Enhancing ESG Reporting with Cloud-Based data Platforms

Environmental, Social and Governance (ESG) metrics reflect an organization’s commitment to sustainability, and discerning investors demand transparency. Asset managers and CFOs have a duty to deliver the effective ESG reporting that shareholders seek, but data quality and management issues make this a highly complex challenge for many.

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The accessibility and traceability of your information is crucial to data quality, which robust reporting and governance rely upon. But not only will your data quality dictate the effectiveness of your ESG reporting, it will decide the success and consistency of your sustainability strategy overall.
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Cloud-based data platforms present a significant opportunity to transform the state of your underlying data infrastructure, simultaneously enhancing scalability, flexibility, and security. The right data platform will enable real-time data processing and dynamic resource management - without heavy upfront investments or physical infrastructure.

In this article, we offer insights on overcoming data challenges associated with ESG metrics, how to scale data platforms and reporting, and what it takes to achieve advanced data management.

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Overcoming the Challenges

Treat ESG metrics like data processing products. For this to be achieved, a consistent approach must be taken to the lifecycles of ESG metrics, including data gathering, aggregation, calculation, storage, and distribution. Without effective streamlining, each phase in the process presents a data quality risk that could result in unreliable ESG reports and diminished stakeholder trust.

Cloud-based data platforms enhance the entire data process end-to-end. They automate the collection of data from various sources, including internal systems or external databases, before cleansing and enhancing it to increase accuracy. During aggregation and calculation, these platforms use built-in tools to integrate and process the data, generating insights with AI models and formulas.

The lineage of your data is also governed meticulously when using a cloud platform, by tracking and recording every instance of modification and access to create a detailed audit trail. A prime example is the implementation of metadata management tools, which log data origins and history to ensure that ESG reports are both verifiable and compliant.

Cloud platforms create a single source of ESG data truth and maintain consistency by standardizing the architecture, whether through centralized data storage or a distributed data mesh. This means all stakeholders will be basing their strategies on the same precise information, while also streamlining internal operations.

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How to Drive Business-Wide Impact at Scale

There are several important architectural and vendor-specific factors to consider when scaling sustainability reporting across business units. Creating a holistic, consolidated view of ESG metrics across product lines and geographic locations forms a foundation for consistency.

The architecture of the cloud-based data platform you use is the first consideration, and it must support multi-tenancy effectively. With this capability in place, each business unit can be equipped with a tailored environment, promoting independence and security while contributing to business-wide sustainability goals.

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In addition to a platform’s support for multi-tenancy, its level of scalability is another critical factor. Providers like AWS, Google Cloud, and Microsoft Azure provide complete tech stacks that offer the agility to process data in real-time. This agility also allows a cloud-based platform to adapt alongside the evolving regulatory landscape.

When it comes to selecting the right vendor to support your cloud platform journey, there are some questions to prioritize. Which provider offers the greatest ease of integration with existing systems? How readily available are specialized data governance tools? How sophisticated are the overall security features? Is the solution cost-effective?

Industries with specific data processing needs, such as manufacturing or healthcare, may require bespoke cloud solutions created with their specific regulatory and operational needs in mind. SAP would be particularly beneficial in an instance like this, due to its industry-specific solutions and strong data management capabilities.

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Advanced Emissions Tracking in Action

In a case involving a leading asset management firm, the client needed to aggregate data of varying quality from multiple sources to achieve comprehensive carbon emissions tracking. The firm leveraged a cloud-based data platform to aggregate carbon emissions from assets under management in different business units (from public to private market).

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With the platform in place, the team was able to easily replace old data points with new, high-quality information from alternative/strategic sources. This facilitated more detailed, up-to-date reporting, while also making it possible to trace all data modifications and demonstrate accountability. In just six months, the platform had been seamlessly integrated and 90% of the organization’s assets were being tracked.

This case exemplifies how cloud-based data platforms with automated data management features can significantly enhance the efficiency and reliability of ESG data operations. The overwriting, historization, and ingestion capabilities meant that the asset manager both streamlined its portfolio emissions tracking and established an effective framework for future reporting.

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Confidentiality and Compliance

The confidentiality of proprietary data, especially in private markets, is of paramount importance. Because of this, data platforms must include advanced security features like low-level access control, enabling the user to meet stringent privacy requirements. Features like these ensure that sensitive data is accessible only to authorized users, maintaining confidentiality.

Data platforms facilitate compliance with various regulatory requirements by making sure that both the data and models used for ESG reporting are versioned together. Versioning is crucial for auditability, as it allows organizations to demonstrate the accuracy and legitimacy of their reported data at any point in time.