Abstract

AbstractHow should organizations approach the evaluation of system complexity at the early stages of system design in order to inform decision making? Since system complexity can be understood and approached in several different ways, such evaluation is challenging. In this study, we define the term “system complexity factors” to refer to a range of different aspects of system complexity that may contribute differentially to systems engineering outcomes. Views on the absolute and relative importance of these factors for early–life cycle system evaluation are collected and analyzed using a qualitative questionnaire of International Council on Systems Engineers (INCOSE) members (n = 55). We identified and described the following trends in the data: there is little between‐participant agreement on the relative importance of system complexity factors, even for participants with a shared background and role; participants tend to be internally consistent in their ratings of the relative importance of system complexity factors. Given the lack of alignment on the relative importance of system complexity factors, we argue that successful evaluation of system complexity can be better ensured by explicit determination and discussion of the (possibly implicit) perspective(s) on system complexity that are being taken.

Highlights

  • Organizations are increasingly having to engineer complex systems to meet the needs of a connected world.[1]

  • Organizations that can effectively evaluate the complexity of their candidate systems early in their life cycle will stand a greater chance of successfully delivering such systems

  • An effective evaluation can usefully inform important operational and technical decisions, such as what is an appropriate architecture for the proposed system, who are the key stakeholders, what are the key risks and how can they be mitigated, should we even proceed with the project? since system complexity can be understood and approached in several different ways, such evaluation is challenging.[9,10]

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Summary

Introduction

Organizations are increasingly having to engineer complex systems to meet the needs of a connected world.[1] There are several challenges inherent in engineering novel complex systems; such systems are generally made up of a large number of diverse, interdependent subsystems and components, interconnected via nonlinear relationships, leading to difficulties in predicting overall system performance.[2,3,4,5,6,7,8] System complexity has been shown to negatively affect system delivery project outcomes.[2] organizations that can effectively evaluate the complexity of their candidate systems early in their life cycle will stand a greater chance of successfully delivering such systems. An effective evaluation can usefully inform important operational and technical decisions, such as what is an appropriate architecture for the proposed system, who are the key stakeholders, what are the key risks and how can they be mitigated, should we even proceed with the project? Since system complexity can be understood and approached in several different ways, such evaluation is challenging.[9,10]. An effective evaluation can usefully inform important operational and technical decisions, such as what is an appropriate architecture for the proposed system, who are the key stakeholders, what are the key risks and how can they be mitigated, should we even proceed with the project? since system complexity can be understood and approached in several different ways, such evaluation is challenging.[9,10]

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