Why ESG Data Strategy Is a C-Suite Priority in 2025

ESG and Data: From Separate Efforts to Unified Strategy

For manufacturing executives, the twin imperatives of driving profitability and achieving true sustainability have converged. Delivering on Environmental, Social, and Governance (ESG) promises is no longer optional, and neither is improving data strategy. 

In the past, ESG and enterprise data governance were treated as distinct initiatives. But regulatory, investor, and customer demands have changed that. The C-suite is now uniting ESG goals with digital infrastructure to create more accountable, efficient, and resilient operations.

Why is this convergence happening? Because data lies at the heart of both compliance and competitive advantage. Manufacturing leaders understand that ESG cannot be tracked or verified without high-quality data. Similarly, operational transformation cannot succeed unless it incorporates sustainability metrics. This makes ESG and data governance two sides of the same coin, a reality that is now driving boardroom conversations across the sector.

Regulations Demand Data-Driven ESG Accountability 

One of the biggest drivers of this alignment is regulatory change. In the European Union, the Corporate Sustainability Reporting Directive (CSRD) is bringing ESG accountability to the forefront. Over 50,000 EU-based companies and thousands of non-EU firms must provide auditable data covering their entire value chain. That means energy use, emissions, labor practices, and other ESG metrics must be measured and reported consistently across all sites and suppliers.

Meeting these requirements with siloed systems is nearly impossible. Manufacturers with disconnected spreadsheets, manual tracking, or department-specific software cannot deliver the traceability or consistency regulators demand. To comply, they must build integrated data environments where ESG data is treated like financial data: validated, standardized, and ready for audit.

Cybersecurity mandates like the EU’s NIS2 Directive are also contributing to this shift. With expanded scope to cover much of the manufacturing sector, NIS2 compels organizations to bolster cyber resilience. That means better governance of security data, tighter controls across IT and OT environments, and faster incident reporting. Together, CSRD and NIS2 illustrate a broader trend: regulators want companies to prove they are managing ESG and cyber risks, and the only way to do that is through trusted, centralized data systems.

Explore how manufacturers are embedding ESG data governance and mitigating reputational risk at the ‘Embedding ESG Data Culture Across the Business’ panel at 2:20 PM at the Manufacturing Data Summit Europe 2025 in London, on October 14.

Earning Trust: Investors and Customers Demand Data-Backed ESG Proof

Pressure is not just coming from governments. Investors are increasingly focused on ESG performance as a factor in portfolio decisions. However, they are growing skeptical of vague sustainability claims. A recent survey found that 94 percent of investors believe corporate ESG disclosures contain unsupported claims, and only one-third rate ESG data quality as good.

For manufacturers, this credibility gap affects more than public image. It can impact market valuation, investor confidence, and access to capital. Companies that cannot back up their ESG statements with solid data risk being labeled as greenwashing, which can damage trust and investor relationships.

Customers are another powerful force. Whether business buyers or end consumers, today’s customers want transparency. Most consumers say they would stop buying from a company that falls short on environmental or social responsibility. On the B2B side, procurement teams now require suppliers to submit ESG data, including emissions reports or labor practices, as part of contract negotiations. To stay competitive, manufacturers need integrated ESG data systems that deliver credible, real-time information across all business units and locations.

The Pitfalls of Fragmented ESG Data

Despite growing urgency, many manufacturers still manage ESG data in silos. One team might track emissions with one tool, while another tracks supplier compliance or diversity metrics with separate spreadsheets. This fragmented approach leads to duplicate work, inconsistent data, and limited insights. When every department uses a different format or definition, it is difficult to assemble a reliable ESG performance report, let alone use that data to make strategic decisions.

In global organizations, the problem multiplies. Each site or region might have its own way of measuring waste, energy use, or labor incidents. When data is not harmonized, ESG reporting becomes a manual, error-prone task. That puts manufacturers at risk of failing audits, losing investor trust, or facing compliance penalties.

It also creates blind spots. Leaders cannot spot risks or opportunities if the data is scattered. Whether it is identifying high-emission sites, tracing supply chain violations, or benchmarking social impact programs, the ability to act depends on having a unified view of ESG performance. Without it, even the best-intentioned ESG strategies fall flat.

See how manufacturers are using metrics and intelligence to deliver credible, investor-grade ESG performance at the 2:00 PM keynote on sustainability at Manufacturing Data Summit Europe.

Unlocking Value: Building a Unified ESG and Data Framework

Manufacturers that succeed in aligning ESG and data strategy unlock a range of benefits. First, they gain operational visibility. When sustainability metrics are integrated with ERP, MES, or data lakes, executives can track everything from energy use per unit produced to supply chain ethics in real time. That makes ESG performance more than a compliance checkbox, it becomes a strategic management tool.

Second, it strengthens resilience. A unified data platform enables faster response to changing regulations, better risk detection, and more agile crisis management. If a supplier is flagged for labor violations or emissions regulations change, a connected system allows for quick action and mitigation. This kind of agility is only possible when data is centralized, verified, and accessible.

Third, it enhances credibility. Reliable ESG reporting, backed by auditable data, builds trust with stakeholders. Investors are more likely to fund companies with solid ESG metrics. Customers are more loyal to brands they see as responsible. Regulators are more cooperative when disclosures are accurate and on time. A robust data strategy turns ESG into a value creator.

Achieving this unified framework isn’t just about policy; it’s crucially enabled by smart application of digital tools.

Are you interested in learning how to operationalize your data and drive ESG-aligned value? Join the Manufacturing Data Summit’s 12:15 PM panel on ‘Making Data Work’.

How Technology Supports ESG-Data Integration

Digital tools are making ESG-data integration more scalable and efficient. Artificial intelligence and automation can handle large-scale data collection from sensors, utility systems, and supplier databases. For example, smart systems can automatically parse utility bills across dozens of plants and feed the data into dashboards, reducing manual labor and error rates.

Advanced analytics can identify trends, predict future performance, and support scenario planning. For instance, manufacturers can simulate the impact of a new production method on carbon output or model different sourcing strategies based on supplier ESG scores. Some are also exploring blockchain to improve transparency and traceability across supply chains.

These technologies must be embedded into a broader data architecture that spans finance, operations, and sustainability functions. Many firms are extending their existing ERP platforms to include ESG modules or building APIs that connect ESG tools to centralized data lakes. The key is to avoid point solutions and aim for a seamless ecosystem.

Real-World Example: Unilever and EnerSys

Global manufacturers are already demonstrating what a unified ESG-data strategy looks like in practice. Unilever, for example, built a centralized ESG data platform that consolidates sustainability metrics across its global operations. The system integrates with financial and operational data and uses AI to flag anomalies. This has improved reporting accuracy, streamlined compliance, and provided leadership with a consistent view of ESG performance.

Similarly, EnerSys, a battery manufacturer, faced challenges in collecting emissions data across more than 180 global sites. By implementing an AI-driven platform, the company automated data extraction from utility documents, drastically improving efficiency and accuracy in Scope 1 and 2 emissions tracking. This innovation allowed EnerSys to meet regulatory deadlines and focus more on analysis and improvement rather than data collection.

A New Imperative for the C-Suite

The convergence of ESG and data strategy is no longer a future goal, it is an urgent priority for manufacturing leaders today. Whether to comply with regulations, build investor trust, meet customer demands, or gain operational insights, the ability to collect and manage ESG data effectively is now a core business capability.

As the industry evolves, manufacturers who treat ESG data with the same rigor as financial data will stand out. Those who delay may struggle to meet expectations or fall behind competitors with more integrated systems.

This October, join Europe’s most forward-thinking C-suite leaders at the Manufacturing Data Summit 2025. This is your unparalleled opportunity to connect with peers, learn from real-world case studies, and acquire the precise tools you need to align sustainability with digital transformation, transforming ESG from a compliance burden into a core driver of competitive advantage. Join us at the Manufacturing Data Summit 2025 in London on October 14.

This is your opportunity to connect with peers, learn from real-world case studies, and build the tools you need to align sustainability with digital transformation.