Active Anomaly Detection for Key Item Selection in Process Auditing

Process mining allows auditors to retrieve crucial information about transactions by analysing the process data of a client. We propose an approach that supports the identification of unusual or unexpected transactions, also referred to as exceptions. These exceptions can be selected by auditors as “key items”, meaning the auditors wants to look further into the underlying documentation of the transaction. The approach encodes the traces, assigns an anomaly score to each trace, and uses the domain knowledge of auditors to update the assigned anomaly scores through active anomaly detection. The approach is evaluated with three groups of auditors over three cycles. The results of the evaluation indicate that the approach has the potential to support the decision-making process of auditors. Although auditors still need to make a manual selection of key items, they are able to better substantiate this selection. As such, our research can be seen as a step forward with respect to the usage of anomaly detection and data analysis in process auditing

The SWORD is Mightier Than the Interview: A Framework for Semi-automatic WORkaround Detection

Workarounds can give valuable insights into the work processes that are carried out within organizations. To date, workarounds are usually identified using qualitative methods, such as interviews. We propose the semi-automated WORkaround Detection (SWORD) framework, which takes event logs as input. This extensible framework uses twenty-two patterns to semi-automatically detect workarounds. The value of the SWORD framework is that it can help to identify workarounds more efficiently and more thoroughly than is possible by the use of a more traditional, qualitative approach. Through the use of real hospital data, we demonstrate the applicability and effectiveness of the SWORD framework in practice. We focused on the use of three patterns, which all turned out to be applicable to the characteristics of the data set. The use of two of these patterns also led to the identification of actual workarounds. Future work is geared to the extension of the patterns within the framework and the enhancement of techniques that can help to identify these in real-world data

The biggest business process management problems to solve before we die

It may be tempting for researchers to stick to incremental extensions of their current work to plan future research activities. Yet there is also merit in realizing the grand challenges in one’s field. This paper presents an overview of the nine major research problems for the Business Process Management discipline. These challenges have been collected by an open call to the community, discussed and refined in a workshop setting, and described here in detail, including a motivation why these problems are worth investigating. This overview may serve the purpose of inspiring both novice and advanced scholars who are interested in the radical new ideas for the analysis, design, and management of work processes using information technology

Special section of business process modeling, development and support (BPMDS) 2019 - transformative BPMDS.

The business process modeling, development and support (BPMDS) working conference series is a meeting place for researchers and practitioners in the areas of business development and business applications development. By incorporating these views, BPMDS offers a unique community venue that integrates different streams of research on business processes and business information systems, and takes in a broad view on the whole range of BPMDS research and interrelationships among different perspectives. This makes it attractive for authors to publish cutting-edge research results at BPMDS. In this special section, a selection of the most influential contributions to the 2019 edition of the working conference are collected

Mapping a high‐level overview of information flows in the Dutch declaration chain for medical specialist health care

This study is based on Philippe van der Voorn’s master’s dissertation at the Utrecht University, Department of Science, Information and Computing Sciences. The problem identified was a lack of an integrated information chain and clear governance structure for information flow in the Netherlands’ health care sector. The method of Design Science was followed to construct an overview model of the chain, and towards a business process model that is intuitive for both technical and business users. An initial declaration chain was identified in the literature and presented, to be confirmed and elaborated on via eight interviews at seven different organisations in the medical specialist health care sector. Based on these interviews, the draft overview was adjusted and a Business Process Model and Notation model created that indicates the shared understanding of the data elements and activities between the organisations. The contribution of the overview of the declaration chain, in particular, can help medical specialist staff obtain an understanding of the administrative side of their work, and with a clear information infrastructure lead to better working processes and information quality

Animation as a dynamic visualization technique for improving process model comprehension

Process models are widely used for various system analysis and design activities, but it is challenging for stakeholders to understand these complex artifacts. In this work, we focus on the use of dynamic visualization techniques, in particular animation, to help reduce users’ cognitive load when making sense of process models. We built on the principles of the cognitive theory of multimedia learning, cognitive load theory, and cognitive dimensions framework to develop an adaptive animation solution. Our experiments suggested that process model comprehension improves when users of process models are provided with animation features; the effect is moderated by process modeling expertise according to a U-shape. Our study contributes to the field of conceptual modeling by making a strong case for the use of animation to support complex problem-solving tasks. Moreover, our animation solution offers ample opportunities for being integrated into industrial modeling tools

The Information Systems Modeling Suite - Modeling the Interplay Between Information and Processes.

According to our recent proposal, an information system is a combination of a process model captured as a Petri Net with Identifiers, an information model specified in the first-order logic over finite sets with equality, and a specification of how the transitions in the net manipulate information facts. The Information Systems Modeling (ISM) Suite is an integrated environment for developing, simulating, and analyzing models of information systems, released under an open-source license. This paper presents the basic features of the ISM Suite

Approaches for Documentation in Continuous Software Development

It is common practice for practitioners in industry as well as for ICT/CS students to keep writing – and reading ­– about software products to a bare minimum. However, refraining from documentation may result in severe issues concerning the vaporization of knowledge regarding decisions made during the phases of design, build, and maintenance. In this article, we distinguish between knowledge required upfront to start a project or iteration, knowledge required to complete a project or iteration, and knowledge required to operate and maintain software products. With `knowledge', we refer to actionable information. We propose three approaches to keep up with modern development methods to prevent the risk of knowledge vaporization in software projects. These approaches are `Just Enough Upfront' documentation, `Executable Knowledge', and `Automated Text Analytics' to help record, substantiate, manage and retrieve design decisions in the aforementioned phases. The main characteristic of `Just Enough Upfront' documentation is that knowledge required upfront includes shaping thoughts/ideas, a codified interface description between (sub)systems, and a plan. For building the software and making maximum use of progressive insights, updating the specifications is sufficient. Knowledge required by others to use, operate and maintain the product includes a detailed design and accountability of results. `Executable Knowledge' refers to any executable artifact except the source code. Primary artifacts include Test Driven Development methods and infrastructure-as-code, including continuous integration scripts. A third approach concerns `Automated Text Analysis' using Text Mining and Deep Learning to retrieve design decisions

Detecting Role Inconsistencies in Process Models

Business process models capture crucial information about business operations. To overcome the challenge of maintaining process definitions in large process repositories, researchers have suggested methods to discover errors in the functional and the behavioral perspectives of process models. However, there is a gap in the literature on the detection of problems on the organizational perspective of process models, which is critical to manage the resources and the responsibilities within organizations. In this paper, we introduce an approach to automatically detect inconsistencies between activities and roles in process models. Our approach implements natural language processing techniques and enterprise semantics to identify ambiguous, redundant, and missing roles in textual descriptions. We applied our approach on the process model repository of a major telecommunication company. A quantitative evaluation of our approach with 282 real-life activities displayed that this approach can accurately discover role inconsistencies. Practitioners can achieve significant quality improvements in their process model repositories by applying the approach on process models complemented with textual descriptions

Method to Address Complexity in Organizations Based on a Comprehensive Overview

Digitalization increasingly enforces organizations to accommodate changes and gain resilience. Emerging technologies, changing organizational structures and dynamic work environments bring opportunities and pose new challenges to organizations. Such developments, together with the growing volume and variety of the exchanged data, mainly yield complexity. This complexity often represents a solid barrier to efficiency and impedes understanding, controlling, and improving processes in organizations. Hence, organizations are prevailingly seeking to identify and avoid unnecessary complexity, which is an odd mixture of different factors. Similarly, in research, much effort has been put into measuring, reviewing, and studying complexity. However, these efforts are highly fragmented and lack a joint perspective. Further, this negatively affects the complexity research acceptance by practitioners. In this study, we extend the body of knowledge on complexity research and practice addressing its high fragmentation. In particular, a comprehensive literature analysis of complexity research is conducted to capture different types of complexity in organizations. The results are comparatively analyzed, and a morphological box containing three aspects and ten features is developed. In addition, an established multi-dimensional complexity framework is employed to synthesize the results. Using the findings from these analyses and adopting the Goal Question Metric, we propose a method for complexity management. This method serves to provide key insights and decision support in the form of extensive guidelines for addressing complexity. Thus, our findings can assist organizations in their complexity management initiatives