Apply core data quality dimensions, including completeness, accuracy, consistency and timeliness, to sustainability metrics before they reach a report.
Quality & Productivity
Data Quality Assurance Practices for ESG and Sustainability Reporting
Builds data lineage, controls and assurance-ready evidence for Scope 1-3 emissions and sustainability data under IFRS S1/S2, CSRD and ISAE 3000.
🗓️Duration5 training days
📚Content4 modules · 8 sessions
🎓On completionAccredited attendance certificate
About the programme
Course Overview
Sustainability disclosures are moving from voluntary narrative reports to assured, audit-grade data under frameworks such as IFRS S1/S2 and CSRD/ESRS, yet many organisations still collect emissions and social data through spreadsheets with no data lineage, no control ownership and no distinction between measured and estimated figures. This course applies established data quality practice to ESG and sustainability metrics: mapping data lineage from meter or invoice to final disclosure, classifying data as measured, calculated or estimated, and building the internal controls that a limited or reasonable assurance engagement under ISAE 3000 will test. Participants work through Scope 1, 2 and 3 data quality problems, including the particular challenge of collecting reliable supplier data, and practise preparing an assurance-ready data pack. The course also covers governance alignment with current disclosure standards and a documented approach to correcting errors and restating prior-period figures. Participants leave with a data lineage template, a data quality scorecard and a pre-assurance review checklist.
Expected Learning Outcomes
Map data lineage for Scope 1, 2 and 3 emissions data from source system to final disclosure.
Design data controls that distinguish measured, calculated and estimated ESG data and flag the difference in reporting.
Prepare an ESG data set for limited or reasonable assurance under ISAE 3000 or an equivalent assurance standard.
Build a supplier data collection process that improves the quality of Scope 3 data without unrealistic data demands.
Align internal ESG data governance with IFRS S1/S2 or CSRD/ESRS disclosure requirements.
Handle data errors and prior-period restatements through a documented correction and disclosure policy.
Who Should Attend
Sustainability reporting managers preparing disclosures under IFRS S1/S2 or CSRD.
Data governance and controllership teams extending existing frameworks to ESG metrics.
Internal auditors assigned to review sustainability data controls.
Finance teams supporting external assurance of sustainability reports.
Supply chain and procurement staff responsible for collecting supplier ESG data.
ESG and sustainability analysts consolidating multi-site emissions and social data.
Course Modules
Select any module to see its sessions and points.
01Data Quality Foundations for Sustainability Metrics
2 sessions · 8 points
Session 1Applying Core Data Quality Dimensions to ESG Data
- Define completeness, accuracy, consistency, timeliness and validity criteria specific to emissions and social data.
- Distinguish activity data errors, such as missing site meters, from emission factor errors in a root cause review.
- Set a materiality threshold for data quality issues that determines whether an error requires restatement.
- Build a data quality scorecard that tracks these dimensions across reporting periods rather than a one-off check.
Session 2Mapping Data Lineage from Source to Disclosure
- Trace Scope 1 fuel and Scope 2 energy data from meter or invoice through to the consolidated emissions figure.
- Document every calculation step, conversion factor and assumption applied between source data and final disclosure.
- Identify manual intervention points in the data flow where errors are most likely to be introduced.
- Build a lineage diagram that an external assurance provider can follow without additional explanation.
02Managing Measured, Calculated and Estimated Data
2 sessions · 8 points
Session 1Distinguishing Data Types and Their Quality Implications
- Classify each data point as directly measured, calculated from activity data, or estimated using proxy methods.
- Apply a hierarchy that prefers site-metered data over industry-average emission factors wherever feasible.
- Flag estimated data transparently in underlying working papers even where the final disclosure presents a single figure.
- Set a plan to progressively replace estimated data with measured data across future reporting cycles.
Session 2Building Supplier and Scope 3 Data Quality
- Design a supplier data request that balances data quality ambition against realistic supplier reporting capability.
- Validate supplier-submitted emissions data against sector benchmarks before it enters the consolidated inventory.
- Sequence a Scope 3 data quality improvement plan around the categories with the highest emissions and the weakest data.
- Document assumptions used for suppliers unable to provide primary data, consistent with the GHG Protocol hierarchy.
03Preparing Data for External Assurance
2 sessions · 8 points
Session 1Understanding Assurance Standards and Provider Expectations
- Compare the evidence requirements of limited versus reasonable assurance engagements under ISAE 3000 or ISO 14064-3.
- Prepare a data pack that links each disclosed figure to its underlying evidence and calculation methodology.
- Anticipate the sampling approach an assurance provider will take and prepare source documentation accordingly.
- Brief site-level data owners on the questions an assurance provider is likely to ask during fieldwork.
Session 2Internal Controls and Pre-Assurance Review
- Design internal control checkpoints, such as sign-off by site and consolidation-level review, before external assurance begins.
- Run a dry-run internal audit of the ESG data set using the same criteria an external assurer would apply.
- Reconcile sustainability data against financial and operational records to catch inconsistencies before assurance.
- Document management's basis for judgement on estimates and assumptions for the assurance provider's file.
04Governance, Restatement and Disclosure Alignment
2 sessions · 8 points
Session 1Aligning Data Governance with Current Disclosure Standards
- Map data governance requirements implied by IFRS S1/S2 and CSRD/ESRS against the organisation's current controls.
- Assign named data owners for each disclosure topic consistent with double materiality assessment outcomes.
- Build a disclosure checklist that links each required data point to its control owner and evidence location.
- Plan the data governance uplift needed to move from voluntary to mandatory assurance-ready reporting.
Session 2Handling Errors, Restatements and Continuous Improvement
- Design a documented policy for correcting prior-period ESG data errors and disclosing the restatement's impact.
- Distinguish errors requiring restatement from methodology changes requiring disclosure of a recalculated baseline.
- Run a lessons-learned review after each reporting cycle to close recurring data quality gaps before the next cycle.
- Report ESG data quality performance to an audit or sustainability committee alongside financial data quality metrics.
What the participant receives
4 course modules
A structured syllabus
8 training sessions
across 5 days
32 detailed points
Applied, detailed content
Accredited attendance certificate
On completing the programme
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