A Few Important Tips for Accountants
The Omnibus package has flipped the ESG regulatory space on its head. Assurance is postponed. Data quality initiatives are shelved. And sustainability reporting starts to slip down the agenda.
But we’re here to tell you that stepping back from ESG data governance is not only a missed opportunity, it is also a strategic risk.
Data quality is the foundation for resilient decision-making, credible external communications, and long-term business value. Companies that treat ESG data with the same seriousness as financial data are better equipped to navigate market pressures, stakeholder expectations, and future regulatory changes.
While skipping assurance may reduce short-term costs, overlooking data quality can erode trust, obscure risks, and undermine strategy. In this article, we explore why ESG data quality still matters—and how companies can take practical steps to strengthen it, even without external pressure.
The Misconception: If It’s Not Required, It Can Wait
There is a growing belief among companies outside CSRD scope that ESG assurance can be deprioritized—or avoided altogether. If it’s not legally required, why invest in it now?
The problem with this thinking is that ESG data often lacks the basic structure, control, and consistency expected in financial reporting. Postponing improvements until assurance becomes mandatory only delays the inevitable—and makes the process messier, costlier, and more stressful later on.
Waiting often means relying on disconnected spreadsheets, ad hoc calculations, and unclear ownership. When the time for external review does arrive, teams scramble to rebuild data trails and justify numbers they barely remember calculating.
Even without formal assurance, a proactive ESG data review can strengthen internal confidence, reveal hidden risks, and lay the groundwork for smarter decisions. Companies that invest early in data quality avoid future firefighting and gain clarity they can act on now.
What We’re Seeing in Practice
In many organizations, ESG data collection remains an improvised and fragmented process. Teams often rely on dozens of Excel files — and sometimes even email threads—spread across departments, with no central oversight, version control, or standard process for verification.
Data is frequently pulled together reactively: for certifications, investor questionnaires, or client audits. But the moment someone asks how a number was calculated or where the original data came from, the answer is unclear—or missing altogether.
These gaps aren’t just inconvenient; they’re indicators of weak internal control. Without a reliable data foundation, ESG reporting becomes a patchwork effort that undermines credibility and makes future assurance far more difficult. What we’re missing is overall confidence in ESG data.
What’s at Stake
When ESG data quality is weak, the consequences extend well beyond reporting errors. Poor data affects strategic decisions, weakens stakeholder confidence, and increases reputational risk.
Externally, companies are expected to share ESG information with investors, banks, certifiers, and customers. If the data is inconsistent or cannot be backed up with clear documentation, it undermines credibility and trust. These stakeholders are increasingly basing real decisions—like financing terms and supplier selection—on ESG performance.
Internally, unreliable data sends the message that sustainability is not a serious priority. It becomes harder to secure buy-in, track progress, or hold teams accountable when ESG data is seen as fragmented or second-rate.
Ultimately, companies that fail to treat ESG data with the same discipline as financial data risk making strategic missteps and losing the confidence of both internal and external audiences.
Poor ESG data quality carries reputational, strategic, and financial risks. Externally, companies are increasingly expected to share ESG data with banks, clients, certifiers, and regulators. Inconsistent or unclear data reflects poorly and can damage trust.
Internally, weak ESG data processes signal that sustainability is not treated as seriously as financial performance. This affects both culture and engagement, making it harder to drive meaningful progress.
ESG data underpins strategic decisions, influences financing terms, and supports supplier and customer relationships. If the data isn’t credible, neither are the decisions based on it.
What Good ESG Data Management Looks Like
Strong ESG data management mirrors the rigour applied to financial reporting. It involves more than just collecting data—it requires clear governance, reliable systems, and repeatable processes.
At a minimum, well-managed ESG data should:
- Follow a documented process, with clear steps and owners
- Assign roles for data collection, review, and approval (with separation of duties)
- Store source data in a way that is secure, accessible, and traceable
- Use consistent definitions and calculations across reporting periods
- Include basic internal checks to validate completeness and accuracy
The goal isn’t perfection, but predictability. Reliable ESG data should withstand scrutiny, be reproducible, and support confident decision-making.
In short: if you wouldn’t accept a financial KPI without controls, don’t accept it for ESG either.
Reliable ESG data should follow the same basic principles as financial data:
- Clear process documentation
- Defined roles and responsibilities (data entry, review, approval)
- Secure and traceable storage of source data
- Transparent definitions and calculation methods
- Internal checks or separation of duties where feasible
This doesn’t mean every company needs an internal audit function. But it does mean asking: Who is responsible for data collection? Who reviews it? Can we easily trace the origin and calculation of key metrics?
Where to Start
Improving ESG data quality doesn’t require starting from scratch. Most companies already have internal control processes in place for financial reporting—these can often be adapted to ESG.
A practical way to begin is by focusing on two or three ESG topics, such as CO₂ emissions, water use, D&I statistics, or waste management. Map how data is currently collected, who is involved, and where risks or gaps exist. This exercise often reveals quick wins and helps lay the groundwork for broader improvements.
At Data For Better, we offer a structured Data Quality Check that results in a clear scorecard: highlighting what’s strong, what needs improvement, and what actions to take. We also tailor our recommendations based on the complexity of the topic—for example, water use data from a single utility provider is less complex than Scope 3 CO₂ emissions, which often involve manual inputs and supplier data.
The result is a practical roadmap—not just for assurance, but for better decision-making.
Data Quality is a Strategic Asset
Even without the external pressure of CSRD, ESG data quality remains essential. It strengthens business credibility, supports strategic decisions, and builds internal trust in sustainability performance. Instead of viewing data quality as a burden, companies should treat it as a tool for insight, alignment, and long-term value.
Organizations that invest early in their ESG data infrastructure are better positioned to adapt, report, and respond to growing expectations—from stakeholders, investors, and regulators alike.
Take the First Step
Not sure where to begin? Start with a Data Quality Check. It’s a fast, structured way to assess your ESG data practices and build confidence across your organization.
