Garbage In, Compliance Out: The Hidden Cost of Poor Data Quality
There is a version of DPP compliance that is technically achievable without being meaningfully useful. It involves populating a digital passport with data — material composition figures, environmental indicators, supply chain references — that is structured correctly, formatted to specification, and present in the required fields. The passport exists. The QR code resolves. The auditor can see the record.
The data behind it is estimated, aggregated, unverified, or last updated three seasons ago.
This version of compliance is not hypothetical. It is the direction many organisations will travel if the DPP is managed as a documentation exercise rather than a data quality one. It satisfies the letter of the requirement — for a while. And it creates liabilities that are, in some respects, worse than non-compliance.
The Green Claims Directive makes this concrete. It exists precisely because a high proportion of sustainability claims in the market — 59%, according to European Commission research from 2024 — are vague, misleading, or unverifiable. Its reach extends to claims made in digital form, which means a DPP containing inaccurate or unsubstantiated data is not a protected compliance document. It is a published claim. And a published claim that cannot be substantiated is an exposure.
That exposure is wider than most organisations have mapped. The same data required for DPP purposes will appear, in various forms, in sustainability reports, on product pages, in marketing materials, and in procurement tenders. When those data points draw from the same underlying record — and that record is inaccurate — the exposure is not limited to one regulatory framework. It propagates across every channel in which the claim was made.
Poor data quality has a particular texture in this industry. It is rarely deliberate falsification. It is usually accumulation — small approximations at the point of collection, averaged figures substituted for product-specific ones, certifications applied to material categories rather than the materials in a specific product.
Each of those choices is understandable in isolation. Supplier data is hard to get. Time is short. The benchmark is close enough. But the accumulation across a product range produces a data set that is systematically less accurate than it appears — and most problematic at precisely the moments when accuracy matters most: a regulatory inquiry, a green claims challenge, an investor disclosure, a procurement process that uses DPP data as a qualification condition.
The inaccuracy is invisible in normal operations because nothing tests it. The DPP, and the scrutiny that will surround it, will.
Data quality is not primarily a technical problem. The instinctive response to a data quality concern is to look for a data management solution — better validation rules, stricter ingestion controls, a more robust master data system. Those tools matter. But data quality in a supply chain context is determined upstream of any system, at the point where information is first created or collected.
A supplier providing estimated figures because the actual measurement process is too costly for the commercial relationship being offered will continue to provide estimates regardless of the system receiving them. A material composition claim accurate at product launch but never updated after a supplier input change will remain inaccurate regardless of how well it is stored. The quality problem lives in the decisions that precede the data: what to measure, how to verify it, what relationship to build with the supplier who provides it, and who in the organisation is accountable for its ongoing accuracy.
Finance and Legal are the two functions most underrepresented in this conversation — and the two with the most direct stake in resolving it. The financial exposure from green claims liability, EPR fees based on inaccurate material declarations, and customs processes that will increasingly rely on DPP data is material. Not an abstract compliance risk. A quantifiable business risk that Finance should want to understand and price.
Legal's exposure is equally direct. Sustainability claims that cannot be substantiated, supply chain representations that conflict across disclosure documents, environmental indicators estimated and then published in a regulatory format — these are not hypothetical risks awaiting a future framework. The Green Claims Directive is in force. Greenwashing enforcement is active. The question of who owns the evidentiary standard behind a published claim is one most Legal teams have not yet been asked to answer systematically.
The cost of poor data quality is not paid at the point of collection. It is paid later, in ways that are harder to trace back to their origin. That delay makes it easy to underestimate — and easier still when the organisation is already navigating compressed margins, slowing sales, and supply chain uncertainty. The temptation to defer, in conditions like these, is understandable. It is also the moment when the gap widens most.
The commercial pressure makes the data quality argument more urgent, not less. Green claims enforcement does not pause for difficult trading conditions. Procurement qualification processes that turn on DPP data do not wait for margins to recover. The organisations building data capability now — under pressure, without ideal conditions — are accumulating an advantage that compliance-led competitors will find difficult to close when conditions improve.
What makes that harder than it sounds is that data quality is not a problem any single function can solve. The decisions that determine whether product data is trustworthy are distributed across the organisation in ways that most functions have not yet fully reckoned with. That reckoning is the next part of this conversation.
Michael Shea is a digital excellence advisor, non-executive director, and leadership coach working with organisations navigating the human and technical dimensions of digital transformation. He hosts The Aeolian Discourse and writes at The Aeolian.