Towards a situation-awareness-driven design of operational business intelligence & analytics systems

With the swamping and timeliness of data in the organizational context, the decision maker’s choice of an appropriate decision alternative in a given situation is defied. In particular, operational actors are facing the challenge to meet business-critical decisions in a short time and at high frequency. The construct of Situation Awareness (SA) has been established in cognitive psychology as a valid basis for understanding the behavior and decision making of human beings in complex and dynamic systems. SA gives decision makers the possibility to make informed, time-critical decisions and thereby improve the performance of the respective business process. This research paper leverages SA as starting point for a design science project for Operational Business Intelligence and Analytics systems and suggests a first version of design principles.

Design principles for an enterprise systems chartering method

Our research follows a design science approach to develop a method that supports the initialization of ES implementation projects – the chartering phase. This project phase is highly relevant for implementation success, but is understudied in IS research. In this paper, we derive design principles for a chartering method based on a systematic review of ES implementation literature and semi-structured expert interviews. Our analysis identifies differences in the importance of certain success factors depending on the system type. The proposed design principles are built on these factors and are linked to chartering key activities. We specifically consider system-type-specific chartering aspects for process-centric Business Intelligence & Analytics (BI&A) systems, which are an emerging class of systems at the intersection of BI&A and business process management. In summary, this paper proposes design principles for a chartering method – considering specifics of process-centric BI&A.

A support system for mentors of novice entrepreneurs

In this study we present online software to rapidly assess the impact of mentoring techniques on a novice entrepreneur. We have built a prototype that collects data from team members in less than five minutes and that automatically returns a diagnostic analysis to the mentor. Between 2012 and 2015 we have tested three versions of our prototype with longitudinal analyses of teams attending startup weekend competitions, to confirm that our prototype supports mentors with few and yet relevant information. The results of our studies open several avenues of research regarding rapid diagnostic of project teams, whereas, from a practical point of view, our prototype entirely done with Google Docs can be easily used by anyone interested in entrepreneurship education. Keywords: Entrepreneurship education, effectuation, mentoring, decision support, design science.