Towards a Real-time Usability Improvement Framework based on Process Mining and Big Data for Business Information Systems

Sharam Dadashnia; Tim Niesen; Peter Fettke; Peter Loos

In: Tagungsband Multikonferenz Wirtschaftsinformatik. Multikonferenz Wirtschaftsinformatik (MKWI-16), March 9-11, Ilmenau, Germany, Technische Universität Ilmenau, 2016.


Workflow improvement nowadays plays an important role in the selection process of supporting software. This is especially true in the context of user-centric development, where the usability of business information systems is a crucial characteristic of differentiation. However, automatically measuring the usability of such systems as well as their dynamic enhancement has not been stud-ied before. This paper describes an approach to improve the usability of web-based information systems in real-time. Different concepts are presented, which build on data gathering methods from web analytics to provide log mechanisms for user interactions at a detailed level and subsequently process this data by means of data analytics and process mining methods. Concepts are then integrated into a comprehensive framework representing the main contribution of this paper. We evaluate our framework with a software prototype based on in-memory technologies developed in cooperation with a major German software company. Furthermore, we report on findings of a user study that was conducted in an exemplary use case scenario demonstrating dynamic workflow improvements to validate our research in a real-world setting.

Dadashnia_et_al._-_Towards_a_Real-time_Usability_Improvement_Framework_based_on_Process_Mining_and_Big_Data_for_Business_Information_Systems.pdf (pdf, 497 KB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence