An empirical investigation of intuitive understandability of process diagrams

• Lower complexity BPMN diagrams were outperformed by EPC or UML AD ones.
• Higher complexity EPC diagrams were outperformed by BPMN or UML AD ones.
• UML AD was recognized as being the most versatile notation.
• Our study can help decide which notation to use when representing processes.

ContextBusiness process modeling is an activity that includes several different roles, e.g. business analysts, technical analysts and software developers. The resulting process diagrams can be either simple or complex. Nonetheless, they must be understandable to everyone, even those without the necessary knowledge of process modeling notations.ObjectiveThe goal of our research was to evaluate intuitive understandability of diagrams, modeled in different process modeling notations, with regard to diagram complexity.MethodAn empirical research was conducted, including 103 students with the goal to empirically validate the intuitiveness of the diagrams, modeled in most commonly used process modeling notations, i.e. Unified Modeling Language 2.0 Activity Diagram (UML AD), Business Process Model and Notation (BPMN) and Event Driven Process Chain (EPC). Results were analyzed using the Kruskal–Wallis test, together with the Mann–Whitney post hoc tests with Bonferroni correction.ResultsIn the case of processes with lesser complexity, participants using BPMN diagrams were significantly outperformed by those using either EPC or UML AD ones. However, when complexity of processes was higher, participants using EPC diagrams performed significantly worse than those using the UML AD and BPMN counterparts. Moreover, participants that used UML AD diagrams were not significantly outperformed by users of diagrams in other process modeling notations, regardless of their complexity. Thus, UML AD was recognized as being the most versatile notation.ConclusionSince the existing studies do not offer a holistic overview of the intuitive understandability of process diagrams with different complexity, modeled in different process modeling notations, our research can help decide which notation to use when representing processes that have to be understandable by all stakeholders.