6,115 research outputs found

    Business Capability Mining - Opportunities and Challenges

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    Business capability models are widely used in enterprise architecture management to generate an abstract overview of an organization’s business activities to reach its business objectives. The creation and maintenance of these models are associated with a huge manual workload. Research provides insights into opportunities for automated modeling of enterprise architecture models. However, most models address the application and technology layer and leave the business layer largely unexplored. Particularly, no research has been conducted on the automated generation of business capability models. This research paper uses 19 semi-structured expert interviews to identify possible automated modeling opportunities of business capabilities and related challenges and to jointly develop a business capability mining approach. This research benefit both, practice and research, by describing a situation-based business capability mining approach and identifying appropriate implementation scenarios

    Business Rules Management Solutions Problem Space: Situational Factors

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    Business rules management solutions are widely applied, standalone or in combination with business process management solutions. Yet scientific research on business rules management solutions is limited. The purpose of this paper is to define the business rules management solution problem space. Using contingency theory and relational theory as our lens, we conducted a qualitative study on 39 business rules management solutions. The range of data sources included interviews and document analysis. From the qualitative study six situational factors have been defined to classify the business rules management solution space: 1) value proposition, 2) approach, 3) standardization, 4) change frequency, 5) n-order compliance, and 6) integrative power of the software environment. The six factors can be clustered in three structures 1) deep structure, 2) physical structure and, 3) organizational structure. The classification of the problem space provides a framework for the analysis of business rules management solutions

    Organic transformation of ERP documentation practices: Moving from archival records to dialogue-based, agile throwaway documents

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    Implementing enterprise resource planning (ERP) systems remains challenging and requires organizational changes. Given the scale and complexity of ERP projects, documentation plays a crucial role in coordinating operational details. However, the emergence of the agile approach raises the question of how adequate lightweight documentation is in agile ERP implementation. Unfortunately, both academia and industry often overlook the natural evolution of documentation practices. This study examines current documentation practices through interviews with 23 field experts to address this oversight. The findings indicate a shift in documentation practices from retrospective approaches to dialogue-based, agile throwaway documents, including audiovisual recordings and informal emails. Project managers who extensively engage with throwaway documents demonstrate higher situational awareness and greater effectiveness in managing ERP projects than those who do not. The findings show an organic transformation of ERP documentation practices. We redefine documentation to include unstructured, relevant information across different media, emphasizing searchability. Additionally, the study offers two vignettes for diverse organizational contexts to illustrate the best practices of agile ERP projects.Organic transformation of ERP documentation practices: Moving from archival records to dialogue-based, agile throwaway documentspublishedVersionPaid open acces

    Automated Modeling with Abstraction for Enterprise Architecture (AMA4EA):Business Process Model Automation in an Industry 4.0 Laboratory

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    The transformation towards the Industry 4.0 paradigm requires companies to manage large amounts of data. This poses serious challenges with regard to how effectively to handle data and extract value from it. The state-of-the-art research of Enterprise Architecture (EA) provides limited knowledge on addressing this challenge. In this article, the Automated Modeling with Abstraction for Enterprise Architecture (AMA4EA) method is proposed and demonstrated. An abstraction hierarchy is introduced by AMA4EA to support companies to automatically abstract data from enterprise systems to concepts, then to automatically create an EA model. AMA4EA was demonstrated at an Industry 4.0 laboratory. The demonstration showed that AMA4EA could abstract detailed data from the Enterprise Resource Planning (ERP) system and Manufacturing Execution System (MES) to be relevant for a business process model that provided a useful and simplified visualization of production process data. The model communicated the detailed business data in an easily understandable way to stakeholders. AMA4EA is an innovative and novel method that contributes new knowledge to EA research. The demonstration provides sufficient evidence that AMA4EA is useful and applicable in the Industry 4.0 environment

    Application Access Control using Enterprise Models

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    In this paper a framework for a model-driven control of identity management systems is presented. An important issue in today\u27s information systems security discussion addresses the effective authorisation of users. With established conceptual modelling languages the assignment of roles to the identity management software is an enormous organisational effort. To decrease administration costs we propose a direct connection between the identity management system and enterprise models which contain the organisational responsibilities. Therefore, we have created the modelling approach EÂł+WS available for the meta-CASE tool cubetto toolset and the Novell Identity Manager

    Maintenance of Enterprise Architecture Models

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    Enterprise architecture (EA) models are tools of analysis, communication, and support towards enterprise transformation. These models need a suitable maintenance process to support comprehensive knowledge of the enterprise’s structure and dynamics. This study aims to identify and discuss the existing approaches to EA model maintenance published in the scientific literature. A systematic literature review was employed as the research method. A keyword-based search in six databases identified a total of 4495 papers in which 31 primary studies were included. A total of nine categories of EA model maintenance approaches were identified from both information systems and enterprise engineering fields of research. The increasing amount of research in EA model maintenance suggests that the topic still presents opportunities for research contributions. This study also proposes future lines of research according to the results identified in the theoretical corpus
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