1,721,438 research outputs found
Call for Papers, Issue 5/2021 Process Mining at the Enterprise Level
No full textMendling, J (reprint author), Vienna Univ Econ & Business, Vienna, Austria.
[email protected]
Event-case correlation for process mining using probabilistic optimization
No full textProcess mining supports the analysis of the actual behavior and performance of business processes using event logs. An essential requirement is that every event in the log must be associated with a unique case identifier (e.g., the order ID of an order-to-cash process). In reality, however, this case identifier may not always be present, especially when logs are acquired from different systems or extracted from non-process-aware information systems. In such settings, the event log needs to be pre-processed by grouping events into cases — an operation known as event correlation. Existing techniques for correlating events have worked with assumptions to make the problem tractable: some assume the generative processes to be acyclic, while others require heuristic information or user input. Moreover, they abstract the log to activities and timestamps, and miss the opportunity to use data attributes. In this paper, we lift these assumptions and propose a new technique called EC-SA-Data based on probabilistic optimization. The technique takes as inputs a sequence of timestamped events (the log without case IDs), a process model describing the underlying business process, and constraints over the event attributes. Our approach returns an event log in which every event is associated with a case identifier. The technique allows users to flexibly incorporate rules on process knowledge and data constraints. The approach minimizes the misalignment between the generated log and the input process model, maximizes the support of the given data constraints over the correlated log, and the variance between activity durations across cases. Our experiments with various real-life datasets show the advantages of our approach over the state of the art
How to Conduct Valid Information Systems Engineering Research?
No full textAlgorithms play an important role for information systems engineering research as they are the foundational building block of many techniques. At the same time, specific methodological guidance on how to design, evaluate, and present algorithm-based research is scarce. This tutorial addresses the needs of doctoral students and early career researchers to understand how they can establish a solid research contribution based on established methodological guidelines. No specific background knowledge is required. The content of the tutorial focuses on general challenges of information systems engineering research. The objective of this tutorial is to provide early career researchers with a profound understanding of basic concepts from the philosophy of science and specific strategies how algorithms can be scientifically investigated and presented in a systematic manner.Einstein Foundation Berlin [EPP-2019-524]; German Federal Ministry o
How to Conduct Valid Information Systems Engineering Research?
No full textAlgorithms play an important role for information systems engineering research as they are the foundational building block of many techniques. At the same time, specific methodological guidance on how to design, evaluate, and present algorithm-based research is scarce. This tutorial addresses the needs of doctoral students and early career researchers to understand how they can establish a solid research contribution based on established methodological guidelines. No specific background knowledge is required. The content of the tutorial focuses on general challenges of information systems engineering research. The objective of this tutorial is to provide early career researchers with a profound understanding of basic concepts from the philosophy of science and specific strategies how algorithms can be scientifically investigated and presented in a systematic manner.Einstein Foundation Berlin [EPP-2019-524]; German Federal Ministry o
Misplaced product detection using sensor data without planograms
Full text linkAccurate and timely provisioning of products to the customers is essential in retail environments to avoid missed sales opportunities. One cause for missed sales is that products are misplaced in the store. This can be addressed by fast and accurately detecting those misplacements. A problem of current detection methods for misplaced products is their reliance on up-to-date planogram information, which is often missing in practice. This paper investigates the effectiveness and efficiency of outlier detection methods for finding misplaced products without planograms. To that end, we conduct simulation studies with realistic parameters for different store parameters and sensor infrastructure settings. We also evaluate the detection methods in a real setting with an RFID inventory robot. The findings indicate that our proposed MiProD aggregation of individual detection methods consistently outperforms individual techniques in detecting misplaced products
Structuring Empirical Research on Process Mining at the Individual Level Using the Theory of Effective Use
No full textA growing number of empirical papers on the topic of process mining has been published in years. After a first wave of contributions on application scenarios, there has been a second wave aiming to establish theoretical insights into how process mining tools are used and how benefits unfold from this usage. Many of these papers follow an explorative, qualitative, or inductive approach. A weakness of these contributions is their theoretical cohesion and integration. This paper makes an effort to integrate them into a more holistic theory that can eventually provide a foundation for more deductive and quantitative empirical research on process mining. To this end, we build on the theory of effective use and focus on the individual effect on decision makers. We find opportunities for revision and refinement of this theory for process mining. Specifically, we discuss moving from constructs on learning to expertise, and integrating a pragmatic perspective that complements the semantic emphasis of representational fidelity
Mining batch activation rules from event logs
No full textBatch processing refers to an organization of work in which cases are synchronized such that they can be processed as a group. Prior research has studied batch processing mainly from a deductive angle, trying to identify optimal rules for composing batches. As a consequence, we lack methodological support to investigate according to which rules human resources build batches in work settings where batching rules are not strictly enforced. In this paper, we address this research gap by developing a technique to inductively mine batch activation rules from process execution data. The obtained batch activation rules can be used for various purposes, including to explicate the real-life batching behavior of human resources; to determine the compliance between the prescribed and actual batching behavior; or to investigate the influence of alternative batching behavior on service levels. The evaluation of our technique using both synthetic and real-world data demonstrates its effectiveness. With this work we complement prescriptive research on batch processing with a descriptive technique that is empirically grounded in process execution data
The NESTT - Rapid Process Redesign
No full textThe higher education sector faces like most information-intensive industries an opportunity-rich, digital future. Nowadays, students demand contemporary, multi-channel learning experiences and fast evolving digital affordances provide universities with a growing design space for their future processes. Legislative changes, a globalizing market of learners and educational providers, and the emergence of new technology-based business models (<i>EduTech</i>) and legislative changes are further features of the current situation in this sector. In order to prepare for and to capitalize on this changing environment the <i>Queensland University of Technology (QUT)</i>, like any university, needs to ensure operational inefficiencies are addressed as part of the required organisational transformation. However, traditional BPM approaches are often time-consuming and not tailored to immediate process transformation, meaning a new, dedicated and agile approach for <i>QUT</i> was needed
Interview with Varun Grover on ‘‘Business Processes, Information Technology and Its Evolution in the Digital Age’’
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