The Role of Enterprise Architecture as a Management Tool

Paredes-Gualtor, Joel; Moscoso-Zea, Oswaldo; Luján‐Mora, Sergio

doi:10.1109/inciscos.2018.00051

Cited by 4 publications

(4 citation statements)

References 8 publications

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“…To begin, the tools of enterprise architecture are difficult to use. EA technologies are notoriously difficult to learn because of their inherent complexity, making it challenging for enterprises to implement them [47,48]. This issue may be remedied with inventive solutions that streamline functionality while streamlining the user interface, making using EA goods more straightforward.…”

Section: Technology Challengesmentioning

confidence: 99%

“…Standardised tools are necessary for businesses that intend to implement Environmental Assessment frameworks and methodologies. Tools considered industry standards provide compatibility between different corporate systems [47,48]. This issue may be remedied by using standardised EA tools, increased industry cooperation, and the formulation of recommendations.…”

Section: Technology Challengesmentioning

confidence: 99%

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A Review of Enterprise Architecture for Strategic Performance Management in the Transportation Sector Digital Transformation

Said AlKharbush,

Zohdi Mahmoud,

Abu Bakar

2023

OIJI

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This paper reviews the use of Enterprise Architecture (EA) for strategic performance management in the transport sector's digital transformation, focusing on the Balanced Scorecard (BSC) theory. EA is essential for strategic planning and performance management in the transport industry, which is vital to the economy. The study analyses academic publications, industry reports, and case studies to assess EA's benefits, drawbacks, and novel solutions in transportation. The Balanced Scorecard framework, which measures and manages performance holistically, should be used to align EA projects. EA and the Balanced Scorecard theory may provide a solid foundation for strategic performance management in the transportation sector's digital transition. It aligns goals, objectives, and KPIs with strategic vision and mission. EA also helps identify important capabilities, processes, and IT systems to accomplish desired results. It also improves decision-making by offering an integrated perspective of the organisation's resources, capabilities, and dependencies. In the transportation industry, EA for strategic performance management faces obstacles, including imprecise communication, insufficient governance, and limited planning. Innovative solutions, including improved communication channels, stronger governance systems, and enhanced planning techniques, are recommended to tackle these issues. This review analysis sheds light on the transport sector's digital transition using EA and the Balanced Scorecard theory. It advises researchers, practitioners, and policymakers to use EA to improve performance management and maintain transportation industry growth.

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Section: Technology Challengesmentioning

confidence: 99%

Section: Technology Challengesmentioning

confidence: 99%

A Review of Enterprise Architecture for Strategic Performance Management in the Transportation Sector Digital Transformation

Said AlKharbush,

Zohdi Mahmoud,

Abu Bakar

2023

OIJI

View full text Add to dashboard Cite

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“…According to Mittmann [44], it is important to analyze the results of the implementation and operation of a service center through indicators. Such analysis is necessary, considering that, without the adoption of indicators, the analysis can become very subjective.…”

Section: Service Operation Indicatorsmentioning

confidence: 99%

“…Granulo and Tanovic [45] also highlighted the need to measure the processes of the Information Technology Infrastructure Library (ITIL) model, using the indicators defined by the library itself [45]. Thus, the authors proposed the use of a group of indicators used to measure the processes related to the operation of services, namely, incidents, problems, interaction, request fulfillment and access [44].…”

Section: Service Operation Indicatorsmentioning

confidence: 99%

A Model for the Definition, Prioritization and Optimization of Indicators

et al. 2022

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Context: The definition and prioritization of indicators is now a common reality and an integral part of the evolution of the strategic, technical and business processes of any organization, whether public or private. Purpose: This paper proposes a new model regarding the definition and prioritization of indicators. Herein, we also investigate the definition and prioritization models currently adopted by academia and industry, and analyze the context of the proposed strategies against the traditional view of indicator definition currently adopted. In addition, we conducted a survey with organizations that had well-defined indicator management processes, seeking to identify customer expectations with a new indicator management model proposed by this work. Method: To gather evidence, we defined a methodology that relates the literature review and an exploratory case study with the application of an experiment. Driven by a set of research questions, this methodology comprised four main phases: planning, literature review, experiment execution and documentation of results. The method used is supported by some techniques, such as design thinking, design sprint and the Cynefin framework. Results: The analysis of the results was carried out in two different ways: Through the verification of the achievement of specific objectives and through a questionnaire applied to assess the degrees of perception of all employees who participated in the work. Regarding the specific objectives, it is clear that most of the objectives were achieved. Regarding the applied questionnaire, it is clear that, although the collaborators did not have adequate knowledge regarding the conceptual and practical aspects of some approaches used in the proposed model, there was a general perception that the model, in fact, supported top management for decision making. For professionals, the proposed model has a restricted scope; that is, it does not serve all types of organizations. Conclusion: The model proposed in this work proved to be effective, considering that the indicators were defined, prioritized and optimized, with a focus on the user experience. As future work, we intend to expand the scope of the model’s performance, evaluating business indicators alongside IT indicators.

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