Site Selection Scoring Tool
Compare North American cities for your next facility based on the factors that matter most. Select a facility type, customize scoring weights, and find your optimal location.
Step 1 β Select Facility Type
Select a City
Click on any city in the rankings to see its detailed breakdown and compare it against other locations.
Methodology & Scoring Framework
How we evaluate and rank cities for different facility types.
Weighted Multi-Criteria Scoring
Each city receives a raw score (0β100) across seven dimensions. The final composite score is a weighted sum, where the weights depend on the facility type selected. Different facility types have fundamentally different priorities β a data center cares most about energy cost and connectivity, while an R&D campus prioritizes talent density and cost of living.
Seven Evaluation Dimensions
| Dimension | Key Inputs |
|---|---|
| Energy & Power | Industrial electricity rates (EIA/NRCan data), grid reliability (SAIDI), renewable energy percentage, available power capacity |
| Talent & Workforce | STEM graduates per capita, tech job concentration (BLS/StatCan), university CS/engineering programs within 50mi, LinkedIn talent insights |
| Regulatory & Incentives | Average permitting timelines, corporate tax rates, available enterprise zones, state/provincial incentive programs |
| Connectivity & Broadband | Fiber penetration rate, 5G coverage, internet exchange proximity, average latency to top 10 metros |
| Climate & Hazard Risk | FEMA/NRC risk scores for flood, earthquake, hurricane, wildfire, extreme heat exposure days per year (inverted: lower risk = higher score) |
| Cost of Living & Real Estate | Commercial lease rates ($/sqft), COLI index, residential housing costs, industrial land availability |
| Logistics & Access | Airport connectivity score, interstate highway access, rail freight availability, drive-time to 50M+ population |
Default Weight Profiles by Facility Type
| Dimension | Data Center | R&D Campus | Mfg. | HQ/Office | Logistics |
|---|---|---|---|---|---|
| Energy | 28% | 5% | 22% | 4% | 8% |
| Talent | 8% | 32% | 15% | 25% | 8% |
| Regulatory | 15% | 10% | 18% | 10% | 12% |
| Connectivity | 25% | 12% | 8% | 15% | 10% |
| Climate Risk | 12% | 8% | 12% | 6% | 12% |
| Cost of Living | 4% | 18% | 8% | 22% | 10% |
| Logistics | 8% | 15% | 17% | 18% | 40% |
Worked Example
Consider evaluating Ashburn, VA for a Data Center:
Ashburn's exceptional connectivity score (98) heavily boosts its data center ranking, while its moderate energy cost (62) and high cost of living (42) slightly drag the composite down β though those dimensions carry less weight for data center use cases.
Fit Tier Definitions
| Tier | Score Range | Interpretation |
|---|---|---|
| Excellent Fit | 80β100 | Top-tier location with strong performance across all weighted dimensions |
| Strong Fit | 70β79 | Competitive location with minor trade-offs in one or two areas |
| Moderate Fit | 60β69 | Viable but with notable weaknesses that require mitigation strategies |
| Weak Fit | <60 | Significant challenges for this facility type; may still suit niche use cases |
Key Assumptions & Limitations
City-level aggregation: Scores represent metropolitan statistical areas (MSAs). Conditions can vary significantly within a metro β e.g., suburban Ashburn, VA vs. downtown Washington, DC.
Static snapshot: Data reflects conditions as of early 2025. Markets evolve rapidly β new incentive programs, infrastructure investments, and climate events can shift rankings.
Aggregate scoring: The weighted composite model is useful for initial shortlisting but cannot capture deal-specific variables like individual parcel availability, utility interconnection timelines, or negotiated incentive packages.
Cross-border comparison: US and Canadian cities are scored on the same scale, but regulatory and incentive structures differ fundamentally between countries. Direct numerical comparison should be supplemented with jurisdiction-specific analysis.
No micro-location data: This tool does not evaluate specific parcels, buildings, or real estate listings. It is designed for metro-level market screening prior to detailed site visits.
Data Sources & References
Energy: U.S. Energy Information Administration (EIA) state-level industrial electricity rates; Natural Resources Canada energy pricing data; LBNL grid reliability metrics (SAIDI/SAIFI).
Talent: U.S. Bureau of Labor Statistics (BLS) Occupational Employment and Wage Statistics; Statistics Canada Labour Force Survey; National Center for Education Statistics (NCES) STEM completions; LinkedIn Economic Graph data.
Regulatory: Tax Foundation state business tax climate index; KPMG competitive alternatives; state/provincial economic development agencies.
Connectivity: FCC broadband deployment data; CRTC Communications Monitoring Report; PeeringDB internet exchange data; Ookla Speedtest Intelligence.
Climate Risk: FEMA National Risk Index; Natural Resources Canada climate risk assessments; First Street Foundation flood and fire risk data.
Cost of Living: CBRE commercial real estate market reports; C2ER Cost of Living Index; Numbeo metro area comparisons.
Logistics: U.S. DOT Bureau of Transportation Statistics; Transport Canada; Airports Council International (ACI) connectivity rankings.