In sustainability data, quality is critical
Environmental data is critical to our clients in many ways. Banks use the data to make lending decisions as part of their net-zero commitments. Investors use the data to evaluate investments and decarbonize their portfolios. Corporations report the data to their regulators and evaluate capital investments from an emissions impact perspective. For all these activities, the quality of the data is critical. At S&P Global Sustainable1, we want to advance this quality imperative. To this end, we’re putting our money where our mouth is and planting five trees for every qualifying and corrected error identified in our public company disclosure based environmental data.
We collect environmental data for more than 20,000 listed companies worldwide on a wide variety of measures, including greenhouse gas (GHG) emissions, air pollution, water use, waste disposal, and other land and water pollutants. This data can then be used to assess environmental costs, identify and manage environmental and climate risk, and to conduct peer and portfolio analysis from a climate and environmental perspective.
The data comes to us from many different sources — such as Sustainability or Corporate Social Responsibility (CSR) reports, company websites and public disclosures made to CDP. Adding a layer of complexity, this data can be reported in many different languages and formats. And as each data point is connected to a larger data universe, any error can have an impact on downstream calculations and derived metrics and reports.