest Path to Yield and Cost Reduction
Maximizing the valorisation of raw materials into finished products and co-products is key to reducing waste. By transforming portions of raw material that cannot be used for the original product into an alternative co-product, manufacturers can create a new revenue stream, maximize yield, and lower production costs.
Manufacturers must optimize every stage of the production cycle and especially on 3 levels, which will allow the measurement of performance.
- For raw materials, measuring composition and purity enables manufacturers to adjust process and equipment parameters before processing begins, ensuring product quality despite fluctuations in raw material properties.
- At each process unit step, continuous material-balance tracking makes it possible to trace and identify the specific causes of losses. These typically include product degradation due to incorrect thermal or chemical parameters, inefficiencies in washing and cleaning cycles, physical leaks from equipment, and incomplete reaction of the raw material. Once losses are identified, process conditions and equipment efficiency can be optimized to reduce them.
- For the finished product, actively controlling packing weights, nonconformities, and composition helps reduce rework and the extra use of raw materials needed to meet regulatory requirements. Process parameters and equipment conditions can then be corrected.
Data Platforms + AI: The New Operating System for Material Efficiency
But one of the main obstacles to optimization is the significant time for manufacturers to process and manage material-related information. That’s where integrating data platforms and AI can help respond to these challenges to reduce scrap and rework, improve operational efficiency, and generate insights into internal factory processes and machine performance.
Several companies have already gone through a digitalisation process to reduce scrap/rework/down-grading/off-grading while also addressing legal and ecological challenges. Data platforms, when paired with AI and Machine Learning models, offer an effective solution for managing material variability and navigating supply chain volatility. These data platform and AI solutions provide four major axes of improvement:
- The speed of analysis and operational efficiency: Data systems process vast amounts of information and run complex analyses far faster than humans can. This enables real-time tracking of the raw materials and related traceability required for the Digital Product Passport.
- Predictive and Prescriptive Control: In terms of material utilization, approaches based on Statistical Process Control (SPC) or Artificial Intelligence (AI) can evaluate the inherent variability of a batch and either provide precise recommendations to human operators or automatically adjust process parameters in real time. When a scrap event occurs, the system can run correlations and anomaly detection across thousands of variables to pinpoint the root cause, reducing Root Cause Analysis (RCA) from days or weeks to minutes.
- Simulation and Resilience: to manage complicated geopolitical shifts (such as a sudden change in suppliers), data platforms can rapidly simulate how a new raw material will behave. This enables manufacturers to configure machines with optimized parameters from the first hour of production, bypassing the expensive "trial and error" phase and avoiding the surge in scrap typically associated with material changeovers.
- Strategic Freedom: The Ultimate Competitive Advantage: perhaps the most significant benefit of integrating data and AI is the strategic freedom it gives leadership. In a digitally mature company, adapting to a changing market is no longer a crisis-driven exercise in "firefighting." By removing manual root-cause investigations and compliance paperwork, leadership can redirect human resources toward high-level strategic initiatives and innovation. Data and AI platforms such as Manufacturing Performance Intelligence (MPI) therefore help an organization protect its competitive advantage and remain a resilient, major player, regardless of how unpredictable the global landscape becomes.
Regulatory Pressure Is Accelerating the Need for Digital Traceability
Reducing scrap/rework/down-grading/off-grading has always been a fundamental objective for industries globally, driven by the desire to improve efficiency and minimize operational costs. But industries are facing additional major external challenges such as changing laws and market dynamics that traditional manual management cannot overcome. In Europe and the US, regulatory pressure is increasing, although it is less centralized and more sector- and state-driven in the US.
- Supply chain transparency and ESG disclosures: large manufacturers and their suppliers are increasingly expected to provide auditable data on sourcing, labor, and environmental footprint. This pushes companies to implement stronger material traceability and data governance to avoid compliance risk and customer penalties.
- The « digital passport » for every material and the mandatory integration of recycled materials. These regulations require companies to collect, record, and verify detailed information on the provenance, composition, and processing history of the raw materials used in their products. This turns existing data collection and management into a legal obligation.
- Mandatory recycled materials: to reduce their carbon impact, factories are required to use recycled raw materials. Paradoxically, these materials show greater variability and come with less historical knowledge of their behavior in the process. This increases scrap and rework until production is optimized.
Resilience by Design: Win Amid Raw‑Material Volatility and Rising Compliance Pressure
This has become a digital race: the pace of production, the volume of data, and the weight of compliance make manual approaches obsolete. Companies that connect traceability, analytics, and AI to daily operations will turn volatility into higher yield, lower cost, and faster decisions—while those that delay will keep paying for waste.
In industry, the primary challenge is to significantly reduce scrap, rework, and waste while complying with a changing market and increasingly stringent regulations. Global geopolitical instability introduces constant volatility that compromises supply chain stability and makes sourcing high-quality, consistent raw materials a constant struggle. Integrating data platforms and AI can help respond to these challenges, reduce scrap and rework, improve operational efficiency, and generate insights into internal factory processes and machine performance.
The impact on global performance
To effectively improve raw material performance, it is important to define waste correctly. Companies must shift their perspective from a binary view—which pits “good products” against “bad products”—to a multidimensional view in which “bad product” can be reused. Raw materials do not simply disappear; they flow into one of four distinct categories.
- Commercially valued finished products, meeting all quality specifications and ready for sale. Maximizing the share of raw material converted into this category is the core commercial objective.
- Non-compliant production, material that results in defective products and must be sold at a discount, reworked or recycled at an additional cost, or disposed of as unrecoverable waste. Reducing the volume associated with this category is a key performance indicator (KPI) and directly affects production throughput and cost.
- Co-products, secondary materials mechanically produced alongside the main product, which can be sold, repurposed, and valorized.
- Effluents, discharges, and other unrecovered losses, material lost to the environment, particularly through washing inefficiencies or equipment degradation, and disposed of without any form of recovery or valorization. Minimizing this category directly reduces environmental impact and operational costs.
Maximizing the valorisation of raw materials into finished products and co-products is key to reducing waste. By transforming portions of raw material that cannot be used for the original product into an alternative co-product, manufacturers can create a new revenue stream, maximize yield, and lower production costs.
