Amid global climate change challenges, the construction industry faces an urgent  transition from a linear production model to a Circular Economy (CE). Initiatives  and recommendations in Dutch transition roadmaps and literature predominantly  focus on ensuring a future circular built environment, while lacking concrete actions on leveraging the existing assets for reuse. Dutch CE roadmap timelines  and interventions are developed based on Material Flow Analysis (MFA) studies with highly uncertain data input, this uncertainty impacts either environment or  economy with inaccurate interventions on the CE-transition. Secondly, the Replacement & Renovation (R&R) task of civil structures poses a threat for the  industry due to the limitations of capital, contractor capacity, and material  resources required to facilitate this peak. There is currently a lack of centrally  stored high-quality physical asset data available at public organisations. This data is essential in effectively managing the decommissioning peak and reduces risk for reuse realization. Lastly, Asset Management (AM) is transitioning towards a 3D-centralised strategy in line with Building Information Modelling (BIM) and  digital twins, while existing assets are still in 2D with often incomplete and  fragmented data documentation. Consequently, a large data quality gap is forming between new and existing assets. This led to the research question: How can centrally stored, quantified, and visualised asset data of existing infrastructure impact the CE-transition, bridge R&R-task efficiency, and AM practices? An upgrade towards 3D-BIM is required for existing assets to bridge this data gap. In doing so, facilitate higher quality- and more accessible asset specific  information that can be used in reusability scanning and structural assessments,  material quantification for CE-transition roadmap accuracy, and numerous AM  benefits. The costs for upgrading the existing assets using manual modelling or  3D scanning technology are currently too large to justify. An opportunity was  identified for modelling 3D-BIM of existing beam & slab bridges from 2D drawings using a modular approach to Parametric Engineering, aiming to reduce the investment threshold, and accelerating the digitization transition. Preliminary testing executed by the author showed a potential for 50-80% reduction in modelling efforts compared to conventional modelling practices with a volume  accuracy of >97%. The prototype calls for further development, validation, and similar efforts for other infrastructure types. The tool also showed potential for 3D structural & reusability assessments, reinforcement approx., and ptioneering & circularity scoring for the design phase. To put the tool’s use in perspective, a roadmap towards 3D centralized AM and a reuse economy was developed for AM.