Municipal stormwater programs must rapidly characterize large networks despite funding, staffing, and data gaps. This presentation highlights how Nashville has evaluated various data collection and modeling strategies that both increase and decrease engineering funding needs, and examines how these strategies influence project identification and construction costs.. We evaluate three cost-scaling alternatives against a “full data” baseline to understand tradeoffs in accuracy, coverage, and decision usefulness: (1) Assumed Elevations - reducing model set-up efforts by importing known pipe and culvert locations into PCSWMM, assigning structure elevations from public LiDAR (since elevations are unknown), and assuming 3 ft of cover for pipes with known diameters; (2) Reduced Data Collection - focusing data collection effort on public infrastructure that is ≥24 inches by avoiding small private driveway culverts and prioritizing primary conveyances; and (3) Flow Monitoring and Calibration - deploying targeted, short-term flow monitoring at representative basins to ground-truth hydrographs and recalibrate parameters currently based on SCS Type II design distributions. Each cost-scaling alternative is compared using a capital-planning evaluation framework. Key factors include: drainage area and linear feet analyzed per dollar, consistency of level-of-service at critical nodes, changes in hotspot identification and CIP ranking, and accuracy of modeled flows where observations exist. The framework also considers risk from potential misclassification. This presentation will evaluate results that show where assumed pipe invert elevations are “good enough,” where excluding private culverts and smaller pipes creates blind spots, and how limited monitoring improves model reliability. Attendees will gain a practical decision matrix and implementation tips to scale citywide assessments while balancing costs, speed, and accuracy.