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Designing systems for adaptability by means of architecture options

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  • Avner Engel
  • Tyson R. Browning

Abstract

The value of a system usually diminishes over its lifetime, but some systems depreciate more slowly than others. Diminished value is due partly to the increasing needs and wants of the system's stakeholders and partly to its decreasing capabilities relative to emerging alternatives. Thus, systems are replaced or upgraded at substantial cost and disruption. If a system is designed to be changed and upgraded easily, however, this adaptability may increase its lifetime value. How can adaptability be designed into a system so that it will provide increased value over its lifetime? This paper describes the problem and an approach to its mitigation, adopting the concept of real options from the field of economics, extending it to the field of systems architecture, and coining the term architecture options for this next‐generation method and the associated tools for design for adaptability. Architecture options provide a quantitative means of optimizing a system architecture to maximize its lifetime value. This paper provides two quantitative models to assess the value of architecture adaptability. First, we define three metrics—component adaptability factors, component option values, and interface cost factors—which are used in a static model to evaluate architecture adaptability during the design of new systems. Second, we enhance a dynamic model to evaluate architecture adaptability over the maintenance and upgrade lifetime of a system, formulating a Design for Dynamic Value (DDV) optimization model. We illustrate both models with quantitative examples and also discuss how to obtain the socio‐economic data required for each model. © 2008 Wiley Periodicals, Inc. Syst Eng

Suggested Citation

  • Avner Engel & Tyson R. Browning, 2008. "Designing systems for adaptability by means of architecture options," Systems Engineering, John Wiley & Sons, vol. 11(2), pages 125-146, June.
    • Handle: RePEc:wly:syseng:v:11:y:2008:i:2:p:125-146
    DOI: 10.1002/sys.20090
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    4. Avner Engel & Yoram Reich, 2015. "Advancing Architecture Options Theory: Six Industrial Case Studies," Systems Engineering, John Wiley & Sons, vol. 18(4), pages 396-414, July.
    5. Alessandro Golkar & Edward F. Crawley, 2014. "A Framework for Space Systems Architecture under Stakeholder Objectives Ambiguity," Systems Engineering, John Wiley & Sons, vol. 17(4), pages 479-502, December.
    6. Eun Suk Suh & Noemi Chiriac & Katja Hölttä‐Otto, 2015. "Seeing Complex System through Different Lenses: Impact of Decomposition Perspective on System Architecture Analysis," Systems Engineering, John Wiley & Sons, vol. 18(3), pages 229-240, May.
    7. Benedict Bender & Clementine Bertheau & Tim Körppen & Hannah Lauppe & Norbert Gronau, 2022. "A proposal for future data organization in enterprise systems—an analysis of established database approaches," Information Systems and e-Business Management, Springer, vol. 20(3), pages 441-494, September.
    8. Jan-jaap Moerman & Seppe van Heusden & Brigitte Matheussen & Alberto Martinetti, 2022. "Encouraging a Modal Shift to Passenger Railway Transportation: A Case Study in Adaptable Rolling Stock Interior Design," Sustainability, MDPI, vol. 14(15), pages 1-17, August.
    9. Sungchul Kim & Ronald Giachetti & Sangsung Park, 2018. "Real Options Analysis for Acquisition of New Technology: A Case Study of Korea K2 Tank’s Powerpack," Sustainability, MDPI, vol. 10(11), pages 1-18, October.
    10. Michel‐Alexandre Cardin & Mehdi Ranjbar‐Bourani & Richard de Neufville, 2015. "Improving the Lifecycle Performance of Engineering Projects with Flexible Strategies: Example of On‐Shore LNG Production Design," Systems Engineering, John Wiley & Sons, vol. 18(3), pages 253-268, May.
    11. Jessica Ryan & Shahram Sarkani & Thomas Mazzuchi, 2014. "Leveraging Variability Modeling Techniques for Architecture Trade Studies and Analysis," Systems Engineering, John Wiley & Sons, vol. 17(1), pages 10-25, March.

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