Tom Thaler, Sabine Norek, Vittorio De Angelis, Dirk Maurer, Peter Fettke, Peter Loos
Situation faced: The quality of the technical support of business processes plays an important role in the selection of corresponding software products. Against that background, software producers invest considerable capital and manpower in improving their business software’s usability with regard to customers’ needs and process-related requirements. However, existing approaches fromthe field of usability engineering generally require laboratory environments, which do not cover the real user behavior without limitations. Therefore, the case described here seeks to improve a user-centric UX approach based on the idea of automatic identification of real customer needs.
Action taken: For that purpose, the German Research Center for Artificial Intelligence (DFKI) and Software AG analyzed the issues in the currently available UX process at Software AG. Research and practice were searched for additional approaches to the critical point of understanding the user. Finally, a four-step approach based on process mining, consisting of user monitoring, trace clustering, usage model derivation, and usage model analysis was conceptualized and evaluated in a user study.
Results achieved: The application of the developed approach showed high flexibility and scalability in terms of the level of detail. Despite the small number of participants, it was possible to identify several process-related software issues and to reduce significantly needed resources (e.g., cost and time). Hence, a promising alternative to the existing techniques of understanding was found, leading to important improvements regarding a comprehensive and continuous lifecycle.
Lessons learned: The adapted UX approach increases flexibility and widens the spectrum to proceed to the development of a user-centric business software. Although the improved procedure had a promising performance for further application in production environments, there are some open questions, such as handling the possibly high amount of upcoming data or privacy aspects that must be addressed in the future. Independently and regarding the transferability to other application scenarios, promising potential were identified, such as a mechanism for controlling the software’s evolution, the inductive development of usage reference models, and an approach to measuring the ease of learning a new business software.