Data: the driving force behind tax management of the future

The fact that data in the tax department is the basis for the correct tax determination, analysis, and correction is nothing new. However, as digitalisation increases, within both companies and financial authorities worldwide, the demands on and handling of “raw material” data are changing, as well as the possibilities of what can be done with the “right” data.

In the course of digitalisation, automation and the like, tax management is also developing. Traditionally data recipients of data typically aggregated from a wide range of departments in a company, more and more tax managers are striving to participate much more in the data and process management of their company. This trend is also further strengthened by the increasing need for access to data sources. This goes hand in hand with the direct connection or integration into the relevant systems and processes. Only in this way can the requirements of the tax authorities also be fulfilled in a compliant manner in the future, because the demands on data transmission, e. g. in the case of electronic submission obligations, are growing, with increasingly shorter deadlines and higher quality expectations. On top of that, it is also easier to achieve one’s own efficiency goals and information needs.

Data originates and exists everywhere in a company, in different formats, and in different locations. However, there is often a lack of transparency and structure, understanding of the contexts or the technical implementation of interfaces, for example. The most important task when handling data is to unlock it and make it easy to use and visualise for various purposes. This is especially true for companies operating internationally and complex groups of companies, because ideally, data from subsidiaries or branch offices should also be centrally available. Companies should therefore consider which data can be made available in which form and via which processes in central instances, for example so-called data warehouses or data lakes. For this purpose, in many cases, the system-side connection, specific adaptation and structuring of the original data or the selection of the methodology in the case of unstructured data sources is required in advance. The initial effort and practical issues are a real challenge for most companies.

To really get data “under control”, it’s best to develop a data strategy. This basically serves to achieve long-term goals and ensures the selection of suitable measures and methods for the company-specific use of existing data. Data strategies are usually dependent on company-specific factors such as the data and system landscape or the economic situation and are therefore quite different in most cases.

Strategy development starts with the definition of goals, e. g. with regard to data/process transparency, key reporting areas, controls, automation requirements, and much more.

The actual situation is then analysed based on the objectives. The actual state, i.e. the data landscape of a company, is characterised by various aspects. This includes the type of business, the number of lines of business, the type of products, and the international presence. If a company wants to use its data strategically, this requires a deep understanding of the company processes, the different data sources and structures.

To this end, we recommend answering the following basic questions for comprehension:

• What is the ERP landscape?
• Are there already central data structures?
• How are data and systems accessed?
• What technology solutions are used?
• How is the tax department currently involved and connected?

After defining the objectives and analysing the actual situation, the appropriate measures are selected to achieve the defined objectives.

In addition to these basic procedures, one topic in particular requires special attention: When designing the future data landscape, not only the technical environment is relevant, but also the data design itself. The goal is to transfer data from a variety of sources and structures into a unified data model (common data model or tax data assets). As a result, the raw data from the different source systems is converted into a form that allows the user to process such data easily and use it for automation.

If you want to bring transparency and structure to your tax-relevant data, we would be happy to support you with our professionally and technologically experienced team. We help you define your tax-relevant data, develop a data strategy tailored to your individual situation, including appropriate technological solutions, and provide you with the transparency and data availability you need.

Contact us - we look forward to a no-obligation initial meeting.