The Circular Shift: Embedding Reuse and Recycling in Industrial Strategies

Moving from ESG commitments to measurable circular operations in Discrete Manufacturing

A joint 2025 report from Bain & Company and the World Economic Forum surveyed 491 manufacturing executives across 10 industries. 79% said circularity creates significant business value. Fewer than 1 in 5 had built circular supply chain capabilities they considered fit for purpose.

That gap tells a clear story. The recognition is there. The operational infrastructure is not.

For operations leaders in Discrete Manufacturing, the circular economy is no longer a boardroom concept. The EU's Ecodesign for Sustainable Products Regulation (ESPR) entered into force in July 2024. Digital Product Passports will be mandatory for targeted product categories from 2027. The CSRD requires granular disclosure of material use and waste data. And boards across Europe are asking the same question: when do our sustainability commitments show up in operational numbers?

The answer starts at the shop floor.

Key takeaways

• Circular economy strategies create measurable financial value in manufacturing, but fewer than 20% of companies have scaled them beyond pilot programs.
• The EU regulatory environment - ESPR, CSRD, and Digital Product Passports - is making data collection on material flows a compliance requirement, not just a sustainability aspiration.
• In Discrete Manufacturing, circular strategies live inside existing operational processes: scrap tracking, rework classification, production scheduling, and supplier return programs.
• Overproduction is the largest single driver of circular economy failure in manufacturing. Pull-based planning and demand-driven approaches reduce it at the source.
• Building circular operations requires the same data infrastructure as operational excellence: real-time visibility of material flows, integrated planning systems, and execution systems that capture what actually happens on the shop floor.
• The Operational Intelligence solutions that improve OEE and on-time delivery address the same underlying requirements as circular strategy: MES for material flow tracking, Factory Scheduling for changeover waste reduction, DDM+ for overproduction elimination, and Control Tower for cross-functional circular performance visibility.
• The business case is strongest when circular KPIs are linked to operational metrics (yield, scrap rate, OEE) that leaders already track.

The gap between circular ambition and circular operations

Pull any major manufacturer's annual report from 2024 and you will find a sustainability section. It will describe circularity targets, reuse commitments, and zero-waste ambitions. Then walk into the plant and ask the shift supervisor how much material was scrapped this week, how much of that scrap was recovered, and what the current rework rate is costing in materials.

Chances are good the answer involves a spreadsheet, an estimate, or a shrug.

This is not an indictment of the operations teams. It is a structural gap between where sustainability commitments are made and where the data to support them is generated. Board-level targets require operational-level measurement. For most Discrete Manufacturing organizations, that measurement infrastructure does not yet exist.

The Bain and WEF Circular Transformation of Industries report identifies four catalysts required to scale circular operations: technology and data (including IoT, digital tracking, and AI), people and culture, finance and investment structures, and policy and regulation. Technology and data rank first. Not because the other three do not matter, but because without data, circular commitments remain unverifiable, unmanageable, and ultimately unconvincing to the people who need to act on them.

The strategic question is not whether to pursue circularity. Competitive pressure, regulatory timelines, and customer expectations are answering that. The operational question is how to build the data infrastructure that makes circular strategies measurable, and therefore manageable.

What circularity actually means in Discrete Manufacturing

The Ellen MacArthur Foundation defines a circular economy around three principles: eliminate waste and pollution, circulate products and materials at their highest value, and regenerate natural systems. These principles scale down to specific shop floor decisions.

In Discrete Manufacturing, circularity operates across several practical levels:

Reduce means manufacturing less material waste per unit produced. This includes optimizing material yield (the ratio of input material to finished product), minimizing setup scrap during changeovers, and eliminating overproduction through tighter alignment between demand signals and production schedules.

Reuse means designing production processes and products so that components, subassemblies, or materials can be reintroduced into the production cycle without full reprocessing. This ranges from straightforward applications (reusing packaging materials internally) to more sophisticated programs (supplier return loops for partial-use components).

Remanufacture means restoring end-of-life products or components to their original functional specification. Research published in the journal Business Strategy and the Environment found that remanufacturing practices significantly improve quality and operational speed metrics. In sectors like automotive, electronics, and industrial equipment, remanufacturing is already a revenue stream, not just a sustainability initiative.

Recycle and recover represent the last resort in the value hierarchy: breaking materials down for reuse as inputs, or recovering energy from materials that cannot otherwise be recirculated.

Most Discrete Manufacturing operations are already engaging with these levels in some form. Scrap is being managed. Rework is being tracked. Returns from customers create reverse logistics flows. The difference between a manufacturer with a genuine circular strategy and one with a sustainability report is whether these activities are measured, connected to a plan, and actively optimized.

That requires operational systems capable of capturing material flow data at every stage of production.

The regulatory environment is accelerating the timeline

For operations leaders who prefer to build business cases on financials rather than sustainability narratives, the regulatory trajectory provides a more immediate driver.

The EU Ecodesign for Sustainable Products Regulation entered into force in July 2024. It expands product coverage to nearly all categories sold in the EU market and introduces mandatory requirements for durability, repairability, and recyclability at the design stage. Unlike its predecessor directive, which focused primarily on energy efficiency, ESPR treats circularity as a core product characteristic.

The ESPR also introduces Digital Product Passports: structured data records attached to each product that document its materials composition, repair and recycling instructions, and lifecycle information. For targeted product categories, these will be mandatory from 2027. Compliance requires manufacturers to have data about their products' material content, which means tracing inputs at a granularity most current MES implementations do not provide.

The CSRD adds a parallel layer. Companies in scope must disclose material flows, including the ratio of recycled inputs to virgin materials, waste generation by category, and the fate of materials at end of product life. Manual reporting for these disclosures is possible for a single reporting cycle. It is not sustainable as an ongoing operational practice.

Eurostat data published in late 2025 shows the EU circular material use rate reached 12.2% in 2024, the highest on record but still less than half the 2030 target of approximately 23%. For metal ores specifically - a core input category for Discrete Manufacturing - the circularity rate was 23.4%. That number is meaningful: it means more than three-quarters of metal ore inputs still come from virgin extraction. The gap between current performance and EU policy targets is large enough to drive regulatory tightening, not relaxation.

Taken together, ESPR, CSRD, and the DPP timeline create a data collection requirement that is most efficiently met by building proper material tracking into production systems, rather than retrofitting it through manual processes each reporting cycle.

Where circular strategies live inside manufacturing operations

The practical entry points for circular strategy in Discrete Manufacturing are not found in a new sustainability department. They are found in the operational processes that already run every day.

Scrap and rework management. Every Discrete Manufacturing facility generates scrap and rework. How much of it is measured in detail, by material type, by production stage, and by root cause, varies enormously. A facility that knows its scrap rate is 3.2% is in a different position from one that knows scrap is highest on the third shift, concentrated in one material type, and traceable to a specific tooling configuration. The second level of detail is what enables circular interventions. Without it, reduction programs are guesswork.

Manufacturing Execution Systems capture the data that makes this detail possible. When production events are recorded at the machine and operator level in real time, scrap patterns become visible that batch-level reporting misses. Elisa IndustriQ's MES software solutions track material consumption, scrap events, and rework classification at the workstation level as a live operational record, not a monthly summary. That means an operations team can identify that 60% of material waste in a given product family originates at a specific workstation, on a specific shift, linked to a specific tooling configuration. That level of specificity is the difference between a circular KPI that moves and one that stays flat regardless of effort. It is also the level of granularity that Digital Product Passport compliance will require from 2027: material traceability built into production, not reconstructed from memory at year-end.

Changeover and setup waste. In high-mix Discrete Manufacturing environments, changeovers generate disproportionate material waste. First-article rejects, purging losses, and setup scrap often represent a larger share of total waste than in-cycle defects. Sequencing production to minimize changeovers, or at least to cluster similar setups, directly reduces this waste category without a dedicated waste reduction program. sedApta Factory Scheduling optimizes job sequences by grouping orders with compatible setup requirements, balancing on-time delivery targets against changeover frequency. When changeover frequency drops, setup scrap drops with it. The circular improvement is a side effect of better scheduling, not a separate initiative, which is exactly why it tends to stick.

Yield and first-pass quality. First-pass yield, the percentage of units completing production without rework, is simultaneously an efficiency metric and a circular metric. Every unit requiring rework consumes additional energy, labor, and materials. Improving first-pass yield improves resource efficiency at the most fundamental level. The connection between quality systems and circular performance is direct, but rarely framed that way.

Reverse flows and supplier return programs. In many Discrete Manufacturing value chains, unused components, partially consumed materials, and packaging represent significant circular opportunities if return programs exist. Building these flows requires supplier collaboration infrastructure and logistics coordination, but the economics are often compelling, particularly for high-value components or regulated materials.

Connecting planning decisions to material efficiency

Here is a dynamic that most circular economy discussions miss: the largest single driver of material waste in manufacturing is not poor scrap management. It is overproduction.

Producing more than demand requires stores, consumes materials, risks obsolescence, and creates downstream waste when excess inventory is eventually scrapped or discounted. For operations leaders focused on circular performance, the upstream planning decisions that determine batch sizes, safety stock levels, and production sequences have as much impact as any downstream recycling program.

Demand Driven Manufacturing approaches address this at the root. The DDM+ logic replaces forecast-driven push with buffer management anchored to actual consumption: production orders are triggered when inventory buffers are drawn down, not when a model predicts they might be. Production quantities are therefore sized to what customers are actually consuming, not what a planning system estimated months earlier. When production volumes align with real demand, the cycle of overproduction, excess stock, and eventual write-off breaks. That is circular strategy at the planning level: waste eliminated before it is created, rather than managed after.

The article Shaping the Future of Discrete Manufacturing covers the planning-execution gap in detail. The connection to circularity is worth making explicit: when planning decisions are disconnected from execution reality, production runs against incorrect signals, generating overproduction, excess changeovers, and material waste that circular programs then have to recover. Closing the planning-execution gap is circular strategy by another name.

The same logic applies to supply planning. Procurement decisions that optimize unit cost without visibility into actual consumption patterns generate excess inventory and material risk. When demand signal accuracy improves, purchasing becomes more precise, safety stock requirements fall, and the circular burden of managing excess reduces accordingly.

For operations leaders managing both cost and sustainability objectives, the insight is practical: investment in planning integration and demand signal accuracy improves circular performance as a side effect of improving operational efficiency. The two goals are not competing. They are the same goal measured from different angles.

Turning circular commitments into measurable outcomes

The board meeting where circular commitments are made is not the right venue for designing the operational infrastructure that delivers them. That design work happens at the intersection of operations, IT, and sustainability functions, and it requires a structured approach.

Real-time visibility across material flows, from incoming raw materials through production stages to finished goods and waste streams, is the foundation. Without it, circular KPIs are estimates. Elisa IndustriQ's Simulative Control Tower connects data from planning, production, and logistics into a single operational view, so an operations director can see scrap generation, yield trends, and material consumption broken down by line, shift, or product family, in real time rather than through monthly reports.

The "simulative" dimension matters specifically for circular strategy. Before committing to an intervention - resequencing a production line to reduce changeovers, launching a supplier return program, or adjusting batch sizes to reduce obsolescence risk - teams can model the likely circular outcome against current operational data. That turns circular decisions from intuition into evidence. An operations director who can present the board with a modeled scenario showing projected waste reduction against a defined investment is in a materially different position from one who can present only intentions.

With visibility in place, circular KPIs become manageable in the same way that any other operational metric is managed: scrap rate by material category, rework percentage by production stage, recycled input ratio for key material classes, yield trajectory over time. These metrics connect sustainability commitments to the operational numbers that drive daily decisions.

From circular commitment to circular operations: a 7-step framework

Getting from a sustainability target to an operational circular program requires a structured sequence. The following framework reflects how mature organizations build this capability:

• Baseline your material flows. Before setting circular targets, establish what actually happens to materials in your facility. Map inputs, in-process consumption, scrap categories, rework volumes, and waste streams. An MES that captures material events at the workstation level provides this baseline automatically and continuously. Without it, the mapping exercise is a manual audit that will be outdated by the time it is complete.
• Connect sustainability KPIs to operational metrics. Circular targets set at the board level (percentage recycled content, zero-waste-to-landfill) need operational counterparts. Identify the shop floor metrics - scrap rate, first-pass yield, rework percentage, overproduction rate - that directly drive the sustainability outcomes you are committing to.
• Audit your data infrastructure. Review what your current MES, ERP, and quality systems actually capture about material flows. If scrap is recorded at the machine level in real time, you have the raw material for circular reporting. If it is logged in shift reports and consolidated monthly, you have a gap. The most common obstacle to circular measurement is not missing strategy - it is missing granularity in execution data.
• Prioritize the highest-impact circular lever. For most Discrete Manufacturing operations, one of three areas will dominate: overproduction (addressed through planning logic such as DDM+), changeover and setup waste (addressed through intelligent production scheduling), or scrap and rework (addressed through MES-driven quality visibility and root-cause analysis). Start where the volume is largest and the data already supports measurement.
• Implement traceable material tracking at the production stage. Close the data gap by ensuring that material consumption and waste events are captured at the machine or workstation level, in real time, and classified by type. This step is also a DPP compliance prerequisite: material traceability built into production from 2024 onward avoids the costly retrofit that companies who delay will face.
• Build circular performance into operational reviews. Circular KPIs gain traction when they appear alongside OEE, OTIF, and cost metrics in the same review forums. A Control Tower that surfaces scrap rate, yield trends, and material consumption in the same view as delivery performance makes this integration natural. When a plant manager sees scrap rate alongside availability and quality in the weekly operations review, it becomes an operational responsibility, not a sustainability team metric.
• Close the loop with suppliers and customers. Fully circular strategies extend beyond the factory boundary. This means collaborative programs for component return, material recovery, and packaging recirculation. These take longer to build and require supplier agreement, but they represent the highest-value circular opportunities for many Discrete Manufacturing value chains.

Closing the gap

The distance between a circular commitment and circular operations is a data and infrastructure problem as much as a strategic one. The organizations closing that gap are not necessarily the ones with the most ambitious sustainability targets. They are the ones that treat material flow visibility with the same seriousness as production visibility.

For operations leaders in Discrete Manufacturing, the opportunity is significant. The regulatory timeline is real. The board expectations are real. And the operational infrastructure to support both, tracking materials from input to output, connecting planning decisions to material efficiency, making circular performance measurable and manageable, is available and proven.

The circular shift is not a departure from operational excellence. It is operational excellence applied to the full material lifecycle.

Explore more: For operations teams building the data foundation that circular strategy requires, Shaping the Future of Discrete Manufacturing covers the visibility and planning integration priorities that underpin both operational and sustainability performance.