A Pattern-based Approach to Quantitative Enterprise Architecture Analysis

Enterprise Architecture (EA) management involves tasks that substantially contribute to the operations of an enterprise, and to its sustainable market presence. One important aspect of this is the availability of services to customers. However, the increasing interconnectedness of systems with other systems and with business processes makes it difficult to get a clear view on change impacts and dependency structures. While management level decision makers need this information to make sound decisions, EA models often do not include quality attributes (such as availability), and very rarely provide quantitative means to assess them. We address these shortcomings by augmenting an information model for EA modeling with concepts from Probabilistic Relational Models, thus enabling quantitative analysis. A sample business case is evaluated as an example of the technique, showing how decision makers can benefit from information on availability impacts on enterprise business services

Towards a classification framework for approaches to enterprise architecture analysis

Analysis is an important part of the Enterprise Architecture Management Process. Prior to decisions regarding transformation of the Enterprise Architecture, the current situation and the outcomes of alternative action plans have to be analyzed. Many analysis approaches have been proposed by researchers and current Enterprise Architecture Management tools implement Analysis functionalities. However, few work has been done structuring and classifying Enterprise Architecture Analysis approaches. This paper collects and extends existing classification schemes, presenting a framework for Enterprise Architecture Analysis classification. For evaluation, a collection of Enterprise Architecture Analysis approaches has been classified based on this framework. As a result, the description of these approaches has been assessed, a common set of important categories for Enterprise Architecture Analysis classification has been derived and suggestions for further development are drawn

On exposing strategic and structural mismatches between business and information systems: misalignment symptom detection based on enterprise architecture model analysis = Stratégiai és strukturális összehangolási zavarok feltárása az üzleti és informatikai területek között: összehangolási zavarok tüneteinek azonosítása vállalati architektúra modellek elemzésével

One of the most important issues on information systems (IS) research is the need to align business with information systems and information technology (IT). Since information systems facilitate the success of business strategies, the importance of business-IT (or strategic) alignment is unquestionable. While organisations address alignment achievement, they are continually suffering from misalignments. These difficulties (the misalignments) encumber the achievement of alignment, and lead us to the phenomenon of misalignment. This Ph.D. dissertation deals with the concept of misalignment, with special attention on enterprise architecture (EA)-based analytical potential. The main purpose of the proposed research is to analyse strategic misalignment between the business dimension and the information systems dimension. The problem of business-IT alignment is translated into the aspects of enterprise architecture. The study aims to accomplish an EA-based, systematic analysis of mismatches between business and information systems

An Exploration of Enterprise Architecture Research

Management of the enterprise architecture has become increasingly recognized as a crucial part of both business and IT management. Still, a common understanding and methodological consistency seems far from being developed. Acknowledging the significant role of research in moving the development process along, this article employs different bibliometric methods, complemented by an extensive qualitative interpretation of the research field, to provide a unique overview of the enterprise architecture literature. After answering our research questions about the collaboration via co-authorships, the intellectual structure of the research field and its most influential works, and the principal themes of research, we propose an agenda for future research based on the findings from the above analyses and their comparison to empirical insights from the literature. In particular, our study finds a considerable degree of co-authorship clustering and a positive impact of the extent of co-authorship on the diffusion of works on enterprise architecture. In addition, this article identifies three major research streams and shows that research to date has revolved around specific themes, while some of high practical relevance receive minor attention. Hence, the contribution of our study is manifold and offers support for researchers and practitioners alike