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How Data, Standards, and Automation Are Reshaping Environmental Product Declarations

Key Takeaways from the Digital EPD Session at eClad Conference

1. The EPD market is Scaling Fast, but the Foundation is Still Fragmented

EPDs are growing rapidly across industries, driven by regulatory pressure, customer demand, and procurement requirements. But the underlying systems have not kept pace. As Robert highlighted, the EPD ecosystem has evolved organically over time. Different regions, standards, tools, and workflows have developed independently.

The result is a fragmented landscape where:

    • Data formats are inconsistent
    • Processes vary by region and program operator
    • Digital workflows are not fully standardized
    • Scalability remains limited

This creates a fundamental challenge. The industry is trying to scale outputs without first standardizing the data infrastructure.

2. The Real Bottleneck is Not EPD Creation – It’s the Data.

Across every EPD workflow, the same bottlenecks appear:

    • Data collection
    • Data transformation
    • Data completeness and consistency
    • LCA modeling
    • EPD & LCA verification
    • Non-harmonized calculation rules

These challenges are not new. But they become exponentially more complex as companies try to scale across hundreds or thousands of products. The takeaway is clear: EPD challenges are not primarily about reporting. They are about data architecture.

3. Digital EPDs are the Path Forward. But Only if Done Correctly

Digital EPDs have the potential to solve many of these challenges.

They enable:

    • Automated data validation
    • Structured, machine-readable datasets
    • Faster integration into downstream systems
    • Scalable lifecycle assessments

However, the current reality is more complicated. In many cases today, the process is still reversed. Teams generate a PDF first, then manually transfer data into digital formats. This introduces errors, inconsistencies, and inefficiencies.

The future state is the opposite. A digital dataset should be the single source of truth. From that, any human-readable format, including PDFs, can be generated.

4. Verification Must Evolve to Support Automation and Scale

As EPD volumes grow, traditional verification approaches become a bottleneck.

The current verification guidelines are often:

    • Tool-specific instead of tool-agnostic
    • Lacking detailed requirements
    • Not designed for automated workflows

To address this, new approaches are emerging that focus on:

    • Tool-based verification frameworks
    • Logging and traceability of data and mapping
    • Scalable validation processes
    • Integration of AI-assisted verification

The goal is not just faster verification. It is more consistent and reliable verification at scale.

5. The Shift to Digital Enables Interoperability and Global Alignment

One of the biggest barriers to scaling EPDs today is lack of harmonization. Different program operators, regions, and standards require different formats and calculations. This creates duplication, inefficiency, and inconsistencies.

Digital EPD initiatives aim to solve this by:

    • Standardizing machine-readable formats
    • Enabling interoperability across systems
    • Reducing reliance on region-specific PDF formats
    • Supporting global comparability

This is a foundational shift. It moves EPDs from static documents to interoperable data assets.

6. EPDs are Not the End Goal. Decision-Making Is.

One of the most important points from the session was simple but critical. Companies are not creating EPDs just to have EPDs. They are creating them to enable better decisions.

Whether at the product level, building level, or portfolio level, EPD data should support:

    • Material selection decisions
    • Product design improvements
    • Procurement strategies
    • Regulatory compliance

Without this connection to decision-making, EPDs remain a reporting exercise rather than a business capability.

The Core Problem: EPD Workflows Are Not Built for Scale

Across industries, the challenge is consistent. Organizations are trying to scale EPDs using processes that were never designed for volume, speed, or interoperability.

This leads to:

    • Manual, time-intensive data collection
    • Inconsistent and non-harmonized datasets
    • Duplicated effort across regions and standards
    • Limited ability to reuse or integrate data
    • Slow and costly verification processes

The result is a system that struggles to keep up with growing demand.

The Solution: From EPD Documents to Product Lifecycle Intelligence

The path forward is not just digitization. It is transformation. Instead of creating EPDs one by one, the model shifts to:

    • Ingest all available product and supply chain data
    • Structure it into a unified, digital data model
    • Create digital twins of products
    • Apply logic to generate lifecycle insights
    • Output results across multiple use cases

This approach enables:

    • Automated EPD generation
    • Substance compliance analysis
    • Lifecycle impact modeling
    • Continuous data improvement

All from the same underlying data foundation. This is what Makersite defines as Product Lifecycle Intelligence.

From Data to Decisions: Why This Matters Now

For manufacturers and construction stakeholders, this shift is critical. The market is demanding:

    • More EPDs
    • More specific EPDs
    • Faster turnaround
    • Higher data quality
    • Greater transparency

At the same time, products are becoming more complex and configurable. This creates a new requirement: the ability to generate accurate, scalable, and decision-ready environmental data.

Companies that can do this gain a significant advantage:

    • Faster compliance and reporting
    • Improved product design decisions
    • Reduced operational effort
    • Stronger, more credible sustainability claims

What the Market Is Moving Toward

The conversation is changing. Organizations are no longer asking: “Can we create EPDs?”

They are asking:

    • Can we scale EPDs across entire product portfolios?
    • Can we trust and verify the data consistently?
    • Can we integrate EPDs into digital workflows and systems?
    • Can we use EPD data to drive real decisions?

This reflects a broader shift:

    • From static documents to dynamic data
    • From manual workflows to automated systems
    • From reporting outputs to decision intelligence

Final Thought

The biggest takeaway from the session: EPDs are evolving from documents into infrastructure. Digital EPDs, standardized data models, and automated workflows are not just improving reporting. They are enabling a new foundation for environmental decision-making.

By moving toward connected, digital, and scalable data systems, organizations can turn EPDs from a compliance requirement into a strategic capability.

Want to Scale EPDs Without Scaling Manual Effort?

If your team is working to:

    • Automate EPD generation
    • Improve data quality and consistency
    • Reduce verification bottlenecks
    • Connect EPDs to product and design decisions

See how Makersite enables digital EPD workflows, lifecycle intelligence, and scalable sustainability insights across your product portfolio.

Download Makersite’s EPD ebook 

Electronics On-Demand: Turning Component Data into Sustainable Product Decisions

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Key Takeaways

Pressure is mounting from every direction. Customers demand product carbon footprints and configuration-level reporting. Regulators are raising expectations for material transparency and compliance documentation. Engineering teams must move faster. Procurement needs better supplier visibility and alternatives. Sustainability teams are expected to deliver precise answers that legacy product data environments cannot support. 

That is why we hosted the Electronics On-Demand Masterclass with SiliconExpert. The session showcased a practical shift across the electronics industry. Manufacturers must move beyond fragmented BOMs, generic assumptions, and manual supplier outreach by connecting component-level intelligence to lifecycle modeling. This enables faster, more accurate sustainability, and compliance decisions. 

At the center of this shift: SiliconExpert supplies authoritative component intelligence and materials and compliance data. Makersite transforms that data into lifecycle insights and product-level decisions. Put simply, SiliconExpert supplies the ingredients, and Makersite is the chef that turns them into five‑star sustainability outcomes.

1. Component-level data is the missing link in electronics sustainability

Ambition is not the barrier. Usable data is. Most manufacturers only have MPNs on their BOMs. What is missing is validated material composition, environmental impact metrics, and compliance status needed for PCFs, LCAs, and eco design. Without component-level intelligence, sustainability work relies on estimates instead of defensible insights.

2. PCFs require part-specific modeling, not generic assumptions

Demand for PCFs across data center infrastructure and enterprise electronics exposes the limits of average weights and generic datasets. These approaches fail to support: 

    • Supplier-level comparisons 
    • Component-level optimization 
    • Configuration-specific reporting 
    • Defensible customer disclosures 

Manufacturers need part-specific, BOM-level modeling to be credible and actionable.

3. Compliance and sustainability converge into a single workflow

RoHS, REACH, and other compliance data are increasingly the same inputs required for sustainability analysis. Leading companies combine compliance and sustainability into one workflow. Component intelligence feeds both regulatory reporting and environmental decision-making.

In this collaboration SiliconExpert delivers compliance data, IPC material declarations, and component specifications. Makersite automates lifecycle modeling and sustainability insights from that data

4. Eco design becomes actionable when data enters engineering early

A powerful outcome from the session was the ability to compare qualified component alternatives by environmental impact. Example results included: 

    • Approximately 10 percent reduction in carbon footprint from a single part swap
    • Additional reductions in water use 

This is the difference between reporting an impact and reducing it. When sustainability data is available inside engineering and sourcing workflows, it becomes a lever for product improvement.

5. Scale is unlocked by reducing manual supplier data collection

Manual FMD requests, spreadsheet harmonization, validation, and model building does not scale across thousands of components. Makersite and SiliconExpert change the equation: 

    • 75 to 85 percent or more of electronic components already have data coverage 
    • Supplier data collection effort can be reduced by up to approximately 90 percent 

This turns sustainability from a resource-heavy project into a scalable capability across product portfolios. 

The Core Problem: Lacking Usable Component Data

The industry faces consistent challenges: 

    • BOMs listing MPNs but lacking material composition 
    • Fragmented compliance datasets 
    • Manual supplier workflows 
    • Disconnected sustainability modeling 

These gaps make it difficult to answer critical questions: What is the PCF for a product or configuration? Which component alternative lowers impact? Where are high-impact materials or compliance risks? How do we scale across thousands of parts? 

The issue is not the absence of data. It is the absence of connected usable component-level data. 

The Solution: Connect Component Intelligence to Product Decisions

The Electronics On-Demand approach turns disconnected component data into usable sustainability and compliance insights. It starts with the BOM and MPNs, enriches parts with material and compliance context, and translates that into lifecycle insights for full product impact assessment. Outcomes include: 

    • Product carbon footprints at BOM and configuration levels 
    • Lifecycle impact insights across multiple categories 
    • Compliance and material risk visibility 
    • Supplier and alternative comparisons 

Instead of manual collection and modeling for thousands of parts, teams can adopt a scalable flow where sustainability and compliance insights are generated alongside product decisions. 

This is a shift from data collection to decision intelligence. 

From Data to Decisions: Why This Matters

For data center suppliers and electronics manufacturers, this is a business capability, not a side project. Customers expect: 

    • Product carbon footprints 
    • Configuration-level reporting 
    • Material transparency 
    • Fast, defensible responses to sustainability questionnaires 

Products are becoming more configurable and more dependent on complex supply chains. This creates a requirement to generate accurate, component-level sustainability insights at speed. Companies that can do this gain a clear advantage: 

    • Faster customer response times 
    • Stronger, credible sustainability claims 
    • Better product design decisions 
    • Lower operational effort 

The Market is Moving

Electronics Manufacturers have moved beyond asking, “Can we do LCA for electronics?” 

They are now asking: 

    • Can we scale across thousands of components? 
    • Can we trust the data? 
    • Can we use it in real decisions, not just reports? 
    • Can we embed it into PLM and engineering workflows? 

The market is shifting from data collection to data confidence to decision intelligence. 

Real World Examples

ThinkPad can now generate more precise, traceable, and defensible PCFs that look beyond model-level estimates

Lenovo used Makersite to deliver configuration‑level, ISO‑aligned PCFs across enterprise products. By structuring millions of supplier FMDs and adopting component‑level modeling, Lenovo replaced portfolio averages with auditable, configuration‑specific footprints—speeding reporting, strengthening sustainability claims, and improving bid competitiveness.

See how Makersite helped Lenovo >

Microsoft reduce the carbon footprint of Surface Pro 10 by up to 28%

Makersite partnered with Microsoft to operationalize a repeatable, auditable LCA methodology that scales supplier‑validated LCAs across product lines. By ingesting supplier FMDs and integrating BOM‑level modeling into engineering workflows, Microsoft moved from generic portfolio estimates to traceable, configuration‑ready lifecycle insights—raising supplier data coverage from ~20% to ~70%.

Learn how Makersite is used for ecodesign >

 

Final Thought

Sustainability in electronics starts at the component level. Value is unlocked when that component data drives decisions. By combining SiliconExpert component intelligence with Makersite’s AI-driven lifecycle modeling, manufacturers can move from fragmented data to scalable, decision-ready sustainability insights.

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