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Abstract Field concept selection is a critical step in subsea field development, as decisions made during early phases strongly influence cost, schedule, and risk throughout the project lifecycle. However, this stage faces persistent challenges: limited data gathering, complex interdisciplinary interfaces, frequent changes in development strategy, multiple competing concepts to evaluate, and compressed timelines for optimization and decision-making. This often results in a restricted number of concepts screened and makes it difficult to maintain a system-level perspective across subsea production systems (SPS); subsea umbilicals, risers, and flowlines (SURF); and installation disciplines. The result is increased risk of late design changes, inefficient vessel utilization, and potential cost escalation during execution. The objective of this paper is to present case studies and the improvements achieved by applying a model driven system engineering methodology for concept selection, implemented through a collaborative digital platform. This approach integrates subsea engineering disciplines into a unified environment, enabling scenario evaluations, and real-time collaboration by replacing traditional trial-and-error workflows with model driven processes. Benchmarking against conventional methods demonstrates significant gains. Traditional workflows typically allow only two or three concepts to be evaluated end-to-end due to manual data transfers and fragmented tools. In contrast, the digital approach enables screening of different permutations within the same timeframe, leveraging parametric models and governed data libraries to accelerate derivative generation such as layouts, bills of material, and preliminary installation sequences. Engineering hours for repetitive tasks are reduced by up to 50%, freeing resources for higher-value analysis and optimization. Risks related to design and installation feasibility are mitigated earlier, reducing the likelihood of vessel delays and associated cost exposure. Furthermore, by consolidating multiple tools and interfaces into one governed workspace, the methodology simplifies cross-functional collaboration and enhances decision quality without extending field development. The continued application of this approach has proven that the use of a model driven system engineering methodology in early phases improved information flow and strengthened the decision-making process during field development. By incorporating cross-functional engineering when design changes are least expensive, the method supports smarter decisions and more robust architectures. Ultimately, this paper demonstrates how unifying disciplines into a single digital environment reduces complexity, accelerates early-phase development, and enables rapid, informed concept selection, delivering practical solutions beyond the limitations of traditional trial-and-error methods.