USER EVALUATION OF SYMBOLS FOR CORE BUSINESS PROCESS MODELING CONCEPTS

Process modeling notations are visual languages that use symbols to represent their main concepts. This study investigates the quality of such symbols from users’ perspective. The design of a symbol influences whether it is easy to spot in a model and is correctly associated with the concept it represents. In an empirical study with 188 participants, the normative ratings of process model symbols (for the basic concepts of start, end, task, AND, XOR) were gathered on the dimensions of perceptual pop-out, semantic transparency, perceptual discriminability, and aesthetics. Overall, the results are consistent with our predictions based on the theoretical analyses of the designs of the symbols. Prior familiarity with process modeling notations led to more clear-cut evaluations of routing symbols (AND, XOR) and a reduced tendency to prefer middle rating options, but it did not affect the evaluations of the other symbols. Standardization organizations and academic developers of notations can use insights from the study to enhance the usability of process modeling notations

Influence factors for local comprehensibility of process models

The main aim of this study is to investigate human understanding of process models and to develop an improved understanding of its relevant influence factors. Aided by assumptions from cognitive psychology, this article attempts to address specific deductive reasoning difficulties based on process models. The authors developed a research model to capture the influence of two effects on the cognitive difficulty of reasoning tasks: (i) the presence of different control-flow patterns (such as conditional or parallel execution) in a process model and (ii) the interactivity of model elements. Based on solutions to 61 different reasoning tasks by 155 modelers, the results from this study indicate that the presence of certain control-flow patterns influences the cognitive difficulty of reasoning tasks. In particular, sequence is relatively easy, while loops in a model proved difficult. Modelers with higher process modeling knowledge performed better and rated subjective difficulty of loops lower than modelers with lower process modeling knowledge. The findings additionally support the prediction that interactivity between model elements is positively related to the cognitive difficulty of reasoning. Our research contributes to both academic literature on the comprehension of process models and practitioner literature focusing on cognitive difficulties when using process models

ON THE THEORETICAL FOUNDATIONS OF RESEARCH INTO THE UNDERSTANDABILITY OF BUSINESS PROCESS MODELS

Against the background of the growing significance of Business Process Management (BPM) for Information Systems (IS) research and practice, especially the field of Business Process Modeling gains more and more importance. Business process models support communication about as well as the coordination of processes and have become a widely adopted tool in practice. As the understandability of business process models plays a crucial role in communication processes, more and more studies on process model understandability have been conducted in IS research. This article aims at investigating underlying theories of research into business process model understandability by means of an in-depth analysis of 126 systematically retrieved research articles on the topic. It shows in how far process model understandability research is multi-theoretically founded. Identified theories differ regarding addressed subject matters, their coverage, their focus as well as the underlying notion of model understanding, which is exemplarily demonstrated and discussed in this article. Moreover, implications of the findings are discussed and an outlook on future business process model understandability research and on the integration potential of theories in this field is given

Towards the development of stylized facts on the understandability of graphical business process models

The development of theory is one of the major tasks of every scientific discipline, and thus of Information Systems Research (ISR) as well as Business Informatics (BI). While different approaches can be used to develop theory in ISR and BI, there is one “dominant” way of IS theory development which has been described by GROVER and LYYTINEN in a recent article published in MISQ as the common “epistemic script”. The authors criticize this epistemic script for promoting a quite restricted production of IS-related knowledge. Furthermore, GROVER and LYYTINEN, identify new potential ways of overcoming the common epistemic script and propose – among others – the concept of Stylized Facts (SF) as one potential way for innovative knowledge production in ISR and BI. Against the background that we – the authors of this report – have been using Stylized Facts as a research approach for some years and can confirm the potential of this approach, the following report presents the idea and the current state of a promising comprehensive dissertation project (first author of this report) using Stylized Facts in ISR and BI which started in 2014. In the following, the idea of developing Stylized Facts regarding the understandability of graphical business process models is elaborated. Besides the presentation of an approach for a transparent development of SF, a comprehensive application example will illustrate the derivation of a SF regarding the relationships of the structuredness of business process models and the resulting model understandability

Towards the development of stylized facts on the understandability of graphical business process models

The development of theory is one of the major tasks of every scientific discipline, and thus of Information Systems Research (ISR) as well as Business Informatics (BI). While different approaches can be used to develop theory in ISR and BI, there is one “dominant” way of IS theory development which has been described by GROVER and LYYTINEN in a recent article published in MISQ as the common “epistemic script”. The authors criticize this epistemic script for promoting a quite restricted production of IS-related knowledge. Furthermore, GROVER and LYYTINEN, identify new potential ways of overcoming the common epistemic script and propose – among others – the concept of Stylized Facts (SF) as one potential way for innovative knowledge production in ISR and BI. Against the background that we – the authors of this report – have been using Stylized Facts as a research approach for some years and can confirm the potential of this approach, the following report presents the idea and the current state of a promising comprehensive dissertation project (first author of this report) using Stylized Facts in ISR and BI which started in 2014. In the following, the idea of developing Stylized Facts regarding the understandability of graphical business process models is elaborated. Besides the presentation of an approach for a transparent development of SF, a comprehensive application example will illustrate the derivation of a SF regarding the relationships of the structuredness of business process models and the resulting model understandability

Design of Data-Driven Decision Support Systems for Business Process Standardization

Increasingly dynamic environments require organizations to engage in business process standardization (BPS) in response to environmental change. However, BPS depends on numerous contingency factors from different layers of the organization, such as strategy, business models (BMs), business processes (BPs) and application systems that need to be well-understood (“comprehended”) and taken into account by decision-makers for selecting appropriate standard BP designs that fit the organization. Besides, common approaches to BPS are non-data-driven and frequently do not exploit increasingly avail-able data in organizations. Therefore, this thesis addresses the following research ques-tion: “How to design data-driven decision support systems to increase the comprehen-sion of contingency factors on business process standardization?”. Theoretically grounded in organizational contingency theory (OCT), this thesis address-es the research question by conducting three design science research (DSR) projects to design data-driven decision support systems (DSSs) for SAP R/3 and S/4 HANA ERP systems that increase comprehension of BPS contingency factors. The thesis conducts the DSR projects at an industry partner within the context of a BPS and SAP S/4 HANA transformation program at a global manufacturing corporation. DSR project 1 designs a data-driven “Business Model Mining” system that automatical-ly “mines” BMs from data in application systems and represents results in an interactive “Business Model Canvas” (BMC) BI dashboard to comprehend BM-related BPS con-tingency factors. The project derives generic design requirements and a blueprint con-ceptualization for BMM systems and suggests an open, standardized reference data model for BMM. The project implements the software artifact “Business Model Miner” in Microsoft Azure / PowerBI and demonstrates technical feasibility by using data from an educational SAP S/4 HANA system, an open reference dataset, and three real-life SAP R/3 ERP systems. A field evaluation with 21 managers at the industry partner finds differences between tool results and BMCs created by managers and thus the po-tential for a complementary role of BMM tools to enrich the comprehension of BMs. A further controlled laboratory experiment with 142 students finds significant beneficial impacts on subjective and objective comprehension in terms of effectiveness, efficiency, and relative efficiency. Second, DSR project 2 designs a data-driven process mining DSS “KeyPro” to semi-automatically discover and prioritize the set of BPs occurring in an organization from log data to concentrate BPS initiatives on important BPs given limited organizational resources. The project derives objective and quantifiable BP importance metrics from BM and BPM literature and implements KeyPro for SAP R/3 ERP and S/4 HANA sys-tems in Microsoft SQL Server / Azure and interactive PowerBI dashboards. A field evaluation with 52 managers compares BPs detected manually by decision-makers against BPs discovered by KeyPro and reveals significant differences and a complemen-tary role of the artifact to deliver additional insights into the set of BPs in the organiza-tion. Finally, a controlled laboratory experiment with 30 students identifies the dash-boards with the lowest comprehension for further development. Third, OCT requires organizations to select a standard BP design that matches contin-gencies. Thus, DSR project 3 designs a process mining DSS to select a standard BP from a repository of different alternative designs based on the similarity of BPS contin-gency factors between the as-is process and the to-be standard processes. DSR project 3 thus derives four different process model variants for representing BPS contingency factors that vary according to determinant factors of process model comprehension (PMC) identified in PMC literature. A controlled laboratory evaluation with 150 stu-dents identifies significant differences in PMC. Based on laboratory findings, the DSS is implemented in the BPM platform “Apromore” to select standard BP reference mod-els from the SAP Best Practices Explorer for SAP S/4 HANA and applied for the pur-chase-to-pay and order-to-cash process of a manufacturing company