Flexible Task Management Support for Knowledge-Intensive Processes

Knowledge-intensive processes (KiPs) are driven by knowledge workers utilizing their skills, experiences and expertise. As KiPs are emergent and unpredictable by nature, their operational support is challenging. For coordinating and synchronizing their work, usually, knowledge workers rely on simple task lists like to-do lists or checklists. Though these instruments are intuitive and prevalent, their current implementations tend to be ineffective and error-prone. Tasks are neither made explicit nor are they synchronized. In addition, no task lifecycle support is provided and media disruptions aggravate task management. As a consequence, the efforts knowledge workers spent in task management are not exploited for optimizing future KiPs. This work presents the proCollab approach, focusing on its stateful and customizable components of processes, task trees, and tasks. proCollab processes may constitute KiPs in the shape of projects and cases, while generic task trees and tasks support required digital task lists of any kind. To enable domain-specific task support, the proCollab state management allows to integrate domain-specific procedure models (e.g., Scrum) and to enrich proCollab components with customized states. Finally, this customizable task management support fosters knowledge workers' coordination, increases work awareness, reduces media disruptions, and enables the reuse of valuable coordination efforts and knowledge

Design and Implementation of a Dynamic Web-based User Interface for the proCollab System Supporting Knowledge-intensive Business Processes

Globalization and the change to post-industrial societies have led to an increased value of knowledge-intensive processes. Areas creating and utilizing new knowledge, such as research and development are of high importance for today’s companies. In these areas, knowledge workers drive the creation of value in knowledge-intensive processes. However, there is still no established process-based support due to the dynamic nature of these processes. The latter requires a high level of communication and cooperation between all involved workers. The proCollab research project, hosted at Ulm University, aims to holistically support knowledge workers and knowledge-intensive processes. The concept of proCollab relies on the lifecycle-based task management in the context of processes. In particular, knowledge workers may use digital task lists to synchronize and coordinate their work more effectively. To demonstrate the capabilities of proCollab, a sophisticated proof-of-concept prototype has been developed. This work presents the design and implementation of the dynamic, web-based user interface of the current version of the proCollab prototype

Supporting Task Constraints and Dependencies in Knowledge-intensive Processes

Knowledge-intensive processes are widely found in modern societies and important to many fields of work. Driven by knowledge gained only during their execution, this type of process brings along challenges like a gradually emerging structure, uncertainty and frequent changes. Through contribution and communication the knowledge workers involved in the process shape and improve it while advancing towards a common goal. One very important part of the knowledge are the dependencies that naturally exist between the tasks on which these workers perform. With the latter often being spatially divided, expressing the dependencies existing for their jobs is a determining factor for success. Relying on insufficient software systems or, even worse, on paperbased solutions for coordination proves to be error-prone and lacks reliance in practical scenarios. Adequate aid in form of information systems, specifically designed for knowledge-intensive processes and their accompanying challenges, and operated on by the knowledge workers themselves, is needed. The work on such systems is a still ongoing endeavor and in need of concepts and solutions. This work presents a concept for the support of constraints to express task dependencies in knowledge-intensive processes. With the focus on the unique challenges coming with the latter, the concept puts great emphasis on providing guidance instead of strict ruling, adaptability to frequent changes and usability in practical scenarios. A rule-based, declarative approach is laid out for applying the concept, designed to be ready for extension, to various systems alongside other, already existing functionality. Based on it, a catalog of constraints is given, with clear semantic meanings and effects, tailored towards the use in knowledge-intensive processes. A proof-of-concept prototype for it was implemented for the process-aware Support for Collaborative Knowledge Workers (proCollab) system, an example of an adequate and sophisticated solution