Your ESG Data Is Scattered Across Six Teams.

The data for an ESG report sits across systems built for other jobs. One disclosure can pull energy consumption from operations, spend and supplier data from procurement, headcount and pay-gap figures from HR, revenue or CapEx denominators from finance, and product data from engineering.

Those teams built their systems to run their own functions, not feed a sustainability filing. Sorena AI ESG compliance treats collection as part of the core workflow.

EFRAG issued its final IG3 Detailed ESRS Datapoints implementation guidance on 31 May 2024. A 2026 study in Humanities and Social Sciences Communications, built on that dataset, says the complete list contains 1,184 quantitative and narrative indicators, then filters it to 297 quantitative indicators for its SDG mapping. Materiality and scope determine which datapoints a company reports, but the work can still involve hundreds of source, owner, definition, and evidence decisions.

Each value needs a definition, boundary, reporting period, and owner. Electricity consumption lives with facilities, workforce metrics with HR, and supplier locations and spend with procurement. Each also needs an evidence trail before it reaches the disclosure.

Finance, operations, HR, and procurement use different calendars, keys, and definitions. Each system can be internally correct while remaining incompatible with the others.

Building one emissions figure or workforce metric requires reconciling what each system means by a site, period, supplier, or business unit. Manual reconciliation is slow and error-prone, and it repeats each cycle. Sorena AI single source of truth gives each data point one owner, definition, and lineage.

Start with a collection matrix. For each metric, record the owner team, source system, reporting period, unit, definition, calculation method, evidence file, reviewer, and open data-quality issue. If EU Taxonomy reporting is in scope, add turnover, CapEx, and OpEx KPI inputs the same way.

Finance may own revenue denominators, Operations energy use, HR workforce metrics, Procurement supplier data, and Legal entity scope. The matrix gives those inputs a shared definition and evidence trail.

Under the CSRD, in-scope sustainability reporting is subject to assurance, beginning with limited assurance. A reviewer asks where a figure came from, who calculated it, which method was applied, and whether the source record still exists.

Every reported data point needs a trail back to its origin: the meter reading, invoice, payroll record, or emissions factor and its version. Manual collection across several teams can break that trail, leaving a figure the reviewer cannot test.

Manual collection repeats the same work each cycle. The same people chase data from the same teams, explain definitions, and reconcile mismatches. Little carries forward when the work lives in one person's inbox and one workbook.

Errors may surface only during assurance or a stakeholder challenge: inconsistent boundaries, periods that do not align, or estimates that nobody flagged. Scattered data increases rework and the risk of audit findings.

Give every ESG figure an owner, definition, and lineage in a governed store. Reuse that record across the disclosures that need it, and update the reporting view when the source changes. When an auditor asks where a figure came from, provide the documented trail.

A shared data layer reduces the spreadsheet reconciliation that teams repeat each reporting cycle.