The world of ESG analysis is rapidly evolving, and one of the driving forces behind this change is the rise of alternative data. Unlike traditional data sources, which primarily rely on company disclosures, alternative data encompasses a broader range of information sources.
What is Alternative Data?
In essence, alternative data refers to information that is outside of traditional sources. Instead of relying solely on a company's disclosed financial or earnings reports, alternative data might include insights from social media, web scraping, research reports, and other unique sources of data from reputable alternative data aggregators, such as ExtractAlpha.
The Impact of COVID-19 on Data Reliability
The year 2020, marked by the global pandemic, highlighted the limitations of traditional data sources. With markets experiencing unprecedented volatility, investors sought more timely and relevant data to make informed decisions. An excellent example of this was OpenTable's decision to publish daily data on restaurant bookings. This real-time insight provided a fresh perspective on consumer behavior during the pandemic, showcasing the power of alternative data.
Why Alternative Data Matters in ESG Analysis
Alternative data offers a more comprehensive view of a company's ESG performance. For instance, research reports can be analyzed to reveal sentiment of analysts, and social sentiment from platforms like Glassdoor can provide insights into a company's workplace culture and employee satisfaction. LinkedIn data can be used to monitor executive turnover, offering clues about a company's governance.
In a recent survey, 78% of investment funds expressed their intention to incorporate alternative data into their investment selection process. This growing trend underscores the increasing recognition of alternative data's value in ESG analysis.
Conclusion
As the ESG landscape continues to evolve, the integration of alternative data will play a pivotal role in providing investors with a more holistic view of a company's ESG performance. By leveraging these non-traditional data sources, investors can gain deeper insights and make more informed decisions.
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Why is ESG data expensive?
The costs of collecting, analyzing and storing data are not cheap. And unlike financial data, there is no standardized process for determining ESG scores.The complexity of ESG data and the lack of standardization in the process for assessing environmental, social and governance factors also makes it difficult to compare companies on these metrics. Regulators are trying to make ESG information more transparent by mandating that companies disclose them alongside their financials, but this is still materializing globally. Traditional providers such as MSCI or Refinitiv employ armies of analysts to get this data from corporate disclosures (if it exists) and then normalize that data and provide it back to you. This is a very expenive process, with lots of quality control, and importantly - because this data is not disclosed very frequently (companies typically disclose ESG related data annually), there is less incentive to have a continuous subscription to a ESG data feed, along with risk of information leakage. All of this results in very expensive, and limited annual contracts.
Artificial Intelligence is changing the way we create and consume ESG data, which address many of the issues above - but that is a topic for another day.
Why is ESG data expensive? 6
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What’s a Rich Text element? 5
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- The costs of collecting
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