912 resultados para Business Administration, Management|Information Science|Engineering, System Science


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Nowadays, process management systems (PMSs) are widely used in many business scenarios, e.g. by government agencies, by insurance companies, and by banks. Despite this widespread usage, the typical application of such systems is predominantly in the context of static scenarios, instead of pervasive and highly dynamic scenarios. Nevertheless, pervasive and highly dynamic scenarios could also benefit from the use of PMSs.

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Automated process discovery techniques aim at extracting process models from information system logs. Existing techniques in this space are effective when applied to relatively small or regular logs, but generate spaghetti-like and sometimes inaccurate models when confronted to logs with high variability. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. This leads to a collection of process models – each one representing a variant of the business process – as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity and low fitness. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically using subprocess extraction. Splitting is performed in a controlled manner in order to achieve user-defined complexity or fitness thresholds. Experiments on real-life logs show that the technique produces collections of models substantially smaller than those extracted by applying existing trace clustering techniques, while allowing the user to control the fitness of the resulting models.

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Determining similarity between business process models has recently gained interest in the business process management community. So far similarity was addressed separately either at semantic or structural aspect of process models. Also, most of the contributions that measure similarity of process models assume an ideal case when process models are enriched with semantics - a description of meaning of process model elements. However, in real life this results in a heavy human effort consuming pre-processing phase which is often not feasible. In this paper we propose an automated approach for querying a business process model repository for structurally and semantically relevant models. Similar to the search on the Internet, a user formulates a BPMN-Q query and as a result receives a list of process models ordered by relevance to the query. We provide a business process model search engine implementation for evaluation of the proposed approach.

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In order to execute, study, or improve operating procedures, companies document them as business process models. Often, business process analysts capture every single exception handling or alternative task handling scenario within a model. Such a tendency results in large process specifications. The core process logic becomes hidden in numerous modeling constructs. To fulfill different tasks, companies develop several model variants of the same business process at different abstraction levels. Afterwards, maintenance of such model groups involves a lot of synchronization effort and is erroneous. We propose an abstraction technique that allows generalization of process models. Business process model abstraction assumes a detailed model of a process to be available and derives coarse-grained models from it. The task of abstraction is to tell significant model elements from insignificant ones and to reduce the latter. We propose to learn insignificant process elements from supplementary model information, e.g., task execution time or frequency of task occurrence. Finally, we discuss a mechanism for user control of the model abstraction level – an abstraction slider.

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Process models are usually depicted as directed graphs, with nodes representing activities and directed edges control flow. While structured processes with pre-defined control flow have been studied in detail, flexible processes including ad-hoc activities need further investigation. This paper presents flexible process graph, a novel approach to model processes in the context of dynamic environment and adaptive process participants’ behavior. The approach allows defining execution constraints, which are more restrictive than traditional ad-hoc processes and less restrictive than traditional control flow, thereby balancing structured control flow with unstructured ad-hoc activities. Flexible process graph focuses on what can be done to perform a process. Process participants’ routing decisions are based on the current process state. As a formal grounding, the approach uses hypergraphs, where each edge can associate any number of nodes. Hypergraphs are used to define execution semantics of processes formally. We provide a process scenario to motivate and illustrate the approach.

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Conceptual modeling is an important tool for understanding and revealing weaknesses of business processes. Yet, the current practice in reengineering projects often considers simply the as-is process model as a brain-storming tool. This approach heavily relies on the intuition of the participants and misses a clear description of the quality requirements. Against this background, we identify four generic quality categories of business process quality, and populate them with quality requirements from related research. We refer to the resulting framework as the Quality of Business Process (QoBP) framework. Furthermore, we present the findings from applying the QoBP framework in a case study with a major Australian bank, showing that it helps to systematically fill the white space between as-is and to-be process modeling.

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Besides classical criteria such as cost and overall organizational efficiency, an organization’s ability to being creative and to innovate is of increasing importance in markets that are overwhelmed with commodity products and services. Business Process Management (BPM) as an approach to model, analyze, and improve business processes has been successfully applied not only to enhance performance and reduce cost but also to facilitate business imperatives such as risk management and knowledge management. Can BPM also facilitate the management of creativity? We can find many examples where enterprises unintentionally reduced or even killed creativity and innovation for the sake of control, performance, and cost reduction. Based on the experiences we have made within case studies with organizations from the creative industries (film industry, visual effects production, etc.,) we believe that BPM can be a facilitator providing the glue between creativity management and well-established business principles. In this article we introduce the notions of creativity-intensive processes and pockets of creativity as new BPM concepts. We further propose a set of exemplary strategies that enable process owners and process managers to achieve creativity without sacrificing creativity. Our aim is to set the baseline for further discussions on what we call creativity-oriented BPM.

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In this editorial letter, we provide the readers of Information Systems Management with a background on process design before we discuss the content of the special issue proper. By introducing and describing a so-called process design compass we aim to clarify what developments in the field are taking place and how the papers in this special issue expand on our current knowledge in this domain.

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Business transformation is, without any doubt, one of those concepts attracting substantial attention in the boardrooms of corporations. However, and not uncommon for an emerging approach, there is currently a plethora of viewpoints on the core characteristics of a business transformation. Unlike well-established approaches such as change, lean, or quality management, business transformation is still under-specified in terms of methodologies and techniques. This status compromises the reaching of shared understanding and progress in an area of ever increasing importance. Motivated by this lack of consensus, this article proposes a new typology of business transformations based on the assessment of 20 global case studies

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As Business Process Management (BPM) is evolving and organisations are becoming more process oriented, the need for Expertise in BPM amongst practitioners has increased. Proactively managing Expertise in BPM is essential to unlock the potential of BPM as a management paradigm and competitive advantage. Whilst great attention is being paid by the BPM community to the technological aspects of BPM, relatively little research or work has been done concerning the expertise aspect of BPM. There is a substantial body of knowledge on expertise itself, however there is no common framework in existence at the time of writing, describing the fundamental attributes characterising Expertise in the illustrative context of BPM. There are direct implications of the understanding and characterisation of Expertise in the context of BPM as a key strategic component and success factor of BPM itself, as well as for those involved in BPM. Expertise in the context of BPM needs to be characterised to understand it, and be able to proactively manage it. Given the relative infancy of research into Expertise in the context of BPM, an exploration of the relevance and importance of Expertise in the context of BPM was considered essential, to ensure the study itself was of value to the BPM field. The aims of this research are firstly to address the two research questions 'why is expertise important and relevant in the context of BPM?', and 'how can Expertise in the context of BPM be characterised?', and secondly, the development of a comprehensive and validated A-priori model characterising Expertise in the illustrative context of BPM. The study is theory-guided. It has been undertaken via an extensive literature review across relevant literature domains, and a revelatory case study utilising several methods: informal discussions, an open-ended survey, and participant observation. An a-priori model was then developed which comprised of several Constructs and Sub-constructs, and several overall aspects of Expertise in BPM. This was followed by the conduct of interviews in the validation phase of the revelatory case study. The primary contributions of this study are to the fields of expertise, BPM and research. Contributions to the field of expertise include a comprehensive review of expertise literature in general and synthesised critique on expertise research, characterisation of expertise in an illustrative context as a system, and a comprehensive narrative of the dynamics and interrelationships of the core attributes characterising expertise. Contributions to the field of BPM include firstly, the establishment of the importance of understanding Expertise in the context of BPM, including a comprehensive overview of the role the relevance and importance of Expertise in the context of BPM, through explanation of the effect of Expertise in BPM. Secondly, a model characterising Expertise in the context of BPM, which can be used by BPM practitioners to clearly articulate and illuminate the state of Expertise in BPM in organisations. Contributions to the field of research include an extended view of Systems Theory developed, reflecting the importance of the system context in systems thinking, and a narrative on ontological innovation through the positioning of ontology as a meta-model of Expertise in the context of BPM.

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Business process models have traditionally been an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach for process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions as they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. Empirical data obtained in this study suggests that this approach may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

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Business processes are prone to continuous and unexpected changes. Process workers may start executing a process differently in order to adjust to changes in workload, season, guidelines or regulations for example. Early detection of business process changes based on their event logs – also known as business process drift detection – enables analysts to identify and act upon changes that may otherwise affect process performance. Previous methods for business process drift detection are based on an exploration of a potentially large feature space and in some cases they require users to manually identify the specific features that characterize the drift. Depending on the explored feature set, these methods may miss certain types of changes. This paper proposes a fully automated and statistically grounded method for detecting process drift. The core idea is to perform statistical tests over the distributions of runs observed in two consecutive time windows. By adaptively sizing the window, the method strikes a trade-off between classification accuracy and drift detection delay. A validation on synthetic and real-life logs shows that the method accurately detects typical change patterns and scales up to the extent it is applicable for online drift detection.

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This paper addresses the problem of identifying and explaining behavioral differences between two business process event logs. The paper presents a method that, given two event logs, returns a set of statements in natural language capturing behavior that is present or frequent in one log, while absent or infrequent in the other. This log delta analysis method allows users to diagnose differences between normal and deviant executions of a process or between two versions or variants of a process. The method relies on a novel approach to losslessly encode an event log as an event structure, combined with a frequency-enhanced technique for differencing pairs of event structures. A validation of the proposed method shows that it accurately diagnoses typical change patterns and can explain differences between normal and deviant cases in a real-life log, more compactly and precisely than previously proposed methods.

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Many organizations realize that increasing amounts of data (“Big Data”) need to be dealt with intelligently in order to compete with other organizations in terms of efficiency, speed and services. The goal is not to collect as much data as possible, but to turn event data into valuable insights that can be used to improve business processes. However, data-oriented analysis approaches fail to relate event data to process models. At the same time, large organizations are generating piles of process models that are disconnected from the real processes and information systems. In this chapter we propose to manage large collections of process models and event data in an integrated manner. Observed and modeled behavior need to be continuously compared and aligned. This results in a “liquid” business process model collection, i.e. a collection of process models that is in sync with the actual organizational behavior. The collection should self-adapt to evolving organizational behavior and incorporate relevant execution data (e.g. process performance and resource utilization) extracted from the logs, thereby allowing insightful reports to be produced from factual organizational data.

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With the increasing competitiveness in global markets, many developing nations are striving to constantly improve their services in search for the next competitive edge. As a result, the demand and need for Business Process Management (BPM) in these regions is seeing a rapid rise. Yet there exists a lack of professional expertise and knowledge to cater to that need. Therefore, the development of well-structured BPM training/ education programs has become an urgent requirement for these industries. Furthermore, the lack of textbooks or other self-educating material, that go beyond the basics of BPM, further ratifies the need for case based teaching and related cases that enable the next generation of professionals in these countries. Teaching cases create an authentic learning environment where complexities and challenges of the ‘real world’ can be presented in a narrative, enabling students to evolve crucial skills such as problem analysis, problem solving, creativity within constraints as well as the application of appropriate tools (BPMN) and techniques (including best practices and benchmarking) within richer and real scenarios. The aim of this paper is to provide a comprehensive teaching case demonstrating the means to tackle any developing nation’s legacy government process undermined by inefficiency and ineffectiveness. The paper also includes thorough teaching notes The article is presented in three main parts: (i) Introduction - that provides a brief background setting the context of this paper, (ii) The Teaching Case, and (iii) Teaching notes.