This dissertation discusses how organizations can use enterprise architecture (EA) artifacts to adapt to the rapidly changing digital landscape. EA artifacts are documents that communicate decisions, diagnostics, and facts about an organization’s current, transitions, and future states to improve the alignment between business and information technology (IT) stakeholders. Moreover, the EA is the organizing logic of people, processes, data, and technology. We emphasize the importance of dynamic capabilities, which enable organizations to adjust to market changes, and EA capability, which helps design and develop organizational architecture. Our research context concerns the relationship between EA approaches, specifically its documentation practices, digital transformation, and dynamic capabilities.
First, we delve into the role of EA artifacts in facilitating digital transformation within highly volatile and uncertain environments. We focus on identifying and understanding the specific EA artifacts and EA routines that can aid in the strategy planning process for digital transformations. A systematic literature review revealed fifteen EA artifacts. It distinguished three EA routines relevant to the strategy planning process for digital transformations. Additionally, our empirical findings from a multiple case study conducted in the financial services sector revealed additional EA artifacts and further enhanced our understanding of these artifacts.
We found that organizations in the financial services sector implement EA artifacts in a fragmented manner, with each organization adopting its unique approach. Only four of the theoretically conceptualized artifacts were found to be standard across all organizations, while two EA artifacts utilized by all case organizations were not initially included in the theoretical conceptualization. This highlights the need for further empirical research to understand EA artifacts and their practical implications comprehensively.
Moreover, we emphasize the increasing importance of leveraging digital capabilities and technologies to drive strategic initiatives and adapt to the complexities and advancements in the business environment. This underscores the role of EA in bridging the gap between strategic planning and implementation efforts and highlights the challenges and limitations in the existing understanding of how EA can contribute to creating business value for organizations.
Next, we delve into the critical role of EA information in advancing digital transformation within organizations. We emphasize the significance of leveraging knowledge about the arrangement of individuals, processes, data, and technology encapsulated in EA artifacts to drive digital transformation strategies effectively. Furthermore, the text highlights the specific EA information components that drive the dynamic capability essential for successful digital transformations. It underlines the importance of utilizing this information to systematically anticipate and respond to changes to integrate new digital technologies in an increasingly complex business environment. We offer valuable insights that can aid decision-makers and enterprise architects in organizing the requisite information to propel dynamic capabilities for successful digital transformation endeavors.
Furthermore, we discuss the significance of EA artifacts for organizational performance and value creation within the context of EA. We outline a comprehensive model that aims to elucidate the impact of EA artifacts on EA value and organizational performance. We focus on the challenges that companies encounter in fully leveraging the potential value from EA, and we underline the need for a unified understanding of the role of EA artifacts in value creation from an EA capability.
Therefore, we present a model of EA artifact-enabled EA value, contributing to understanding the mechanisms, inhibitors, and success factors associated with EA value. Furthermore, we propose a research agenda that contains future research areas to help better understand the mechanisms and interrelatedness of EA practices in highly dynamic environments.
Finally, we focus on understanding how EA artifacts improve organizational performance in general, particularly during significant transformations such as adopting digital technologies. In an additional empirical study, we identified 17 different EA artifacts and 16 ways EA contributes to strategic renewal, leading to 16 distinct EA values. By examining the interrelatedness of these values, the research developed a model that illustrates how EA artifacts contribute to strategic renewal and ultimately enhance organizational performance.
Overall, we thoroughly investigated the role of EA artifacts in driving and facilitating digital transformations and their impact on value creation and organizational performance. We utilized dynamic capabilities as a theoretical framework to examine how EA artifacts enable strategic renewal and value creation for digital transformations. Our main findings addressed by four main research questions are as follows:
- The study developed a comprehensive framework of 17 EA artifacts and their routines for successfully implementing digital transformations, including sensing, seizing, and transforming capabilities. The framework was validated through a metaplan session and a multiple case study on financial services providers.
- It identified 19 distinct information components embedded within EA artifacts that drive the sensing, mobilizing, and transforming capabilities for digital transformations.
- The research developed an integrative model positioning EA artifacts in the context of EA value creation, highlighting pre-decision-making and post-decision-making
organizational values and success factors, approaches, and inhibitors related to EA practices. - Through a multiple case study, the study established a universal model illustrating the role of EA artifacts in improving organizational performance, emphasizing their contribution to preserving knowledge and enhancing insight, oversight, communication, and decision-making.
Altogether, this dissertation provides valuable insights into the significance of EA artifacts in the context of digital transformations and EA value creation.
Year published: 2024