Ill-Structured Commercial Ship Design Problems: The Responsive System Comparison Method on an Offshore Vessel Case

In this paper, we address difficulties in ill-structured ship design problems. We focus on issues related to evaluation of commercial system performance, involving perceptions of value, risk, and time, to better understand trade-offs at the early design stages. Further, this paper presents a two-stakeholder offshore ship design problem. The Responsive Systems Comparison (RSC) method is applied to the case to untangle complexity, and to address how one can structure the problem of handling future contextual uncertainty to ensure value robustness. Focus is on alignment of business strategies of the two stakeholders with design decisions through exploration and evaluation of the design space. Uncertainties potentially jeopardizing the value propositions are explicitly considered using epoch-era analysis. The case study demonstrates the usefulness of the RSC method for structuring ill-structured design problems. 1. Introduction In a competitive maritime industry, there is a need to design, develop, and deliver systems able to sustain value throughout a multi-decade lifetime. However, design of ocean engineering systems remains a difficult task, mainly due to the complexity and uncertainty governing these systems and their sociotechnical contexts. Even a clear definition of what is a better ship is ambiguous (Ulstein & Brett 2015)—it all depends. Understanding the relation between business strategies and corresponding marine design decisions, is not straight forward, and the ship design task could be considered a wicked problem (Andrews 2012), or an ill-structured problem (Simon 1973). An ill-structured problem lacks a specified beginning and goal states, and the relation between these are unknown. More information must be gathered to enrich the problem definition and take informed decisions. A differentiation can hence be made between the problem of defining the problem to solve, and the problem of solving this problem. In this paper, we stress the importance of understanding both of these aspects when it comes to design of complex systems.