2013, Emmenegger, Sandro, Hinkelmann, Knut, Laurenzini, Emanuele, Thönssen, Barbara, Fred, Ana, Dietz, Jan L. G, Liu, Kecheng, Felipe, Joaquim

In the APPRIS project an Early-Warning-System (EWS) is developed applying semantic technologies, namely an enterprise ontology and an inference engine, for the assessment of procurement risks. Our approach allows for analyzing internal resources (e.g. ERP and CRM data) and external sources (e.g. entries in the Commercial Register and newspaper reports) to assess known risks, but also for identifying black swans, which hit enterprises with no warning but potentially large impact. For proof of concept we developed a prototype that allows for integrating data from various information sources, of various information types (structured and unstructured), and information quality (assured facts, news); automatic identification, validation and quantification of risks and aggregation of assessment results on several granularity levels. The motivating scenario is derived from three business project partners real requirements for an EWS.

2011-03-21T00:00:00Z, Brander, Simon, Hinkelmann, Knut, Martin, Andreas, Thönssen, Barbara

Organizational agility is a key challenge in today's business world. The Knowledge-Intensive Service Support approach tackles agility by combining process modeling and business rules. In the paper at hand, we present five approaches of process mining that could further increase the agility of processes by improving an existing process model.

2010-06-08T00:00:00Z, Hinkelmann, Knut, Merelli, Emanuela, Thönssen, Barbara

2010, Wolff, Daniela, Hinkelmann, Knut, Thönssen, Barbara, Vitvar, Tomas, Peristeras, Vassilios, Tarabanis, Konstantinos

2012-10-04T00:00:00Z, Thönssen, Barbara, Lutz, Jonas

2011, Brander, Simon, Hinkelmann, Knut, Hu, Bo, Martin, Andreas, Riss, Uwe, Thönssen, Barbara, Witschel, Hans Friedrich

The work presented in this paper explores the potential of leveraging the traces of informal work and collaboration in order to improve business processes over time. As process executions often differ from the original design due to individual preferences, skills or competencies and exceptions, we propose methods to analyse personal preferences of work, such as email communication and personal task execution in a task management application. Outcome of these methods is the detection of internal substructures (subtasks or branches) of activities on the one hand and the recommendation of resources to be used in activities on the other hand, leading to the improvement of business process models. Our first results show that even though human intervention is still required to operationalise these insights it is indeed possible to derive interesting and new insights about business processes from traces of informal work and infer suggestions for process model changes.

2010-01-04T00:00:00Z, Thönssen, Barbara, Hinkelmann, Knut, Wolff, Daniela

2012-10-04T00:00:00Z, Emmenegger, Sandro, Laurenzini, Emanuele, Thönssen, Barbara

2011, Thönssen, Barbara

2010-01-02T00:00:00Z, Thönssen, Barbara