A Flexible Approach Towards Self-Adapting Process Recommendations

Abstract

A company's ability to flexibly adapt to changing business requirements is one key factor to remain competitive. The required flexibility in people driven processes is usually achieved through ad-hoc workflows which are naturally highly unstructured. Effective guidance in ad-hoc workflows therefore requires a simultaneous consideration of multiple goals: support of individual work habits, classification of unstructured messages, exploration of crowd process knowledge, and automatic adaptation to changes. This paper presents a flexible approach towards the mapping of unstructured messages onto processes as well as patterns for self-adjusting and context-sensitive process recommendations based on the analysis of user behavior, crowd processes, and continuous application of process detection. Specifically, we classify users as eagles (i.e., specialists) or flock. The approach is evaluated in the context of the European research project Commius.