Complexity Levels of Representing Dynamics in EA Planning

Abstract. Enterprise Architecture (EA) models provide information on the fundamental as-is structure of a company or governmental agency and thus serve as an informational basis for informed decisions in enterprise transformation projects. At the same time EA models provide a means to develop and visualize to-be states in the EA planning process. Results of a literature review and implications from industry practices show that existing EA planning processes do not sufficiently cover dynamic aspects in EA planning. This paper conceptualizes seven levels of complexity for structuring EA planning dynamics by a system of interrelated as-is and to-be models. While level 1 represents the lowest complexity with non-connected as-is and to-be models, level 7 covers a multiperiod planning process also taking plan deviations during transformation phases into account. Based on these complexity levels, a multi-stage evolution of EA planning processes is proposed which develops non-dynamic as-is EA modeling into full-scale EA planning

Where We Are With Enterprise Architecture

Enterprise architecture has been continuously developing since the mid-1980s. Although there is now 35 years of research and use, there is still a lack consistent definitions and standards. This is apparent in the proliferation of so many different enterprise architecture frameworks. Despite the significant body of research, there is a need for standardization of terminology based upon a meta-analysis of the literature. Enterprise architecture programs require commitment throughout an organization to be effective and must be perceived to add value. This research offers an initial basis for researchers who need to expand and continue this research topic with an actual meta-analysis, and for practitioners who would like to use an efficient method for EA projects

Assessing the Complexity of Dynamics in Enterprise Architecture Planning – Lessons from Chaos Theory

Enterprise Architecture (EA) models capture the fundamental elements of organizations and their relationships to serve documentation, analysis and planning purposes. As the elements and their relationships change over time, EA planning becomes increasingly complex. An analysis of existing methods shows that the complexity of dynamics is not sufficiently addressed. We argue that a sophisticated understanding of the complexity matter is prerequisite for EA planning method construction. As Chaos Theory (CT) is deployed in natural and social sciences—as well as in different contexts of IS research—to describe and understand the behavior of complex systems over time, we use properties of CT to assess the complexity of dynamics in EA planning and to derive requirements for EA planning methods. Our findings emphasize the importance of initial conditions of the architecture for EA planning and the need to harmonize planning granularities in order to achieve predictable results

Exploring Enterprise Transformation from a Path Dependence Perspective: A Recycling Case and Conceptual Model

In dispersed, multinational enterprises, complex integrations of information systems are a commonly hated threat as they render difficult fundamental changes of IT structures and standards embedded therein. This paper explores how integrations can turn into a burden and how thereby a company\u27s technology platform can lock-in to a local optimum. We conceptualize information system architectures - a company\u27s set of information systems and integrations - as networks. Based thereupon, we suggest a network model of path building that formalizes architectural growth processes and on-top technology adoptions, as when new systems attach preferentially to important hubs. Agent-based simulations give insights into how different growth parameters, i.e. new systems\u27 degree of integration and preferentiality, increase the architecture\u27s complexity and can reinforce predominant architectural patterns, such as islands of shared technologies . We contrast the simulation results to empirical data that show the emergence of a fragmented IT landscape in a regionally-dispersed recycling company

Enterprise Architecture Planning: Analyses of Requirements from Practice and Research

Enterprise architecture management (EAM) has become an increasingly important topic in practice due to the growing complexity of organizations and their underlying IT. While there is a strong interest in Enterprise Architecture (EA) modeling, evaluation, and frameworks, a lack of knowledge remains in the research field of EA planning. We conducted a series of expert interviews on the topic of EA planning. From these interviews we were able to extract requirements for EA planning from practice as the foundation of our analyses. Additionally, we conducted a structured literature review to elicit requirements for EA planning from a research perspective. This paper combines the results of both the practitioner interviews and the literature review to emphasize the gaps between the two worlds. As a result, we identified that current research does not adequately address the pressing problems of EA planning in practice

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