Data Analytics & Foresight
Data is the gold of the 21st century not only in industry, but also in the service sector and in trade. The ability to generate information and subsequently knowledge of action and decision-making from data and to systematically integrate it into company processes is becoming a key competence in ever more complex and volatile value creation networks. This systematic handling of data and its conscious use in the respective context is summarized under the term "data literacy". Data literacy encompasses the identification and processing of the relevant data in the respective area, the collection and aggregation of correct information, the (further) development and application of appropriate analysis methods and the contextualization that supports decision-making.
IIn the “Data Analytics and Foresight” competence field, those methods and approaches are researched on an application-oriented level that can be used to obtain data literacy in future retail. As part of the research projects, research is carried out on the operational and tactical level using methods of supervised learning (e.g. support vector machines) and unsupersvised learning (e.g. neural networks) to find out which patterns can be recognized in the data of complex value-added networks and how these can be used as the basis for predictive statements and recommendations for action can be prepared and implemented. On the other hand, corporate foresight methods (trend monitoring, weak signal analysis, bibliometrics) are used to research on a strategic level.