Most brands know EPR is coming. Very few realize how unprepared their packaging data actually is.
In our last article, we broke down why 2026 is a step‑change year for packaging EPR as brands gear up to report.
This follow‑up article focuses on what underpins every EPR obligation, every fee calculation, and every audit question:
The elephant in the room, your packaging data.
For many brands, compliance challenges aren’t caused by misunderstanding the regulation (that’s its own can of worms). They’re caused by lack of actionable data that has never needed to be collated at a granular level before. Organising your data, collecting it, having a single source of truth.
It's not sexy, but it's necessary. Skipping this step and just trying to cobble together a best-guess report creates the illusion of progress while institutionalizing uncertainty into a (growing) recurring cost as more states adopt packaging EPR.
How EPR Compliance Is a Data Problem First
EPR reporting requires you to prove, at SKU and component level, what packaging you put on the market, where, and in what quantities.
That proof is entirely data‑driven.
To meet EPR packaging data requirements, producers must reliably answer questions like:
- Which SKUs were sold into which states? When? To whom?
- What is the full packaging bill of materials (BOM) for each SKU?
- What are the various component-level attributes—material type, physical dimensions, plastic composition, weight, labeling, and end‑of‑life treatment?
- How much of each material type was sold in market?
- Where did those data points come from, and can they be defended?
Combining the answers to these questions may sound like simplistic, logical math. And it is, if the underlying data is accessible, consistent, and reliable. In practice, many brands assume they already have what they need and can work it out later. That assumption is where problems begin.
“We Have The Data” Is an Expensive Assumption
Many teams believe they already have what they need because packaging data exists somewhere in the organization.
In reality, packaging data is usually:
- Fragmented — scattered across PDFs, spreadsheets, ERP exports, and supplier files
- Incomplete — missing component-level details or relying on outdated specs
- Inconsistent — conflicting formats, units, and assumptions across teams
- Unowned — no clear accountability internally for accuracy over time
The right question isn’t whether you have packaging data, it’s how actionable, trustworthy, and complete is your data to report so your business understands what you will be paying on a SKU-level and why?
What passed for complete in the first reporting cycle becomes a liability as programs mature. States are tightening validation in year two. Oregon DEQ has made the risk explicit: poor or missing packaging data can place brands on a public non-compliance list, trigger audits, and result in fines of up to $25,000 per day, with escalating consequences that can restrict product sales in the state.
When gaps are discovered late, teams default to estimates and conservative assumptions.
Those assumptions don’t increase risk — they increase fees.
Poor Data Quality Drives Higher EPR Fees
EPR fees are calculated directly from reported packaging data.
When weights are overstated, materials are misclassified, or redundant SKUs are included “just to be safe,” brands quietly lock in higher annual obligations.
This is how EPR can quickly become a seven‑figure problem:
- Estimates inflate reported material volumes
- Inflated volumes increase fee exposure across multiple states
- Errors compound year over year as bad data is reused
Without a structured system, finance teams are left reacting to invoices instead of forecasting exposure.
Good data doesn’t just reduce compliance risk. It restores financial control.
Why Spreadsheets Break at Scale
Spreadsheets have been foundational business tools since the early 1980s.
But they are risky as a system of record for packaging data in the EPR compliance era for a plethora of reasons.
1. Spreadsheets Are Ill-Suited To Be Load-Bearing Infrastructure
As EPR expands across states, spreadsheets fail structurally because they:
- Flatten complex reality, making it impossible to enforce multi-dimensional data structures and relationships across SKUs, components, materials, and jurisdictions
- Rely on human, error-prone workflows, with mistakes compounding as files grow; studies suggest the majority of large spreadsheets contain significant errors
- Lack defensible auditability, with no clear provenance, versioning, or trust layer
- Break when supplier data changes, forcing manual rework across every dependent file
- Accept errors silently, allowing gaps, conflicts, and assumptions to persist unnoticed
- Multiply as regulations diverge, creating conflicting files by state, year, and reporting cycle
- Offer weak security, governance, and scalability for non-harmonized regulatory data
2. EPR Forces Constant Data Translation
EPR reporting requires packaging data to be pulled from dozens, hundreds, or even thousands of sources — supplier PDFs, specifications, ERP exports, emails, and historical files — and then translated into different versions for each jurisdiction’s reporting requirements.
Every change, whether a new supplier spec, an updated weight, or a new state rule, triggers re-mapping columns, converting units, adjusting formulas, and rechecking assumptions.
3. Manual Upkeep Means Increased Headcount
This level of manual upkeep simply doesn’t scale.
It turns spreadsheets from a solution into a burden, from a tool into a full-time job spent babysitting files, not improving data quality or helping the business reduce EPR fees.
4. Dashboards Create a False Sense of Control
Spreadsheets, even Power BI dashboards built on top of them, can produce polished charts. But those visuals only reflect the inputs beneath them.
If the underlying data is estimated, outdated, or assumption-heavy, the insights are too.
What looks like control is often uncertainty dressed up as well-formatted work.
5. Scale Is the Breaking Point
At 50–100 SKUs, a spreadsheet approach may feel manageable.
At hundreds or thousands of SKUs, it becomes expensive technical debt — locking teams into reactive compliance and making meaningful EPR fee optimization impossible.
Wrangling Your Packaging Data Is a Job For Software
Why hire human data wranglers when suitable technology exists delivering cheaper, faster, and more accurate outcomes?
The brands navigating EPR successfully in 2026 know their starting point. They understand their exposure, their gaps, and their path forward because they operate from a single, structured source of truth powered by fit-for-purpose software.
This is exactly what Unpac was built to do: ingest fragmented data sources into a centralized system of record that normalizes packaging data once and reuses it everywhere.
When packaging data is structured and owned:
- Reporting becomes repeatable, not disruptive
- Fee exposure can be modeled before invoices arrive
EPR isn’t getting simpler. But it can become manageable.
Final Thought
EPR rewards precision and penalizes ambiguity.
If your packaging data isn’t ready to stand up to scrutiny, compliance will remain costly, reactive, and increasingly difficult to unwind over time.
If it is, EPR becomes just another process your business runs well.
If you want to understand the true state of your packaging data, the Unpac team can help.
Stay tuned for more articles breaking down state-specific requirements, packaging data management strategies, and how leading brands are operationalizing EPR at scale.