Martin Matzner

Beyond process monitoring: a proof‐of‐concept of event‐driven business activity management

Purpose – The purpose of this paper is to show how to employ complex event processing (CEP) for the observation and management of business processes. It proposes a conceptual architecture of BPM event producer, processor, and consumer and describes technical implications for the application with standard software in a perfect order scenario.Design/methodology/approach – The authors discuss business process analytics as the technological background. The capabilities of CEP in a BPM context are outlined an architecture design is proposed. A sophisticated proof‐of‐concept demonstrates its applicability.Findings – The results overcome the separation and data latency issues of process controlling, monitoring, and simulation. Distinct analyses of past, present, and future blur into a holistic real‐time approach. The authors highlight the necessity for configurable event producer in BPM engines, process event support in CEP engines, a common process event format, connectors to visualizers, notifiers and return c...

Comprehensible predictive models for business processes

Predictive modeling approaches in business process management provide a way to streamline operational business processes. For instance, they can warn decision makers about undesirable events that are likely to happen in the future, giving the decision maker an opportunity to intervene. The topic is gaining momentum in process mining, a field of research that has traditionally developed tools to discover business process models from data sets of past process behavior. Predictive modeling techniques are built on top of process-discovery algorithms. As these algorithms describe business process behavior using models of formal languages (e.g., Petri nets), strong language biases are necessary in order to generate models with the limited amounts of data included in the data set. Naturally, corresponding predictive modeling techniques reflect these biases. Based on theory from grammatical inference, a field of research that is concerned with inducing language models, we design a new predictive modeling technique based on weaker biases. Fitting a probabilistic model to a data set of past behavior makes it possible to predict how currently running process instances will behave in the future. To clarify how this technique works and to facilitate its adoption, we also design a way to visualize the probabilistic models. We assess the effectiveness of the technique in an experimental evaluation with synthetic and real-world data.

Configurative Service Engineering - A Rule-Based Configuration Approach for Versatile Service Processes in Corrective Maintenance

Recently, service orientation has increasingly been debated both in research and practice. While researchers postulate a paradigm shift towards services as the basic unit of exchange in economies, companies strive to efficiently provide a wide array of business services to their customers. To accomplish this, companies (a) are required to consciously design the services in their portfolio with respect to a structured engineering approach and (b) also have to flexibly adapt the engineered service processes to individual customer needs, wants, and demands. Hence, services shall be supplied efficiently and in consistent quality without sacrificing customization for customers. Supporting this mass-customization strategy for business services, we present a configurative service engineering approach. After engineering a configurable process model for business services, customized service processes can efficiently be derived from the model by applying configuration mechanisms. The process of configuration is aided by the software tool Adapt(X). We present the concept and tool support by applying them on business services for corrective maintenance in the mechanical engineering sector.

A Review of Event Formats as Enablers of Event-Driven BPM

Event-driven Business Process Management (edBPM) is based upon exchanging and processing business events. As yet, no commonly adopted event format for communicating business events between distributed event producers and consumers has emerged. This paper is an effort to review the status quo of event formats against the requirements of edBPM. We particularly discuss BPAF, CBE, and XES as promising candidates and identify prospects for development.

Teaching medium-sized ERP systems - a problem-based learning approach

In order to increase the diversity in IS education, we discuss an approach for teaching medium-sized ERP systems in master courses. Many of today’s IS curricula are biased toward large ERP packages. Nevertheless, these ERP systems are only a part of the ERP market. Hence, this chapter describes a course outline for a course on medium-sized ERP systems. Students had to study, analyze, and compare five different ERP systems during a semester. The chapter introduces a procedure model and scenario for setting up similar courses at other universities. Furthermore, it describes some of the students’ outcomes and evaluates the contribution of the course with regard to a practical but also academic IS education.

preCEP: facilitating predictive event-driven process analytics

The earlier critical decision can be made, the more business value can be retained or even earned. The goal of this research is to reduce a decision makers action distance to the observation of critical events. We report on the development of the software tool preCEP that facilitates predictive event-driven process analytics (edPA). The tool enriches business activity monitoring with prediction capabilities. It is implemented by using complex event processing technology (CEP). The prediction component is trained with event log data of completed process instances. The knowledge obtained from this training, combined with event data of running process instances, allows for making predictions at intermediate execution stages on a currently running process instances future behavior and on process metrics. preCEP comprises a learning component, a run-time environment as well as a modeling environment, and a visualization component of the predictions.

Design science in service research: a framework-based review of IT artifacts in Germany

The purpose of this study is to analyze the nature of IT artifacts that have been proposed in the emerging discipline of Service Science, Management and Engineering (SSME) as well as to provide further directions for design research in the service discipline. We review a sample of 123 service-related IT artifacts - that we identified on a German online research portal - by coding them with a framework for design research in the service science discipline. The key insights derived from the analysis are: (1) methods dominate other artifact types; (2) instantiations are almost exclusively developed for supporting the potential dimension of services; (3) research on customer solutions focuses on an inside-out perspective; (4) new constructs are predominantly developed for modeling the outcome dimension of services; (5) artifacts often possess a narrow scope; and (6) artifacts are seldom instantiated into software tools. These novel insights are expected to guide future design research in the service discipline by identifying areas which have only been sparsely addressed by design research or are yet to evolve to a sufficient state of maturity. Our approach is original as it features an early and innovative endeavor for identifying the nature of IT artifacts in SSME.

Slipstream: architecture options for real-time process analytics

Timely insight into a companys business processes is of great importance for operational efficiency. However, still today companies struggle with inflexibility of monitoring solutions and reacting to process information on time. We review the current state of the art of business process management and business activity management. Based on that we develop an architecture for event-driven business activity monitoring which is capable of standalone process analytics or can make use of complex event processing engines to filter and aggregate process events in realtime. We discuss advantages and disadvantages of the two options in terms of ease of use, flexibility, and extensibility and close by introducing on future research directions based on our experiences from a prototypical implementation using standard software.

Total Cost of Service Life: The Need for Decision Support in Selecting, Comparing and Orchestrating Services

Conventional services as well as web services are explored and discovered by descriptions of their properties. Such properties are either functional or non-functional. Amongst the non-functional properties is the price for service consumption. Evaluating the price of a service is difficult due to a huge variety of existing pricing models and conditions. But still, it is important to a service consumer to evaluate arising costs, esp. in scenarios of long-term usage and if combining several services. In theory and practice so far there exists no method that sufficiently guides the decision of selecting specific services regarding the non-functional property price. This paper strives to promote research-in-progress for such a method, which is based on the TCO concept and on insights from capital budgeting in investment theory. The method is indented to support service consumers in selecting a specific service, in comparing several functionally similar services, and finally in evaluating complete service orchestrations.

Cloud-based Engineering Design and Manufacturing: State-of-the-Art

Abstract Cloud-based technologies proliferated in the past few years, while the manufacturing industry moved towards digitization and network. Therefore, cloud-based technologies have been adopted in the development of new generation manufacturing systems which orchestrate different activities, including product design, process and task planning, production, customer service, etc. These new cloud-ingrained technologies have the potential to change the collaboration of product development partners, the processing and sharing of information as well as utilization rates of critical equipment. Cloud-based technologies affect many aspects of manufacturing activities, and they therefore have the power to enable new or change existing business models of the manufacturing industry. Based on the literature review, this paper analyzes the latest requirements, challenges, and trends of the manufacturing industry. It structures the findings in the coherent manner and further hypothesizes how cloud computing may address identified requirements and challenges as well as realize or support new concepts in manufacturing.