Service Analytics Research Group


Digitalisation, big data, and artificial intelligence are currently the buzz words of choice. We consider information systems for analysing, predicting, and planning complex service processes. Our goal is always to improve the interplay of humans and algorithms for better decision support. Especially in service operations, human actors play a leading role as customers, but also as participants in all aspects of value creation. Here, our research involves cooperation with industry partners in transport and online retailing. Via intelligent data analyses and simulation modelling, we can factor in human decision making when evaluating new planning approaches.

To that end, we implement and extend methods from all levels in the „pyramid of analytics“: Descriptive approaches to describe and analyse the status quo, predictive analytics to create quantitative forecasts, and prescriptive approaches for planning and for supporting future decision making.

Die Pyramide des Analytics