For many ESG and Sustainability Managers across the UK and Western Europe, 2026 feels like a tipping point. Expectations have accelerated. Reporting requirements have expanded. Scrutiny – from auditors, regulators, investors, and internal leadership – has intensified.
Yet the uncomfortable truth is this: most ESG challenges organisations are facing today are not sustainability problems at all. They are data problems.
This distinction matters. Because while sustainability teams are often tasked with “fixing ESG”, the root causes of missed deadlines, inconsistent disclosures, audit anxiety, and burnout are almost always structural failures in how ESG data is collected, governed, and used.
Understanding this shift – from sustainability as a values-led function to ESG as a data-driven discipline – is the key to real readiness.
ESG teams are drowning in responsibility, not authority
If you work in ESG or sustainability today, your objectives probably look something like this:
- Deliver compliant ESG disclosures across multiple frameworks
- Improve data quality and confidence year on year
- Coordinate inputs from Finance, Operations, HR, Procurement, and Supply Chain
- Prepare for external assurance and internal scrutiny
- Support long-term sustainability strategy, not just reporting
- Do all of the above with limited headcount and budget
On paper, this is a sustainability remit. In practice, every single one of these objectives depends on data – its availability, accuracy, structure, and governance.
And yet, many ESG teams are expected to deliver outcomes without owning the systems that make those outcomes possible.
Compliance is the first place data cracks appear
For most organisations, ESG readiness begins, and often ends with reporting compliance.
Whether the driver is ISSB, CSRD, ESRS, or UK sustainability disclosure requirements, the challenge is rarely understanding what needs to be disclosed. The challenge is answering a far more difficult question:
Can we reliably produce the data to support these disclosures, repeatedly and under scrutiny?
Spreadsheets, shared drives, and manual data requests might work once. They rarely work twice. And they almost never survive audit.
Data issues show up fast:
- Multiple versions of the “same” metric
- Unclear ownership of inputs
- Late or missing supplier data
- Inconsistent calculations year to year
- No audit trail explaining how numbers were derived
At that point, compliance stops being a sustainability exercise and becomes a data integrity problem – one that ESG teams are expected to solve without the right infrastructure.
Audit readiness is a data governance challenge, not a reporting exercise
As ESG disclosures move toward assurance, the role of ESG teams is changing again.
Auditors don’t just ask what you reported. They ask:
- Where did the data come from?
- Who owns it?
- How was it calculated?
- What controls exist?
- Can you reproduce it?
These are not sustainability questions. They are data governance questions.
Many organisations underestimate how quickly ESG reporting begins to resemble financial reporting in terms of expectations. Once assurance enters the picture, ESG data must be:
- Traceable
- Consistent
- Version-controlled
- Defensible
This is where manual approaches collapse. Not because teams aren’t trying hard enough, but because the data architecture was never designed to support assurance in the first place.
Scope 3: where sustainability ambition meets data reality
No area exposes the data challenge more starkly than Scope 3 emissions.
Sustainability leaders know Scope 3 matters. Regulators know it. Investors know it. But managing Scope 3 is less about environmental theory and more about operational data realities:
- Thousands of suppliers
- Inconsistent data maturity
- Partial or estimated information
- Different formats, standards, and timelines
Without structured data processes, ESG teams end up spending their time chasing information instead of analysing it.
The result is frustration on all sides:
- ESG teams feel overwhelmed
- Suppliers feel confused or disengaged
- Leadership questions the reliability of outputs
Again, the problem isn’t commitment. It’s data design.
Strategy stalls when data isn’t decision-ready
Most sustainability professionals want to move beyond compliance. They want ESG to inform decisions, not just reports.
But strategy requires confidence in the underlying data.
If leaders don’t trust the numbers, they won’t:
- Prioritise investments based on ESG insights
- Set credible targets
- Use ESG data in capital allocation or risk discussions
This is why many sustainability strategies stall. Not because ambition is lacking, but because the data foundation isn’t strong enough to support decision-making.
Data that is fragmented, late, or unreliable cannot drive strategy – no matter how compelling the narrative around it may be.
Why ESG teams are being set up to struggle
One of the most persistent problems in ESG is organisational misalignment.
Sustainability teams are accountable for outcomes, but rarely control:
- Source systems
- Data standards
- Calculation logic
- Technology investment decisions
ESG data often lives across Finance, Operations, HR, Procurement, and external partners. Without a unifying data model and clear governance, ESG teams are forced into a coordination role without authority, managing complexity without the tools to control it.
This is not a failure of sustainability leadership. It is a structural issue that requires a different solution.
Reframing ESG readiness as a data capability
Organisations that are genuinely ESG-ready tend to share a common mindset shift:
They treat ESG data as a core business asset, not a reporting by-product.
This reframing unlocks progress.
Instead of asking, “How do we complete this year’s report?”, they ask:
- How do we design ESG data once, and reuse it many times?
- How do we automate repetitive data tasks?
- How do we reduce dependency on individuals?
- How do we build confidence year after year?
From this perspective, ESG readiness becomes a capability-building exercise, not an annual fire drill.
Practical steps toward ESG data excellence
For ESG and sustainability leaders looking to regain control, a few principles consistently make the difference:
1. Centralise ESG data, don’t chase it
Create a single system of record for ESG data. Fragmentation is the enemy of confidence.
2. Standardise before you optimise
Agree definitions, calculation methods, and ownership before worrying about sophistication.
3. Automate what humans shouldn’t be doing
Manual checks, framework mapping, gap identification, and data validation are ideal candidates for automation.
4. Design for audit from day one
If you can’t explain how a number was created, it won’t survive scrutiny later.
5. Treat ESG data as ongoing, not annual
Continuous data management reduces year-end stress and improves quality over time.
The future ESG leader is a data leader
This shift does not diminish the importance of sustainability expertise. It elevates it.
The most effective ESG leaders in the coming years will be those who:
- Understand sustainability deeply
- Speak the language of data and governance
- Build systems that scale beyond themselves
Because in 2026 and beyond, ESG readiness won’t be judged by intent or ambition, but by the quality, reliability, and usability of the data behind it.
And that is why ESG readiness is, fundamentally, a data problem.
Find out more
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Written by Innes Christison
Senior Sustainability Business Analyst
With experience as a Head of Sustainability and supply chain expert, Innes has helped brands including Tesco, KFC and Wowcher turn sustainability strategies into enablers for growth.
Expert in carbon passporting, measuring and managing carbon across the full supply chain, Innes now works with businesses across all sectors to simplify, streamline and optimise their entire ESG reporting requirements.
You can follow Innes on LinkedIn here.
