ESG Reporting Mandates by Enhancing Cyber Posture

Cyber Strategies to Increase Compliance, Mitigate Risk and?Maximize Opportunity In recent years, environmental, social and corporate governance (ESG) has become a hot topic. It’s no longer “good to have” but a “must-have” requirement for many organizations, a considerable shift for companies that voluntarily reported ESG in the past but are now required to in many locales. Growing environmental concerns (e.g., climate change, access to clean water, waste pollutants in oceans, animal extinction, etc.), investor awareness and governmental environment policy commitments are significant drivers for this dynamic shift. Even market analysts are making ESG labelling routine for their ETF portfolios and using ESG as an effective risk management tool.

Companies are scored based on their impact on the environment, social trust with employees and clients and the governance structure and diversity within the company. In essence, performance on a balance sheet is not enough to succeed, and there are direct correlations between the per-share price and an ESG score. For example,

Data privacy is part of the ESG framework and directly falls under the “social” construct.

It's a top-of-mind topic for any organization worldwide, and it has become mainstream. This is especially true where media outlets have been found to have data breaches. Even top organizations are publishing details on how they actively shield the personal and private information of their consumers, including initiatives to drive literacy with their employees ?on the ethical usage of data.

As a result, reports previously created on a best-endeavors basis are now mandatory. And enterprises must demonstrate the same level of controls for ESG reporting that they deliver for traditional financial reporting—disclosing climate-related financial information and reporting their climate-related risks and opportunities. They also must evaluate climate-related risks within their overall risk management profile, add those risks to their strategic plan and pinpoint the potential financial impact of each risk.

Four Key Considerations for Meeting ESG Reporting Mandates

Around the world, new laws require both publicly traded and private organizations to abide by ESG reporting mandates (see Figure 1). Top examples of these rules include the United Kingdom’s Taskforce on Climate-related Financial Disclosures (TCFD) recommendations, the Sustainable Finance Disclosure Regulation (SFDR) in the European Union and the United States’ Securities and Exchange Commission ESG regulations.

Proven Processes Serve as a Foundation for ESG Reporting

?To comply with emerging ESG regulations, executives are looking to learn lessons from their company’s financial reporting efforts. Chief sustainability officers, chief data officers, chief risk officers and chief operating officers are building processes to establish a solid foundation for accurate, efficiently generated ESG reports. We recommend that decision-makers adopt the following six steps to enable ESG reporting.

The final step, preparing for ESG reporting and disclosures, requires a renewed focus on data. Most companies affected by new ESG mandates rely heavily on third-party data to support their operations. They may do business with thousands of suppliers, making it difficult to get real insight into their carbon footprint.

A Comprehensive ESG Strategy Starts with Data Management

Streamlining compliance with ESG mandates and taking advantage of related business opportunities requires a focus on the complete ESG reporting cycle (see Figure 3).

To execute each step in the ESG reporting cycle, enterprises must concentrate on the following five key data elements.

? 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.

? 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 the data as it flows across the organization. They also must demonstrate where the 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 ESG reporting mandates, 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.

“The data lineage [capability] helps [users] see where the data is, how it’s flowing and the quality end to end. It’s really powerful, helping the business find data quicker than ever before.”

Support ESG Compliance with AI-Powered, Cloud-Native Data Management

The need to comply with regulations related to the handling of data and for overarching data governance will continue to rise as more business entities begin to comply with ESG reporting mandates. The ability to disclose climate-related financial information requires near-real-time, easy access to trusted, relevant data, no matter where it resides—in local systems, hybrid clouds or multiple clouds — and no matter who needs to use it.