Part 2: How to Get Ready for the Next Wave of CSRD Reporting

See part 1 here

Undoubtedly, Environmental, Social and Governance (ESG) data management has become a critical aspect of reporting required by the Corporate Sustainability Reporting Directive (CSRD). Without it, collecting, integrating, and managing ESG data from various sources can be time-consuming, costly and prone to errors.

An ESG sustainability data management hub helps companies develop a centralized approach to manage their ESG data: a solution that can integrate ESG data from various sources such as carbon emissions data, ESG rating agency data and supply chain ratings data. Data governance and Data quality can then be applied to ensure the data is accurate and consistent.

Centralize ESG data as a strategic imperative

A centralized hub of data becomes the golden source of truth for all ESG data, with all the controls required by regulators, and enables a comprehensive strategy to address the following business imperatives:

• Comply with regulations. Satisfy industry regulations from the European Union (EU) Taxonomy, SFDR for financial services in the European Union, CSRD for all large publicly listed companies in the EU and TCFD for organizations across most G7 and G20. Allow compliance teams to leverage clean, valid and transparent data used in regulatory report submissions and respond quickly to regulatory requests.
• Power supply chain due diligence and the circular economy. Oversee the ESG performance of suppliers and take corrective action to improve sustainability practices. This entails ‘Scope 3’ carbon emissions in the supply chain, human rights conventions and companies’ environmental policies. It also supports the circular economy, finding opportunities to decarbonize a company’s supply chain across the four ‘Rs’ — reduce, reuse, recycle and remove — in areas such as waste management and end-of-life treatment of products.
• Integrate ESG data. Allows for the integration of ESG data into business decision-making processes across risks and opportunities and strategy and resource allocation.
• Measure ESG impact. Assess ESG performance and alignment to 17 sustainable development goals (SDGS) established by the United Nations.
• Set net-zero carbon emissions. Helps set science-based targets with the Science-Based Targets initiative (SBTi), measuring progress with clean trusted ESG data to achieve net-zero carbon emissions.

Five pillars of ‘audit ready’ data for CSRD compliance

Companies are expected to maintain ‘audit ready’ data for their CSRD Disclosures. This requires a set of controls that auditors and regulators will be looking for, necessitating a focus on the following five critical areas:

• Access and availability: Organizations must access data that originates from multiple sources, including databases, spreadsheets, logs, ‘Internet of Things’ sensors, machine data and business applications. Preparing this data for consumption requires ingesting it into a data warehouse, database or data lake.
• Quality and completeness: To ensure that data is fit for purpose, companies must manage data quality dimensions such as completeness, conformity, consistency, accuracy and integrity. Without proper attention to data quality, it can be difficult to easily process and analyze data, compromising its overall utility and the reliability of its results.
• Common reference data definitions: It’s important to identify the data definitions and business context associated with business terminology, taxonomies and relationships. Companies also need to define data policies, rules, standards, processes and measurements.
• Data lineage and transparency: To develop a better understanding of the data, enterprises need to clarify the availability, ownership, security and quality of data as it flows across the organization. They also must demonstrate where data originated, trace its journey through the systems in the organization and show how it changed along the way.
• Identification, classification and tracking of sensitive data: Companies need to embrace best practices for discovering, securing and managing sensitive data at every stage of its lifecycle. Protection can include data masking, encryption and tokenization. Data governance, policy management and monitoring can help secure sensitive data and let organizations know when to delete, archive and retire data.

Choose a solution with critical cloud data management capabilities

To address CSRD reporting, companies must deploy data management technology. When choosing a solution for ESG reporting, look for one that supports the following capabilities.

Data discovery: The solution should enable data discovery across all internal IT assets, including structured, semi-structured and unstructured data. Choose a technology with broad, complete metadata connectivity. By supporting various data file formats, legacy technologies and stored procedures in database applications, an enterprise data catalog solution helps you quickly build a data catalog and automate data lineage.

Data understanding: Data governance features help the business define critical data elements, creating a single definition across the business for key terms, such as “greenhouse gases.” Using artificial intelligence and machine learning, some tools can automatically link each business term to the underlying technical metadata. When the data is used in a field on a report, business users can easily drill down into the source of the data, providing complete traceability of the data.

Data trust: Data quality capabilities help build trust in the data, allowing data lineage information to be overlayed on the actual data, which can be useful in an audit. Advanced solutions use natural language processing, enabling business users to type in simple data quality rules without any programming experience. Rules are executed against all of the connected sources, delivering an immediate view of data quality. This self-service feature allows business users to address data quality issues at the source, propagating trusted data throughout the company’s systems.

Single view of data: Master data management features help create a single, 360-degree view of the data — for suppliers, products and customers, for example. The technology supports integration of data into data models for reporting, and users can feed the data into an ESG data lake or warehouse.

Data democratization: Leading solutions offer a self-service data marketplace that democratizes data, giving the business access to clean, trusted data. Users can then integrate ESG data into all operating model decisions, allowing the business to take strategic ESG actions and prove progress. They can also use the data marketplace to perform attestations for regulatory reporting.

Automated data consumption: Cloud-based data marketplace capabilities can help consumers shop for data and request data sets. This feature is especially helpful for companies that handle a high volume of ESG-related data requests because it automates the data consumption process.

A comprehensive ESG sustainability hub

The Informatica® Intelligent Data Management Cloud (IDMC) features AI-powered, cloud-native data management and governance that provide the capabilities and scalability needed to discover, cleanse, integrate, catalog, master, govern and protect the immense volume and variety of data involved in every aspect of ESG compliance (see Figure 1). Powered by more than 200 intelligent data services in a single platform, IDMC enables you to achieve the insights, agility and business outcomes that lead to success.

In summary

The implementation of an ESG sustainability data management hub is essential for companies to meet regulatory requirements, ensure supply chain sustainability, integrate ESG data into decision-making processes, measure ESG impact and work towards achieving net-zero carbon emissions.

Companies must focus on ensuring ‘audit ready’ data by addressing critical areas such as data access and data availability, data quality, data lineage and transparency, and sensitive data identification and tracking. These efforts are vital to meet the expectations of auditors and regulators for accurate and reliable data in compliance with CSRD.