Hajo A. Reijers

Business process mining: An industrial application

Contemporary information systems (e.g., WfM, ERP, CRM, SCM, and B2B systems) record business events in so-called event logs. Business process mining takes these logs to discover process, control, data, organizational, and social structures. Although many researchers are developing new and more powerful process mining techniques and software vendors are incorporating these in their software, few of the more advanced process mining techniques have been tested on real-life processes. This paper describes the application of process mining in one of the provincial offices of the Dutch National Public Works Department, responsible for the construction and maintenance of the road and water infrastructure. Using a variety of process mining techniques, we analyzed the processing of invoices sent by the various subcontractors and suppliers from three different perspectives: (1) the process perspective, (2) the organizational perspective, and (3) the case perspective. For this purpose, we used some of the tools developed in the context of the ProM framework. The goal of this paper is to demonstrate the applicability of process mining in general and our algorithms and tools in particular.

Seven process modeling guidelines (7PMG)

Business process modeling is heavily applied in practice, but important quality issues have not been addressed thoroughly by research. A notorious problem is the low level of modeling competence that many casual modelers in process documentation projects have. Existing approaches towards model quality might be of benefit, but they suffer from at least one of the following problems. On the one hand, frameworks like SEQUAL and the Guidelines of Modeling are too abstract to be applicable for novices and non-experts in practice. On the other hand, there are collections of pragmatic hints that lack a sound research foundation. In this paper, we analyze existing research on relationships between model structure on the one hand and error probability and understanding on the other hand. As a synthesis we propose a set of seven process modeling guidelines (7PMG). Each of these guidelines builds on strong empirical insights, yet they are formulated to be intuitive to practitioners. Furthermore, we analyze how the guidelines are prioritized by industry experts. In this regard, the seven guidelines have the potential to serve as an important tool of knowledge transfer from academia into modeling practice.

Discovering Social Networks from Event Logs

Process mining techniques allow for the discovery of knowledge based on so-called “event logs”, i.e., a log recording the execution of activities in some business process. Many information systems provide such logs, e.g., most WFM, ERP, CRM, SCM, and B2B systems record transactions in a systematic way. Process mining techniques typically focus on performance and control-flow issues. However, event logs typically also log the performer, e.g., the person initiating or completing some activity. This paper focuses on mining social networks using this information. For example, it is possible to build a social network based on the hand-over of work from one performer to the next. By combining concepts from workflow management and social network analysis, it is possible to discover and analyze social networks. This paper defines metrics, presents a tool, and applies these to a real event log within the setting of a large Dutch organization.

What makes process models understandable

Despite that formal and informal quality aspects are of significantimportance to business process modeling, there is only little empiricalwork reported on process model quality and its impact factors. Inthis paper we investigate understandability as a proxy for quality of processmodels and focus on its relations with personal and model characteristics.We used a questionnaire in classes at three European universitiesand generated several novel hypotheses from an exploratory data analysis.Furthermore, we interviewed practitioners to validate our findings.The results reveal that participants tend to exaggerate the differences inmodel understandability, that self-assessment of modeling competenceappears to be invalid, and that the number of arcs in models has animportant influence on understandability.

Activity labeling in process modeling: Empirical insights and recommendations

Few studies have investigated the factors contributing to the successful practice of process modeling. In particular, studies that contribute to the act of developing process models that facilitate communication and understanding are scarce. Although the value of process models is not only dependent on the choice of graphical constructs but also on their annotation with textual labels, there has been hardly any work on the quality of these labels. Accordingly, the research presented in this paper examines activity labeling practices in process modeling. Based on empirical data from process modeling practice, we identify and discuss different labeling styles and their use in process modeling praxis. We perform a grammatical analysis of these styles and use data from an experiment with process modelers to examine a range of hypotheses about the usability of the different styles. Based on our findings, we suggest specific programs of research towards better tool support for labeling practices. Our work contributes to the emerging stream of research investigating the practice of process modeling and thereby contributes to the overall body of knowledge about conceptual modeling quality.

A Study Into the Factors That Influence the Understandability of Business Process Models

Business process models are key artifacts in the development of information systems. While one of their main purposes is to facilitate communication among stakeholders, little is known about the factors that influence their comprehension by human agents. On the basis of a sound theoretical foundation, this paper presents a study into these factors. Specifically, the effects of both personal and model factors are investigated. Using a questionnaire, students from three different universities evaluated a set of realistic process models. Our findings are that both types of investigated factors affect model understanding, while personal factors seem to be the more important of the two. The results have been validated in a replication that involves professional modelers.

A discourse on complexity of process models

Complexity has undesirable effects on, among others, the correctness, maintainability, and understandability of business process models. Yet, measuring complexity of business process models is a rather new area of research with only a small number of contributions. In this paper, we survey findings from neighboring disciplines on how complexity can be measured. In particular, we gather insight from software engineering, cognitive science, and graph theory, and discuss in how far analogous metrics can be defined on business process models.

Product-Based Workflow Design

In manufacturing, the interaction between the design of a product and the process to manufacture this product is studied in detail. Consider, for example, material requirements planning (MRP) as part of current enterprise resource planning (ERP) systems, which is mainly driven by the bill of material (BOM). For information-intensive products such as insurances, and many other services, the workflow process typically evolves or is redesigned without careful consideration of the structure and characteristics of the product. In this paper, we present a method named product-based workflow design (PBWD). PBWD takes the product specification and three design criteria as a starting point, after which formal models and techniques are used to derive a favorable new design of the workflow process. The ExSpect tool is used to support PBWD. Finally, using a real case study, we demonstrate that a full evaluation of the search space for a workflow design may be feasible depending on the chosen design criteria and the specific nature of the product specifications.

Editorial: Managing large collections of business process models-Current techniques and challenges

Nowadays, business process management is an important approach for managing organizations from an operational perspective. As a consequence, it is common to see organizations develop collections of hundreds or even thousands of business process models. Such large collections of process models bring new challenges and provide new opportunities, as the knowledge that they encapsulate requires to be properly managed. Therefore, a variety of techniques for managing large collections of business process models is being developed. The goal of this paper is to provide an overview of the management techniques that currently exist, as well as the open research challenges that they pose.

Modularity in Process Models: Review and Effects

The use of subprocesses in large process models is an important step in modeling practice to handle complexity. While there are several advantages attributed to such a modular design, including ease of reuse, scalability, and enhanced understanding, the lack of precise guidelines turns out to be a major impediment for applying modularity in a systematic way. In this paper we approach this area of research from a critical perspective. Our first contribution is a review of existing approaches to process model modularity. This review shows that aside from some limited insights, a systematic and grounded approach to finding the optimal modularization of a process model is missing. Therefore, we turned to modular process models from practice to study their merits. In particular, we set up an experiment involving professional process modelers and tested the effect of modularization on understanding. Our second contribution, stemming from this experiment, is that modularity appears to pay off. We discuss some of the limitations of our research and implications for future design-oriented approaches.