ESG reporting – where does all the data come from?

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​​​​​​​published on 1 March 2024 I reading time approx. 2 minutes


No company would be ill-advised to concern itself with sustainability. However, the limit of 250 employees and/or more than EUR 50 million turnover and/or a balance sheet total of more than EUR 25 million apply to more companies than you might expect. This includes the larger medium-sized sanitary company just as well as a local retail chain or a larger franchisee of well-known catering brands. It is currently estimated that 50,000 companies in the EU and 15,000 companies in Germany alone will have to prepare reports in accordance with the Corporate Sustainability Reporting Directive (and therefore the ESRS standards). The introduction will be gradual and there will also be temporary simplifications. But what always remains is a huge challenge for management as well as for every employee, because data collection does not only take place in management offices, but rather in the factory halls and operational units.


Over 1,000 data points need to be collected, of which over 250 are at least voluntary. Most companies already realise that it is not enough to collect data anew every year and prepare it for the report, presumably with a considerable amount of manpower. Each data point requires documentation on how the data is collected - preferably automatically - where exactly it comes from, how it is verified and how this data is finally collated and prepared for the report. If the report is later audited, the auditor will look at whether the process was used appropriately and effectively for the audit period as part of an internal control system (ICS). In subsequent years, the auditor will also look to see whether the data collection method changes on an ongoing basis. This is because a process that is repeatedly carried out manually or in different ways can harbour a higher risk than a process that (automatically) taps data from a specific source.

It cannot be predicted exactly for any company, but it can be assumed that a good third – if not more – of the data comes from the existing ERP systems. This includes accounting as well as an HR management system or the systems in which wages and salaries are calculated. New data fields may need to be introduced for the data points in the transaction data or master data may need to be expanded. The more international a company is, the more complex the IT infrastructure is and the more complex the data collection processes become.


For example, if we want to calculate Scope 2 emissions - indirect emissions caused by the consumption of purchased energy such as electricity, heating or cooling, as well as the energy purchased for our own vehicle fleet - then it helps to look at the accounts. Energy suppliers such as local municipal utilities will invoice their services at some point. Either a CO2 value is already included in the invoice or certain conversion factors are used. If such invoices - whether for gas, electricity, oil or other energy sources - are recorded separately in corresponding accounts, they can be analysed and used quite quickly. Globally, a corresponding chart of accounts can be used and mapping to any necessary local charts of accounts and, of course, with the help of corresponding posting instructions, ensure that such transactions are recorded uniformly in all countries and units.

In the future, it would also be helpful with this type of data if CO2 values that are specified in invoices by the supplier are also entered in the ERP system at the same time as the invoice. Simply as an additional posting text. Or if CO2 values are not supplied - if the consumption values are then converted to CO2 values by recording the consumption value and a stored conversion table that is as globally standardised as possible. In any case, however, the auditor must also consider audit procedures for auditing the values specified by the supplier. In countries where electronic invoice formats have already been introduced or are in the process of being introduced, legislators would do well to include consumption values or even CO2 values directly in the mandatory information - at least for certain supplies and services such as energy sources.

Resources in accounting departments are scarce and it is important to prevent dedicated ESG managers and operational staff in accounting or the shared service centre from getting bogged down in searching for and tracking data, individual invoices, contact persons at suppliers and evaluating information. Even if it is extensive, the definition of the data points at least makes the procedure clear: the five steps must be carried out and documented for each data point: Data identification (where from?), data collection (how?), validation and verification, preparation and consolidation if necessary, followed by communication and reporting. Ideally, this should then be implemented in a standardised IT system for ESG reporting.

However, accounting is not the only important source of data; social standards are fed by HR systems and payroll systems. Most of the data points concern so-called narrative data types, such as descriptions and explanations, i.e. quasi policies, must be provided on certain topics. However, data that is stored in an HR system or payroll system and then read out may first have to be recorded there in a decentralised manner. Many clients use global HR systems, but often not in all countries. The number of training hours, data for a paygap analysis, etc. cannot be collected “at the push of a button”, but must be painstakingly collected from across systems every year. Here too, all data points should be analysed and planned once with regard to their origin and process. Often, simple interfaces with existing tools can be used to collect certain data fields, for instance from employee master data from different upstream systems, in one system or, if necessary, in an Excel file fully or semi-automatically.

This preparatory work must be done now! In the “List of ESRS Data Points”, there are a number of “quick wins” or “low hanging fruits” that can be used to minimise the initial shock of the large number of data points. Many large companies have already done this homework with their expanded ESG departments. However, the majority of new users still have some way to go.

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