Navigating the ESG Data Management Lifecycle

Environmental, social, and governance (ESG) factors have become increasingly important for investors as they seek to support companies that exhibit sustainable, responsible, and ethical activities. ESG investing requires buy-side firms to evaluate the ESG performance of companies, which means firms need to collect, analyze, and integrate ESG data into the investment decision-making process. This is where ESG data management comes in. In this article, we’ll explore the entire ESG data management lifecycle in buy-side firms.

Stage 1: Data Collection

The first stage of the ESG data management lifecycle is data collection. Buy-side firms need to gather ESG data from various sources such as company reports, regulatory filings, news articles, and third-party ESG data providers and store it in an ESG platform. The data should cover a wide range of ESG factors, such as climate change, human rights, labor practices, corporate governance, and supply chain management.

The sources of ESG data can be classified into two categories: internal and external. Internal sources refer to the ESG data that companies disclose directly in annual reports, sustainability reports, and other public disclosures. External sources refer to the ESG data generated by third-party ESG data providers, such as MSCI, Sustainalytics, and Bloomberg.

Stage 2: Data Validation

Once the ESG data has been collected, it needs to be validated and checked for accuracy and completeness. This involves identifying any missing data points, inconsistencies, or errors in the data and resolving them. For example, if a company reports its carbon emissions in metric tons, while others report it in kilograms, the data needs to be standardized to allow for meaningful comparison.

Stage 3: Data Normalization

After the ESG data has been validated, it needs to be normalized, or put into a standardized format, for easy analysis and comparison. This involves mapping ESG data to a common taxonomy and applying normalization rules to ensure consistency across various companies and industries.

For example, the Global Reporting Initiative (GRI) provides a common framework for companies to report sustainability performance. By mapping ESG data to the GRI framework, buy-side firms can compare the sustainability of different companies using a common language and set of metrics.

Stage 4: Data Analysis

Normalized ESG data is then analyzed to identify ESG risks and ESG investing opportunities associated with various companies and industries. This stage involves using a range of analytical tools and techniques to derive insights from ESG data.

For example, a buy-side firm may use a carbon footprinting tool to analyze the carbon emissions of all the companies in its portfolio. The tool may identify companies that have high carbon emissions relative to their peers, which may indicate a risk of carbon pricing regulations or reputational damage.

Stage 5: Integration

The ESG data and insights derived from the analysis are then integrated into the investment decision-making process. This involves incorporating the ESG factors into the investment criteria and evaluating companies based on their ESG performance.

For example, a buy-side firm with ESG investing goals may decide to exclude companies that have a poor track record on human rights or environmental issues from its investment universe. Alternatively, it may decide to engage with companies to improve their ESG performance and create value for shareholders.

Stage 6: Reporting

The final stage of the ESG data management lifecycle is reporting. Buy-side firms need to report on the ESG data and insights to clients, regulators, and investors. This involves preparing ESG investing reports, disclosures, and other forms of communication to provide transparency and accountability on the ESG performance of the firms and their investments.

For example, a buy-side firm may produce an ESG report that outlines its ESG investing approach, the ESG performance of its portfolio, and its engagement activities with companies. The report may also include case studies and examples of how the firm has integrated ESG factors into its investment decision-making process and created value for its clients.

Why ESG data management is important

ESG data management is an essential process for evaluating the sustainability and ethical performance of companies consistently and accurately. The ESG data management lifecycle involves several stages, including data collection, validation, normalization, analysis, integration, and reporting. With an ESG platform that supports this lifecycle, buy-side firms can gather reliable and standardized ESG data, analyze it to identify risks and opportunities and integrate it into the investment decision-making process to create value for clients and stakeholders.

ESG data management also has broader implications for the broader investment industry. As more investors pursue ESG investing and incorporate ESG factors into their investment decisions, companies will come under increasing pressure to improve ESG performance and disclose more ESG data. This will create a virtuous cycle of transparency, accountability, and value creation that benefits investors, companies, and society as a whole.

How IVP can help

IVP ESG Management is an ESG platform designed to help funds source, manage, and use ESG data effectively for ESG investing and reporting. IVP also offers an ESG Center of Excellence to help funds establish a reliable framework for ESG investing that enables more efficient portfolio construction, asset allocation, risk management and compliance, and regulatory reporting.

 

Learn more about the IVP ESG Management platform right now or contact sales@ivp.in.