Evaluating data-centric process approaches: Does the human factor factor in?

Abstract

The Business Process Management field addresses design, improvement, management, support, and execution of business processes. In doing so, we argue that it focuses more on developing modeling notations and process design approaches than on the needs and preferences of the individual who is modeling (i.e., the user). New data-centric process modeling approaches are taken as a relevant and timely stream of process design approaches to test our argument. First, we provide a review of existing data-centric process approaches, culminating in a theoretical classification framework. Next, we empirically evaluate three specific approaches with regard to the claims they make. We had participants representative of actual users try out these approaches on realistic scenarios via a series of work- of claims behind the approaches, but also identify opportunities to further improve them. Most prominently, we found that the usability aspects of all considered approaches are a source of concern. This leads us to the insight that usability aspects of process design approaches are crucial and, in the perception of groups representative of actual users, leave much to be desired. In that sense, our research can be seen as a wake-up call for process modeling notation designers to consider the usability side-and as such, the interest of the human modeler-more than is currently the case.

DALEC: a framework for the systematic evaluation of data-centric approaches to process management software

“…Therefore, the subjective criteria have been left out. [64] provides a first empirical study regarding the usability of data-centric approaches. We aim at performing extensive experimental evaluations with BPM practitioners in future work; more details are outlined in Sect.…”

“…On the topic of the comparison of data-centric approaches, [64] evaluates data-centric approaches with respect to the interests of human modelers, i.e., usability and understandability. In summary, the authors determine that the usability of data-centric approaches is insufficient and must be improved for these approaches to be truly applicable in practice.…”

Data Impact Analysis in Business Processes

“…Data-aware process modeling Many attempts have been made to address the relations between processes and data, sometimes referred to as ''duality of control flow and data flow'' (Kumar 2018). The importance of integrating data and process flows, and the increasing number of studies on this topic, have led to several surveys that consolidate and compare studies in this area (Meyer et al 2011;Reijers et al 2017;Steinau et al 2019). Meyer et al (2011) claim that processes and data are equally important for business process management.…”

“…The evaluation in Reijers et al (2017) addresses 14 datacentric process approaches. The approaches are categorized into three main groups: (1) Data-driven process structures (e.g., Müller et al 2007Müller et al , 2008, in which the objects involved in the process are described using a data-model (each object has a lifecycle to define its states); (2) Productbased workflow design (e.g., Reijers et al 2003;Vanderfeesten et al 2011), in which a model describes the data elements involved in the process in form of tree-like structure (the top elements in the tree are the final data elements that represent the outcome of the process); and (3) Artifact-centric process modeling (e.g., Bhattacharya et al 2009;Cohn and Hull 2009), which focuses on describing how business data (artifacts) are changed by a particular action, task, or service throughout the process (the states of an artifact are described by a lifecycle model, and an information model of the process describes all business artifacts and their relationships).…”

“…They also form a context for functions of the information systems, tying them together in a logical flow. While in the past process models mainly focused on control flows, in the last decade, data-centric approaches for process models gained recognition as necessary for supporting both control and data flows (Reijers et al 2017). Thus, various studies, such as Trčka et al (2009), Rodríguez et al (2012) and Sun and Zhao (2013), consider analyzing and modeling data flows to ensure the complete and accurate design of business processes.…”