Analytics-Enabled Adaptive Business Architecture Modeling

Shreya Srinivas, Asif Qumer Gill, Terry Roach

Abstract


In a changing competitive business landscape, organizations are challenged by traditional processes and static document-driven business architecture models or artifacts. This marks the need for a more adaptive and analytics-enabled approach to business architecture. This article proposes a framework for adaptive business architecture modeling to address this critical concern. This research is conducted in an Australian business architecture organization using the action design research (ADR) method. The applicability of the proposed approach was demonstrated through its use in a health insurance business architecture case study using the Tableau and Jalapeno business architecture modeling platform. The proposed approach seems feasible to process business architecture data for generating essential insights and actions for adaptation.

Keywords:

Enterprise Architecture; Business Architecture; Analytics; Data Gap Analysis; Adaptive Architecture

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DOI: 10.7250/csimq.2020-23.03

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