As global commerce expands, businesses must confront the grim realities of climate change. Consequently, regulatory authorities and investors have intensified their focus on climate resilience. In step with this changing environment, environmental, social, and governance (ESG) reporting obligations have also shifted from being voluntary to mandatory.
The Corporate Sustainability Reporting Directive (CSRD) requires large public-interest companies with more than 500 employees to disclose their ESG performance for financial years beginning in 2024. The CSRD aims to bring sustainability reporting closer to the level of rigour, auditability, and completeness that governs financial reporting. Jurisdictions are also introducing or aligning with sustainability disclosure standards, collectively raising the baseline for what regulators and investors expect to see and verify.
The ESG data challenge: The tip of the iceberg
Beneath ESG reporting lies substantial complexity: data collection, integration, curation, classification, consolidation, and governance across environmental, social, and governance dimensions.
Three data-related challenges recur across enterprises of every scale.
Origins of data
ESG data originates from procurement, HR, operations, supply chain, finance, and third-party platforms. These functions are rarely connected or standardised, and their data is rarely available in the format that reporting frameworks require.
Manual data collection
Manual data collection and reconciliation are prone to error, and errors in sustainability disclosures often carry significant regulatory and reputational risks.
Data interlinkages
Many organisations underestimate the strategic information already present in their existing systems, including purchasing records, supplier data, and employee master data. These data sources could support both CSRD compliance and internal decision-making if properly surfaced and connected.
CSRD and the new standard of reporting
CSRD intensifies the ESG data challenge by demanding auditability. The requirement is not only to report metrics but to demonstrate, with traceable evidence, how those metrics were calculated, where the underlying data originated, and whether it was reviewed against a quality standard. This shifts the technical requirement from report generation to data governance, which is a fundamentally different capability.
ESG data management software addresses this by replacing fragmented spreadsheet workflows with centralised platforms that automate data collection, enforce standardisation, track data lineage, and produce outputs aligned with GRI (Global Reporting Initiative), SASB (Sustainability Accounting Standards Board), ESRS (European Sustainability Reporting Standards), and other relevant frameworks.
Automated data quality validation reduces the risk of errors reaching a disclosure. Centralised data access means the sustainability function, finance team, and assurance providers work from the same source rather than reconciling between versions at quarter-end.
Analytics as the transformation tool
Using ESG data as a decision asset depends on what happens to the data after it has been validated and reported. Applying advanced analytics to ESG data converts compliance outputs into strategic inputs:
- Predictive analytics forecast the environmental impact of operational decisions.
- Performance tracking against internal targets and industry benchmarks creates a feedback mechanism that most sustainability strategies currently lack.
- Real-time monitoring of ESG metrics allows management to act on signals.
These analytical capabilities require the same data infrastructure that CSRD compliance demands. The investment in building a reliable, centralised, governed ESG data foundation, therefore, serves both purposes: it satisfies the disclosure obligation and creates the analytical layer that turns ESG data into a management tool.
The key value proposition
Three conditions distinguish organisations that have made this transition from those still managing ESG as a reporting task.
A unified ESG data foundation
ESG data that is centralised, standardised, and accessible across the sustainability, finance, and risk functions enables faster disclosure, more credible reporting, and richer analysis. Data that remains siloed in departmental spreadsheets serves only the minimum compliance function.
Analytics embedded in reporting workflows
When ESG data flows continuously into dashboards, performance metrics, and risk indicators instead of being confined to annual reports, leaders gain real-time visibility into sustainability performance and can make more informed decisions.
Governance aligned with regulatory evolution
CSRD (Corporate Sustainability Reporting Directive), ISSB (International Sustainability Standards Board), and related frameworks continue to evolve. An ESG data programme built around a single compliance objective will need constant reconstruction as requirements change. Governance frameworks that treat ESG data management as a continuous operational discipline can adapt without the disruption of periodic rebuilds.
How can Infosys BPM help with ESG reporting?
Infosys BPM enables enterprises to transform complex ESG disclosures into strategic value. Combining deep domain expertise with next-generation technology, we automate data extraction, lineage tracking, and framework-aligned ESG reporting across ESRS, ISSB, and GRI. Our metrics-driven approach and embedded analytics eliminate manual spreadsheet errors, ensure complete auditability, and deliver real-time insights for executive decision-making.
Frequently asked questions
It means that every disclosed figure can be traced to its source system, the calculation method is documented, and evidence exists for the controls applied to it. In practice, this requires data lineage, version history, and a defined review step—the same standard that financial reporting has followed for decades, applied to emissions, workforce, and supply-chain data.
Double materiality means assessing both how sustainability issues affect the business financially and how the business affects people and the environment. It matters operationally because it widens the data set: an organisation cannot scope its reporting from financial impact alone, and the assessment itself has to be documented and defensible.
Scope 3 value-chain data is often the hardest to collect. It sits with suppliers rather than within the enterprise, arrives in inconsistent formats or not at all, and often has to be estimated using published factors. Most organisations make the most progress by prioritising the suppliers that account for the bulk of their spend or emissions and improving that data first.
The source data usually already exists in ERP, HR, procurement, and facilities systems; the gap lies in aggregation, standardisation, and lineage rather than collection. Spreadsheets can produce a report, but they struggle to demonstrate how a number was derived. Dedicated tools justify their cost when assurance is required or when the same data must support several frameworks.
The same governed data set supports supplier risk assessment, energy and cost reduction, product footprinting, and capital-allocation decisions because it maps activity to consumption at a level that operational reporting rarely does. The practical step is to route ESG data into the dashboards that leaders already use rather than leaving it in the annual report.
