Due to the immense growth of collected data and advancing big data technologies, there are countless potential use cases of data and analytics. But most data initiatives fail and do not bring the desired outcome. One essential reason for this situation is the lack of a systematic approach to evaluate and select promising analytics use cases. This study presents an evaluation framework that enables the systematic screening at an early stage by assessing nine criteria with the help of a scoring model. It also supports a prioritization among several use cases and facilitates the communication to decision makers. The action design research approach was followed to build, test, and evaluate the framework in three iterative design cycles. It was developed in close collaboration with Bundesdruckerei GmbH, an IT-security company owned by the German government that offers products and services for secure identities, data, and infrastructures
