The Development of Competence in Applying Enterprise Architecture for Government Personnel

Abstract

Background and Objectives: The effective utilization of Enterprise Architecture (EA) is vital in enabling government organizations to align their digital technology strategies with organizational visions and operations. To achieve this, the development of competence among government personnel in applying EA is paramount. Recognizing the necessity, this study aims to both develop a competence framework and explore guidelines for enhancing the competency of government employees in leveraging EA. The core objective of this research is to define the knowledge, skills, and attributes required of individuals, and to provide structured recommendations for capacity building in this area.

Methodology: This study adopted a mixed methods approach. It employed a purposive sampling method, targeting individuals regarded as experts in EA analysis and design, as well as those specialized in curriculum research and development. Data collection tools included functional task analysis and expert opinion surveys, both geared toward evaluating the appropriateness of competence items and identifying potential pathways for competency enhancement. The research approach involved statistical processing of collected data to derive insights, employing measures such as mean value and standard deviation value to ensure reliability and interpretability of findings.

Main Results: This research categorizes the key competencies required for EA application into three primary domains: knowledge, skills, and personal attributes. Overall, nine key knowledge components, ten key skill areas, and seven key personal attributes form the foundation of competence in EA application. Additionally, the competency framework identifies three core functions understanding EA, analyzing and developing EA, and applying EA. Each core function comes with its own specific sub-units and elements of competence. Furthermore, the study outlines several effective strategies for personnel development, which include training sessions, workshops, mentoring or coaching, self-directed learning, and experiential or on-the-job learning initiatives.

Discussions: The competency framework underscores the significance of equipping government personnel with the ability to effectively utilize EA in drafting digital technology initiatives. Such initiatives are intended to align seamlessly with and support organizational strategies and visions. The findings highlight the interplay of educational interventions and practical applications as critical components in fostering overarching competency. This study emphasizes the importance of a structured training model where theoretical understanding is balanced with practical implementation. Moreover, it reflects the growing importance of initiatives aimed at professional development in response to technological advancements and the digital transformation needs of public sector entities.

Conclusions: This research confirms the necessity of developing a structured and detailed competency framework for government personnel to ensure the effective application of EA. By addressing knowledge, skills, and personal attributes and collectively, the framework provides a comprehensive pathway for capacity building. The recommended guidelines for holding trainings or workshops, coaching, self-learning, and learning on the job serve as practical interventions to achieve this goal. This study contributes to the broader discourse on public sector capability enhancement and sets the stage for further empirical research focused on optimizing EA related processes and applications in government sectors.