Just under a quarter of companies are planning to switch their ERP systems to SAP S/4HANA by 2023 - standardising processes and adapting the operational and organisational structure are the central objectives of the conversion.
These are some of the key findings of the “Digitalisation in Accounting” study, which we carried out for the fourth year in a row together with the Ludwig-Maximilians-University of Munich.
As in previous years, we looked at the status quo and development trends of digitalisation in accounting. In addition, this time there were questions about improvements in efficiency through the use of robotic process automation (RPA) and artificial intelligence (AI) in accounting, the status of SAP S/4HANA transformation projects and the degree of digitalisation of non-financial reporting.
In particular, the conversion to a powerful ERP system such as SAP S/4HANA is one of the most important digital transformation projects planned over the years to come. Real-time analyses are also possible with the latest ERP generation.
It is shown that so far only seven percent of the study participants have switched to SAP S/4HANA. 23 percent of the companies are currently planning to switch by 2023.
More than a quarter of the companies now use RPA in their accounting systems. The use of RPA solutions is particularly well suited to accounting because the processes are often standardised and recurring. The main advantages mentioned by the study participants are the time and cost savings and the improved quality. However, 45 per cent of companies do not see any long-term potential for RPAs.
The use of AI is still not relevant in most areas of accounting. According to the survey, this is due in particular to the heterogeneity of documents, outdated systems and data silos. AI is currently only used to capture standardised documents such as invoices or to process incoming payments.
In 20 percent of companies, operational processes are only (almost) fully automated. To date, the processes for non-financial reporting have been the least digitalised. The reason for this given by many of the study participants is that non-financial data lacks sufficient quality and standardisation compared with financial information.
The results will be discussed in depth in an interview with Prof. Dr Peter Fettke, German Research Centre for Artificial Intelligence (DFKI). We also present two case studies in the study: the use of deep learning technology at Hypatos and CO2 reporting in accounting at the Deutsche Post DHL Group.