Design and Implementation of Task Management Lifecycle Concepts based on Process Mining

In a globalized world, knowledge work and especially Knowledge-intensive Business Processes (KiBPs) become increasingly important in highly developed countries. As a consequence, knowledge workers increasingly require an appropriate system support. Due to the more complex nature and the different characteristics of KiBPs, the Business Process Management (BPM) approach established to support traditional business processes, cannot be applied to KiBPs in the same way. As knowledge workers often rely on paper-based task lists (e.g. checklists, to-do lists) to collaboratively manage their work, a system supporting KiBPs should provide digital task lists based on a lifecycle to achieve a sustainable support.
This thesis discusses new concepts to enable an improved KiBP lifecycle support for task management through the application of process mining techniques. The KiBP lifecycle features the definition of so called collaboration templates, the instantiation of these templates to collaboration instances at run time and the evaluation of collaboration records. In particular, collaboration records are leveraged to automatically derive appropriate templates and to optimize existing templates.
In this context, an optimization approach for task list templates is proposed that incorporates the most frequently applied changes into the corresponding template using a change mining technique. Furthermore, an approach to automatically generate a task list template based on the records of comparable, completed task list instances through the application of a cluster mining algorithm is proposed as well. Additionally, the issue of providing knowledge workers with valuable task recommendations at run time is discussed and an approach addressing this problem is presented. Finally, selected excerpts of the implementation are presented to demonstrate the feasibility of the proposed approaches as a proof-of-concept prototype.