Utilizing Data Analytics to Support Process Implementation in Knowledge-intensive Domains

摘要

In recent times, knowledge-intensive activities and processes have become more and more important in various areas like new product development or scientific projects. Such processes are hard to plan and control because of their high complexity, dynamicity, and human involvement. This imposes numerous threats to successful and timely project execution and completion. In this paper, we propose an approach to support such processes and projects holistically. The basic idea is to utilize various kinds of data analytics on different data sets, reports, and events occurring in a project. This data can be used to fill the gap between the abstract process planning and its dynamic operational enactment. That way, processes can be technically implemented and supported in complicated knowledge-intensive domains and also adapted to changing situations.