A Flexible Approach Towards Self-Adapting Process Recommendations
A companys 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.