Abstract
Evaluating the complexity of an engineered system is challenging for any organization, even more so when operating in a System-of-Systems (SoS) context. Here, we analyse one particular decision support tool as an illustratory case study. This tool has been used for several years by Thales Group to evaluate system complexity across a variety of industrial engineering projects. The case study is informed by analysis of semi-structured interviews with systems engineering experts within Thales Group. This analysis reveals a number of positive and negative aspects of (i) the tool itself, and (ii) the way in which the tool is embedded operationally within the wider organization. While the first set of issues may be solved by making improvements to the tool itself, informed by further comparative analysis and growing literature on complexity evaluation, the second ``embedding challenge'' is distinct, seemingly receiving less attention in the literature.
In this paper we focus on addressing this embedding challenge, by introducing a complexity evaluation framework, designed according to a set of principles derived from the case study analysis; namely that any effective complexity evaluation activity should feature collaborative effort towards building an evaluation informed by a shared understanding of contextually relevant complexity factors, iterative (re-)evaluation over the course of a project, and progressive refinement of the complexity evaluation tools and processes themselves through linking project evaluations to project outcomes via a wider organizational learning cycle. The paper concludes by considering next steps including the challenge of assuring that such a framework is being implemented effectively.
In this paper we focus on addressing this embedding challenge, by introducing a complexity evaluation framework, designed according to a set of principles derived from the case study analysis; namely that any effective complexity evaluation activity should feature collaborative effort towards building an evaluation informed by a shared understanding of contextually relevant complexity factors, iterative (re-)evaluation over the course of a project, and progressive refinement of the complexity evaluation tools and processes themselves through linking project evaluations to project outcomes via a wider organizational learning cycle. The paper concludes by considering next steps including the challenge of assuring that such a framework is being implemented effectively.
Original language | English |
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Pages (from-to) | 707-723 |
Number of pages | 17 |
Journal | Systems Engineering |
Volume | 23 |
Issue number | 6 |
Early online date | 7 Sept 2020 |
DOIs | |
Publication status | Published - 6 Nov 2020 |
Keywords
- complexity science
- project planning/assessment/control
- risk and opportunity management
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Data from Study_How does complexity affect the successful engineering of systems throughout a system lifecycle
Bullock, S. (Creator) & Potts, M. (Creator), University of Bristol, 20 Jul 2020
DOI: 10.5523/bris.pji8xwa0q6ue27lcu8gp62k0q, http://data.bris.ac.uk/data/dataset/pji8xwa0q6ue27lcu8gp62k0q
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