Model-Driven Strategy For Aligning Business Motivation With Enterprise Business Processes
Volume 4 - Issue 5, May 2020 Edition
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Author(s)
Joe Essien
Keywords
Alignment, ArchiMate, Business Process, Enterprise Architecture, Modelling, Organizational Goals
Abstract
As modelling of enterprise continues to influence the way many organisations represent their business strategies and technologies, there is a commensurate growth in knowledge base with resolute lessons gained. This is despite criticism that Enterprise Architecture development should have started by the elaboration of an agreed architecture representation language in order to avoid contemporary perilous proposals. Many practitioners argue that since the advent of Enterprise Architecture (EA), a lot of prominence has continually been placed distinctively on business process modelling and information technology infrastructure with less emphasis on alignment and formalisation. Approaches such as top-down and bottom-up have been proffered with fastidious ambience of best practises for EA development. Without an extensible and comprehensive alignment strategy, it is difficult for enterprise to evaluate the usefulness of architectures as complex architectures are intricate and difficult to understand by stakeholders. This paper explores the adoption of EA models as an effective strategy for aligning EA models with business constraints and goals. It presents an approach for categorization and modelling of EA artefacts with focus on motivation abstraction to alignment of business processes with organizational goals. The paper proposes and exemplifies methods that can segregate domain knowledge from the operational knowledge and facilitates the analysis of the domain structures through formalised decomposition and systematic integration by use of standard modelling notations of ArchiMate. This approach contrasts significantly with other common perspective such as the maturity matrices, balanced scorecard and reference models and espouses the use of interrogative constructs of EA models to confirm that the EA model meets the intrinsic goals defined by their motivation.
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