Effective ESG reporting hinges on an organization's ability to collect, analyze, and report complete and accurate data timely. To face this requirement, organizations must find ways to consume potentially vast amounts of data from various, often isolated systems and synthesize that data into a reportable metric. ESG data analytics provides deeper insights into the information your organization has collected and enables faster, more accurate ESG reporting. This article will explore how ESG data analytics facilitates collecting and analyzing information and how internal audit teams can use ESG data analytics to test the reported data's accuracy and completeness.
- Collecting ESG data
- Analyzing ESG data
- Confirming completeness and accuracy of ESG data reporting
- Supporting reliable ESG reporting
Collecting ESG data
Since ESG covers a variety of domains, identifying and accessing the underlying data will be a challenge for many organizations. As ESG reporting, disclosure standards, and regulations move toward requiring reasonable assurance, the need for complete, accurate, and reliable supporting data is becoming clearer. Data analytics tools help organizations gather and integrate data from disparate sources, such as internal systems, external suppliers, and various databases where sustainability-related data may be stored. For example, collecting ESG data to support greenhouse gas emission reduction claims requires aggregating information from multiple offices, factories, stores, vendor locations, or even employees’ homes, including actual measurements and estimates of CO2 emissions in metric tons. Collecting ESG data in a centralized data repository can streamline the reporting process and ensure all relevant data is considered. .