System complexity, and its evaluation, poses several challenges to any organization hoping to engineer systems operating in a System-of-Systems (SoS) context. Here, we analyse one particular industrial complexity evaluation decision support tool that has been in use for several years across a variety of engineering projects, with the aim of better understanding and overcoming a particular subset of these challenges. While improvements to the tool itself (such as making SoS considerations explicit, or employing structured communications techniques to improve elicitation) are a legitimate line of enquiry, the focus of the current paper is the set of issues relating to the wider organizational context within which any such tool needs to be embedded.Here we characterise this context in terms of a complexity evaluation framework, and, based on the case study analysis, argue for a set of key framework features; collaborative effort towards building a shared understanding of contextually relevant complexity factors, iterative complexity (re-)evaluation over the course of a project, and progressive refinement of complexity evaluation tools and processes through linking these to project outcomes in the form of 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, and, relatedly, the feasibility of collecting sufficient empirical evidence to conduct cost-benefit analyses of the impact of complexity evaluation.
|Title of host publication||2019 International Symposium on Systems Engineering (ISSE)|
|Publication status||E-pub ahead of print - 6 Feb 2020|
Potts, M. W., Sartor, P. N., Johnson, A., & Bullock, S. (2020). Deriving Key Features of a System-of-Systems Complexity Evaluation Framework from an Industrial Case Study Analysis. In 2019 International Symposium on Systems Engineering (ISSE) https://doi.org/10.1109/isse46696.2019.8984534