In the digital cosmos, control systems require a high degree of automation for company management, which allows the business level to really focus on the important questions of the business and to create transparency about the performance of the company. To achieve this, companies must open up to the application of new technological possibilities such as data lakes, machine learning (ML) and artificial intelligence (AI), and integrate these into their control systems. This results in digital analytical assistants that can actively inform you about changes or irregularities in company data via KPI dashboards that can be personalised. With the help of real-time data, it is possible to react more quickly to problems, and the support provided by ML and AI makes it possible for systems to search the data for answers to specific questions or to compile entire dossiers on a topic and ultimately even identify patterns that can be converted into recommendations for action.
Digital analytical assistants thus provide management with an overview that is based exclusively on the relevant data. Where, in the past, standardised analyses were displayed that were not prepared for structural changes, nowadays algorithms should be used that detect and evaluate changes and irregularities in the data in real time.