How Find My Data Center evaluates and ranks data center development sites
Overview
Find My Data Center uses a weighted multi-dimensional scoring model to evaluate US land parcels for AI data center and neocloud development. Each site is scored across 8 dimensions with ~35 sub-dimensions total. Every sub-dimension is evaluated by a priority-based rule engine: rules are checked in order from best to worst, and the first matching ruledetermines the score. This "first-match-wins" approach produces deterministic, fully explainable scores. Each score includes the specific threshold that triggered it and a human-readable reasoning string.
The total site score is a weighted average of dimension scores. Dimension weights reflect importance to DC site viability and are configurable in Settings. Adjusting weights recomputes all scores in real-time.
Data Sources
Site data is aggregated from public and proprietary sources across federal, state, and local levels:
Power & Grid
EIA Forms 860/861, FERC 714, OASIS, utility tariff filings, PUC interconnection queues, ISO/RTO capacity reports, direct utility engagement
Environmental & Climate
FEMA NFHL flood maps, NOAA NCDC weather data (TMY3), US Drought Monitor (USDM), USGS seismic hazard maps, EPA databases, Phase I/II ESAs
Labor & Demographics
BLS Occupational Employment Statistics, Census ACS 5-Year, LEHD Origin-Destination, C2ER Cost of Living Index, National Right to Work Foundation
Regulatory & Incentives
State economic development agencies, county GIS/zoning, NEPA/CEQA registries, IDB/EDA filings, Board of Supervisors minutes, state PUC rulings
The engine reads each field from the database via its field_path (e.g. site_power.capacity_available_24mo_mw), evaluates it against threshold rules using operators like gte, lte, eq, and assigns the score from the first matching rule. Special handling extracts estimated_savings_per_mw from the JSON state_incentives field, and counts the existing_dc_operators_60mi JSON array length.
Dimension Weights (sum to 100)
35%
15%
15%
10%
8%
7%
Power Infrastructure (35%)
Behind-the-Meter (15%)
Regulatory & Permitting (15%)
Labor Supply (10%)
Water (8%)
Network & Fiber (7%)
Climate & Risk (5%)
Deal & Acquisition (5%)
Confidence Scoring
Each score carries a confidence rating (0-100%). Confidence is computed per-field: null/missing values = 0%, string values of "unknown" or empty = 25%, all other values = 85% (baseline from primary-source data). The dimension confidence is the weighted average of its sub-dimension confidences. Fields with no matched rule are excluded from the dimension score and reduce confidence proportionally.
Dimension Breakdown — Click any sub-dimension to see scoring thresholds
⚡
Power Infrastructure35%
Evaluates grid capacity, utility pricing, transmission access, and long-term power availability. This is the single most important factor for data center site selection.
🔋
Behind-the-Meter15%
Assesses opportunities for on-site or adjacent power generation including stranded gas, co-located renewables, and nuclear adjacency. BTM power can dramatically reduce operating costs.
📋
Regulatory & Permitting15%
Measures zoning readiness, state/county incentive packages, permitting timelines, and community opposition risk. Regulatory friction can add 12-24 months to a project.
👷
Labor Supply10%
Evaluates the local skilled labor pool including electricians, HVAC technicians, and IT professionals needed for construction and ongoing operations.
💧
Water8%
Assesses water availability, cost, drought risk, and permitting for cooling systems. Evaporative cooling consumes 300,000-500,000+ gallons per day for a large campus.
🌐
Network & Fiber7%
Evaluates dark fiber availability, provider diversity, peering proximity, and latency to major metros. Network connectivity determines which workloads a site can serve.
🌡️
Climate & Risk5%
Evaluates natural disaster risk profile, free cooling potential, and flood zone classification. Climate factors affect both CapEx (hardening) and OpEx (cooling costs).
🤝
Deal & Acquisition5%
Evaluates deal economics including price/acre relative to comps, seller motivation, broker relationships, and negotiation leverage.
Score Interpretation
80–100
Excellent
Top-tier site, minimal red flags
60–79
Good
Viable with manageable trade-offs
40–59
Fair
Significant issues to address
0–39
Poor
Major blockers, high risk
Notes & Limitations
•Dimension weights are configurable in Settings. Sub-dimension weights within each dimension always sum to 1.0 (100%). Dimension weights sum to 100 across all 8 dimensions.
•Scores are fully deterministic. The engine uses no ML or probabilistic models — every score traces back to a specific threshold rule in the configuration above.
•JSON fields get special extraction: state_incentives.estimated_savings_per_mw is parsed from the regulatory JSON, and existing_dc_operators_60mi is counted as array length (not raw value).
•Data freshness varies by source. Utility capacity is typically refreshed quarterly, FEMA maps update irregularly, BLS labor stats are annual. Scores should be validated with primary research before acquisition decisions.