How data management and advanced analytics drive ESG performance

Rodolphe Dehaspe

Manager, Sustainability Technology & Data, PwC Switzerland

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Başak Schaufelberger

Senior Consultant Technology & Data, PwC Switzerland

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Data plays a pivotal role in successfully establishing environmental, social and governance (ESG) processes. As businesses increasingly commit to sustainable practices, the need to monitor, measure and improve ESG outcomes has become essential. Effective ESG data management allows companies to collect and analyse extensive ESG-related information such as carbon emissions, energy consumption and workforce diversity. This not only involves collecting and processing data, but also analysing it and reporting on key environmental, social and governance metrics.

Discover the blog series

ESG data operating model

Align strategy with execution

Unified data models

Accelerating ESG reporting and keeping up with changing regulations

Main components of successful ESG data management

Challenges in ESG data management and analytics

Gathering accurate and comprehensive ESG data is challenging due to inconsistent data sources, formats, quality and collection processes across departments and regions.

Without clear roles and accountability, ESG initiatives become fragmented and inefficient. A well-defined operating model establishes clear responsibilities and streamlines decision-making, leading to more effective structures and impactful outcomes.

Many companies lack the personnel and technical expertise to manage ESG data effectively. This shortage can hinder the ability to gather, integrate and analyse data comprehensively.

Although new technologies like AI can significantly help companies to manage their ESG data, they must invest in infrastructure and staff training to effectively use these technologies. One key aspect of this investment is establishing a unified data model. By combining various data sources into a central location, companies can improve data accuracy, consistency, traceability, scalability, and real-time access. This centralized approach ensures that ESG initiatives are well-managed and future-proof.

Companies must adapt to regulations that are published and updated with increasing regularity and that also differ by region. Non-compliance can result in financial penalties, legal risks and reputational backlash.

Compared to existing financial reporting, ESG reporting disclosure requires collaboration and data collection across a greater number of departments. Finance has been streamlining the (financial) reporting processes with HR and IT for many years, but sustainability reporting requires additional departments, such as operations, procurement and legal, to be involved to a larger extent.

"One client told us that while it took them 18 days to close their financial reporting, it took 183 days to close the non-financial report. It’s clear that reducing this process by 160 days would deliver significant business value. That's where our support can make a significant difference."

Joscha Milinski,Partner Technology & Data, PwC Switzerland

While the next section of this article explains PwC’s ESG value cycle, our subsequent blog post Designing an ESG data operating model dives deeper into the organisational challenges and recommendations. Developing an ESG data operating model provides clarity, ensures robust data management practices, facilitates integration into business operations and enhances stakeholder engagement.

Following on from the operating model suggestions, our blog post Unified data models are key to accelerating ESG reporting and keeping up with changing regulations describes the challenges and opportunities of integrating technology. It focuses on the benefits of a unified data model for ESG reporting, which addresses multiple pain points simultaneously: it ensures data traceability, reporting consistency and seamless integration from various source systems.

While there are many challenges, the value to overcome them is clear

Overcoming the challenges outlined above delivers significant business value, structured around three key dimensions in PwC’s value cycle: comply, improve and benefit.

Proper ESG data management is the foundation for complying with sustainability reporting standards, which ensures regulatory compliance, increases investor confidence and helps attract investment.

For instance, in Germany, non-compliance can result in fines of up to EUR 500,000 or 2% of company turnover for businesses with annual revenues over EUR 400 million. Even though penalties are strict, many companies are still unprepared. The 2024 Global ESG Practitioner Survey found that 67% of respondents said they were concerned about their company’s ability to comply with new regulatory reporting requirements.

Beyond compliance, sustainability reporting standards improve data comparability and investor decision-making. According to the World Economic Forum’s IBC Measuring Stakeholder Capitalism Report (2020), 88% of investors agree that universal ESG metrics would enhance their investment decisions. The PwC Global Investor Survey (2023) revealed that 75% of investors consider companies’ management of sustainability-related risks as an important factor in investment decisions. Proper ESG data management improves investor confidence, helping companies attract investment.

The benefits of ESG reporting, alongside effective ESG data management, extend beyond boosting investor confidence – they also streamline the audit process. Efficient ESG data management minimises the challenges that companies encounter with both internal and external auditors, by ensuring that the data collection process is well-organised and ESG KPIs are consistently tracked and readily available.

Efficient ESG reporting processes save time and resources. Automating parts of the data collection process eases the burden on employees, reducing reporting time and freeing up resources for other activities. The 2024 Global ESG Practitioner Survey revealed that 83% of respondents found the collection of accurate ESG data to comply with directives to be a major organisational challenge. By implementing automation and improving efficiency, companies can enhance not only their reporting but also their overall operational performance. For example, at the Global Reporting meeting in Amsterdam in March 2024, one client told us that while it took them 18 days to close their financial reporting, it took 183 days to close the non-financial report. It’s clear that reducing this process by 160 days would deliver significant business value.

While efficient ESG reporting is critical, companies can generate even more value by going beyond regulatory reporting. ESG data can be analysed for broader operational benefits, such as improving supplier management, enhancing marketing strategies and optimising internal processes. Advanced technologies like AI and machine learning can provide deep insights into ESG data, uncovering patterns that were previously hidden.

The importance of emerging technologies in ESG is clear. According to the PwC Global Investor Survey (2023), 61% of investors believe that accelerated adoption of AI is critical. They also see technological advancements as the most likely factor to drive value creation over the next three years. Investors want to know how companies will deploy technologies to support sustainability and create long-term value.

Analysing ESG data plays a crucial role in understanding processes and increasing the frequency and accuracy of KPI results. While evaluating KPIs during reporting is essential, greater benefits can be realised by continuously tracking and improving them year on year. Through ongoing analysis and optimisation, businesses not only strengthen their operations but also improve the KPIs that are ultimately reflected in regulatory reports.

Conclusion

In conclusion, effective ESG data management and advanced analytics can drive compliance, enhance strategic decision-making and unlock new operational efficiencies. As regulations evolve and investor expectations rise, companies that embrace data management and advanced analytics will be better positioned to achieve strong ESG performance and create sustainable, long-term value. If you’re facing challenges with managing your ESG data, we’re here to help. Get in touch – we look forward to guiding you on your journey toward ESG reporting.

Contact us

Joscha Milinski

Partner and Data Strategy & Management Leader, PwC Switzerland

+41 58 792 23 58

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Rodolphe Dehaspe

Manager, Sustainability Technology & Data, Lausanne, PwC Switzerland

+41 76 268 94 00

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How data management and advanced analytics drive ESG performance

Discover the blog series

ESG data operating model

Unified data models

Main components of successful ESG data management

Challenges in ESG data management and analytics

While there are many challenges, the value to overcome them is clear

Conclusion

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