16 research outputs found

    An enterprise engineering approach for the alignment of business and information technology strategy

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    Information systems and information technology (IS/IT, hereafter just IT) strategies usually depend on a business strategy. The alignment of both strategies improves their strategic plans. From an external perspective, business and IT alignment is the extent to which the IT strategy enables and drives the business strategy. This article reviews strategic alignment between business and IT, and proposes the use of enterprise engineering (EE) to achieve this alignment. The EE approach facilitates the definition of a formal dialog in the alignment design. In relation to this, new building blocks and life-cycle phases have been defined for their use in an enterprise architecture context. This proposal has been adopted in a critical process of a ceramic tile company for the purpose of aligning a strategic business plan and IT strategy, which are essential to support this process. © 2011 Taylor & Francis.Cuenca, L.; Boza, A.; Ortiz, A. (2011). 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    Consonant duration and degemination in Dutch. At the interface of phonetics and phonology

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    An Empirical Evaluation of Design Decision Concepts in Enterprise Architecture

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    Part 2: Quality of Enterprise ModelsInternational audienceEnterprise Architecture (EA) languages describe the design of an enterprise holistically, typically linking products and services to supporting business processes and, in turn, business processes to their supporting IT systems. In earlier work, we introduced EA Anamnesis, which provides an approach and corresponding meta-model for rationalizing architectural designs. EA Anamnesis captures the motivations of design decisions in enterprise architecture, alternative designs, design criteria, observed impacts of a design decision, and more. We argued that EA Anamnesis nicely complements current architectural languages by providing the capability to learn from past decision making.In this paper, we provide a first empirical grounding for the practical usefulness of EA Anamnesis. Using a survey amongst 35 enterprise architecture practitioners, we test the perceived usefulness of EA Anamnesis concepts, and compare this to their current uptake in practice. Results indicate that while many EA Anamnesis concepts are perceived as useful, the current uptake in practice is limited to a few concepts - prominently ‘rationale’ and ‘layer’. Our results go on and show that architects currently rationalize architectural decisions in an ad hoc manner, forgoing structured templates such as provided by EA Anamnesis. Finally, we interpret the survey results discussing for example possible reasons for the gap between perceived usefulness and uptake of architectural rationalization

    Overcoming implementation challenges in enterprise architecture management: a design theory for architecture-driven IT Management (ADRIMA)

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    Enterprise architecture management (EAM) is acknowledged as a discipline to drive organizational change, to improve IT landscapes' transparency, and to align business and IT. Despite its increasing popularity in practice, many EAM initiatives are confronted with substantial challenges, as demonstrated by the low usage level of enterprise architecture (EA) documentation and enterprise architects' lack of authority, and often fail. This motivates our research, which aims at developing a design theory that may guide organizations to successfully implement EAM. Based on three field studies, we first analyze the issues that arise when implementing EAM in practice. We find that EAM often suffers from being regarded as a separate and parallel initiative, although it needs to be embedded in established management processes and organization. We then suggest a design theory for architecture-driven IT management (ADRIMA) that synthesizes prescriptive knowledge related to embedding EAM practices, artifacts, and roles in the existing IT management processes and organization. By consolidating both IT management and EAM perspectives, our research goes beyond existing EA literature and EA frameworks which describe EAM as a stand-alone management concept focusing on EA models and the EA life cycle
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