Four facets of a process modeling facilitator

Business process modeling as a practice and research field has received great attention in recent years. However, while related artifacts such as models, tools or grammars have substantially matured, comparatively little is known about the activities that are conducted as part of the actual act of process modeling. Especially the key role of the modeling facilitator has not been researched to date. In this paper, we propose a new theory-grounded, conceptual framework describing four facets (the driving engineer, the driving artist, the catalyzing engineer, and the catalyzing artist) that can be used by a facilitator. These facets with behavioral styles have been empirically explored via in-depth interviews and additional questionnaires with experienced process analysts. We develop a proposal for an emerging theory for describing, investigating, and explaining different behaviors associated with Business Process Modeling Facilitation. This theory is an important sensitizing vehicle for examining processes and outcomes from process modeling endeavors

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

Design-time Models for Resiliency

Resiliency in process-aware information systems is based on the availability of recovery flows and alternative data for coping with missing data. In this paper, we discuss an approach to process and information modeling to support the specification of recovery flows and alternative data. In particular, we focus on processes using sensor data from different sources. The proposed model can be adopted to specify resiliency levels of information systems, based on event-based and temporal constraints

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

Effects of Semantic Quality in Business Process Modeling

In contrast to the increasing meaning of business process management (BPM), there is a lack of knowledge about processes that impedes their analysis, implementation, and execution in business process management systems (BPMS). In this context, process modeling is an opportunity to capture process knowledge. Nevertheless, models are incomplete concerning semantic completeness. Therefore, ontologies as explicit and formal specification are used to enrich models semantically to achieve a high degree of semantic quality, model efficiency and effectiveness. But also ontology engineering needs models to describe the underlying discourse of universe. For this reason, it is the paper’s goal to examine and compare the Resource Event Agent Model (REA) with respect to semantic quality, model effectiveness, and -efficiency in data modeling for ontologies. Moreover, the paper addresses the research question, if REA enables an effective modeling to reduce the precision deficit and complexity in BPM. Keywords (Required

Current and Future Issues in BPM Research: A European Perspective from the ERCIS Meeting 2010

Business process management (BPM) is a still-emerging field in the academic discipline of Information Systems (IS). This article reflects on a workshop on current and future issues in BPM research that was conducted by seventeen IS researchers from eight European countries as part of the 2010 annual meeting of the European Research Center for Information Systems (ERCIS). The results of this workshop suggest that BPM research can meaningfully contribute to investigating a broad variety of phenomena that are of interest to IS scholars, ranging from rather technical (e.g., the implementation of software architectures) to managerial (e.g., the impact of organizational culture on process performance). It further becomes noticeable that BPM researchers can make use of several research strategies, including qualitative, quantitative, and design-oriented approaches. The article offers the participants’ outlook on the future of BPM research and combines their opinions with research results from the academic literature on BPM, with the goal of contributing to establishing BPM as a distinct field of research in the IS discipline

Developing a Procedure Model for Business Process Standardization

Firms are focusing more closely on standardizing or homogenizing instances of a particular business process across different business units or locations. Our paper introduces research in progress on a business process standardization (BPS) procedure model that guides firms in conducting effective BPS firm-wide. This model is currently being developed and tested by applying it to a business process at Lufthansa Technik, following a design science cycle and taking an action research approach. This paper shows how we are following the good-practice guidelines of design science and how we intend to evaluate the applicability and effectiveness of the model. Eventually, we expect this model to contribute significantly to extant research on BPS, which has to date focused on the outcomes of BPS and on the contingencies of BPS effectiveness rather than making prescriptive suggestions for reaping substantial process efficiency gains in large and decentralized firms

Business Process Models for Risk Analysis: Expert View

The recent financial turbulences raise questions on how risk analysis is conducted. Regulatory requirements and professional standards have been introduced in the last decade in order to obtain a more reliable internal control on financial reporting process with a new emphasis on business processes. However, there are no standards yet available on how business processes should be captured for facilitating risk analysis in audit assignments. Representations of business processes have been investigated in the field of business process modeling. There exists a broad spectrum of notations and formalisms with relative strengths and weaknesses. Many of the popular notations build on a graph-based representation where activities of a process are connected with directed arcs defining the control flow. Such notations have been widely adopted for redesigning business processes. But also text-based formats have been defined. Corresponding process specifications define the activities of a process as lists with additional free text information. This raises the question whether the tools and methods for analyzing business process risks in auditing practice is appropriate for its objective. This paper reveals the benefits of adopting business process models for auditors toward understanding a companies business processes and the issues need to be considered for further development. The analysis also shows that practitioners use process models rather for risk elicitation and less in risk assessment