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

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