Enterprise Architecture (EA) is created, maintained, and managed through EA processes. While the quality of these processes is perceived to ultimately impact the realization of benefits from the EA approach, it has been considered in relatively few studies. Specific aspects of EA processes such as EA frameworks have been extensively studied, but there is no common understanding of the attributes that make up EA processes of high quality. In this exploratory case study, data from 14 themed interviews of EA stakeholders is utilized to identify 15 quality attributes for EA processes. These are then supplemented and validated by comparison to the hitherto existing state of research. The results provide a comprehensive framework for understanding EA process quality. They can be used to identify areas for development and define metrics for further improvement of the EA practice, and as a basis for further research.
This article proposes a Complex Adaptive Architecture (CAA) method to architect an organic enterprise. It presents a complicated concept in a simple 3×3 matrix bonded by three architecture theories and a three-tiered architecture approach. CAA recognizes that SOA and Cloud Computing is a horizontal architecture practice which cannot be accomplished with the traditional top-down approach. The horizontal architecture consists of the discipline of learning from the experience of others, the discipline of engineering of re-use and consolidation, and the discipline to facilitate buy-in from stakeholders. CAA also discovers that the business community is making decisions based on influence relation rather than structural relation. Coherence Architecture theory is based on enterprise influence modeling and coherence modeling for the purpose of supporting enterprise strategic planning and decision-making. The Coherence Architecture consists of the discipline of influence modeling and the discipline of analogical reasoning. CAA embraces continuous change with a three-tiered architecture approach. The initial tier is the Notional Architecture which serves much like a master plan in city planning. The second tier is the Segment Architecture to close the business performance gaps due to change. The third tier is the daily Enterprise Architecture (EA) to enable an agile solution architecture.
The discipline of Enterprise Architecture (EA) is still relatively immature and incoherent. The discourse is rather fragmented and lacking a shared vocabulary. To shed some light on the situation, some schools of thought on EA have been suggested, each with its distinct concerns and set of assumptions. In this article, we aim to bring more structure and clarity to EA discourse. Not only do we review the identified types and schools of EA, but we also attempt to make sense of the underlying structural and metaphysical underpinnings of the field and to ground EA in theory. As per our analysis, requisite architecture methods and tools are contingent on the level of complexity. In particular, while best practices and linear techniques are applicable in a contained operational scope, they fall severely short in addressing complex problems pertaining to non-linear discontinuities inherent in the increasingly interconnected and global business environment. On the other hand, we view that an ideal scope of an architecture “work system” is bounded by a maximum number of people able to create a shared meaning. Accordingly, we propose that architectural work in an enterprise be divided into three distinct yet interlinked architectures: Technical, Socio-Technical, and Ecosystemic. Each of these architectures is selfregulated, based on different ontological and epistemological assumptions, has its own vertical scope, and requires its own distinct methods and tools.
Enterprise Architecture (EA) is increasingly being adopted and utilized by all types of organizations (Fri 2007; Jung 2009; Kappelman et al. 2008). Despite its growing popularity, the challenge facing many organizations is how to measure and provide evidence of the value that EA provides to an enterprise (Boster et al. 2000; Plessius et al. 2012). This challenge includes determining the best ways to effectively evaluate and measure the impact EA has on an enterprise. To provide some insight into this problem, this article provides an overview of the means used to measure the value of EA within organizations. This article seeks to accomplish four tasks. First, to demonstrate that EA value measurement is a challenge that needs to be addressed within organizations. Second, to highlight the variety of methods and measures that organizations currently use in their attempts to measure the value of EA. Third, to provide insight into the reported challenges facing organizations involved in the process of measuring the value of EA. Fourth, to propose a conceptual model for EA value measurement that can be utilized by organizations who have implemented EA. To provide support and evidence for all four of these tasks, we present the results from a survey that contains the responses from 276 participants whose job roles and responsibilities directly reflected working in EA within their organizations.