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Product and Topic Expert
Product and Topic Expert

ESG Data Foundation

The ESG Data Foundation is a flexible data persistence that allows upload, validation and publication of ESG-relevant data for reporting purposes. The Data Foundation consists of pre-defined Data Provider Interfaces, pre-defined metrics and applications to manage the same. The pre-provided metrics adhere to regulatory standards, predominantly from GRI-based metrics, CSRD (ESRS Standard) and EU-Taxonomy. Other standards may also be applicable and will be mapped going forward.  


Data Provider Interfaces and Metrics

As ESG reporting is often defined based on regulatory standards, we need to have a way to bring data into the system in a structured way. Data Provider Interfaces (DPI) are the answer to this, as they provide an entry point for various ESG domains.

  • General Measures
  • Accounting
  • Corruption Incidents
  • Emissions
  • Energy
  • Injury
  • Land Site
  • People
  • Resource Use
  • Waste
  • Water Consumption and Water Withdrawal

 You can read about the semantic of these interfaces in our online documentation. They all have in common the relevancy for Environment, Social and Governance aspects in corporations. 

A single DPI is semantically structured into three areas:



  • Common Dimensions: These are data fields, that accommodate the organizational hierarchy, time relevance and data origin.
  • Measures: There are typically three data fields for a measure. ID_MEASURE, MEASURE_VALUE and MEASURE_UNIT. These fields allow to submit data for the DPI that have different semantic but belong to the same data domain.
  • Specific Dimensions: Allow to accompany the measure data with relevant attributes that can be used for metric calculation, grouping, filtering or other analytical purposes.  The dimensions are defined specifically for each Data Provider Interface.

 In the illustration below you can see the People DPI with its Common Dimensions, Measures and Specific Dimensions.


Each DPI has a set of measures that are outlined in the picture below. The list of DPIs below and its contained measures is continuously extended while we adopt further regulatory standards. The list below is as of Dec. 2023 and may get enhanced.  


Below is a screenshot of the "Manage Measures" app in SCT that is filtered for the People DPI. The list shows all SAP-provided measures, the metrics in which the measure is used and their current data population state. 



As a next iteration one or more DPIs can be used to calculate a metric. The metric is typically the relevant data point for a regulatory standards to be reported on. 

Example: Gross GHG Emissions Scope 1. The metric uses the measure “CO2E Emissions (ID EMS_QUANTITY_CO2E)” in DPI “Emissions”.


You can inform yourself about the metric in the “Manage Metrics” App that you can find in SCT.


The list of metrics in SCT (as of December 2023) is shown above, combined with the mapping to the respective measure. SAP ships more than 50 pre-defined metrics that can be supplied manually or via pre-defined system integrations with data. One can see that a metric can be build with one or more measures along the standard definition where it originates from. In SAP SCT the manage metric app shows the information in the screen below.


The metric meta-data provides information about which dimensions have been used, the calculation method and unit of measure combined with a textual description. In addition, the metric is technically defined in the online documentation (example: Gross GHG Emissions – Scope 1).

We plan to continuously enhance the meta data of the metric catalog to cater in a better way for auditability purposes in the system (e.g. standard relevancy, calculation formula, etc.). 


The ESG Data Foundation in SAP Sustainability Control Tower is a pre-defined data model, that adheres to supported regulatory standards, provides well-defined data import interfaces and is the basis for the metrics that are both pre-provided or custom-build in the system.

In part 2 of this blog series, we will explain how the ESG Data Foundation can be extended through customers and partners with measures and custom dimensions to cater for additional ESG relevant data objects.