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Adaptive Enterprise Architecture: Complexity Metrics in a Mixed Evaluation Method

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Enterprise Information Systems (ICEIS 2021)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 455))

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Abstract

Classically, enterprises future is intertwined with the needs and demands of society. Nowadays, in addition to those two elements, challenges are becoming more and more numerous and unavoidable. Saying a few, global warming, social responsibilities, Covid 19, digital transformation… We are living in a new era that is highly volatile and unpredictable. We don’t have anymore the privilege to choose threats and opportunities that we want to adapt to. In fact adaptation becomes a necessity to survive in this highly competitive and dynamic environment. Factors coming from those challenges externally on top of internal ones can impact various parts of the enterprise in the form of changes. Thus, Adaptive Enterprise Architecture (EA) is leveraged to assist the continuous adaptation to the evolving transformation. On the other hand, one of the criteria of Adaptive EA is the ability to monitor and control the complexity of changes. In this paper, we suggest a mixed approach of EA complexity measurement based on quantitative and qualitative analysis. First, we begin with a recap of the criteria shaping our Adaptive Enterprise Architecture approach and we give an overview of the model that we worked on in previous work. Then we investigate related work about complexity and subjective measurement. Finally, we describe our mixed approach of assessment of complexity and we focus on the calculation of some objective and subjective metrics.

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Authors and Affiliations

  1. AlQualsadi Team, ENSIAS Mohammed V University in Rabat, Rabat, Morocco

    Wissal Daoudi, Karim Doumi & Laila Kjiri

Authors
  1. Wissal Daoudi
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  2. Karim Doumi
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  3. Laila Kjiri
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Correspondence to Wissal Daoudi .

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Editors and Affiliations

  1. Polytechnic Institute of Setúbal/INSTICC, Setúbal, Portugal

    Joaquim Filipe

  2. Warsaw University of Technology, Warsaw, Poland

    Michał Śmiałek

  3. George Mason University, Fairfax, VA, USA

    Alexander Brodsky

  4. MODESTE/ESEO, Angers, France

    Slimane Hammoudi

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Daoudi, W., Doumi, K., Kjiri, L. (2022). Adaptive Enterprise Architecture: Complexity Metrics in a Mixed Evaluation Method. In: Filipe, J., Śmiałek, M., Brodsky, A., Hammoudi, S. (eds) Enterprise Information Systems. ICEIS 2021. Lecture Notes in Business Information Processing, vol 455. Springer, Cham. https://doi.org/10.1007/978-3-031-08965-7_26

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  • DOI: https://doi.org/10.1007/978-3-031-08965-7_26

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