Methodology

The Georithm Resilience Method

A site decision you can't defend is a site decision you shouldn't sign. This is the complete method behind the Georithm Score — six weighted inputs, the datasets behind each one, and the arithmetic, written down so a reviewer can check it without our help.

Maintained by Jeremy Agoya, founder of Georithm.

The six weighted inputs

InputWeightSourceConfidence
Opportunity

Demand scale and growth balanced against how much of the market is already served.

30%US Census ACS 5-year estimates; Statistics Canada census releasesMeasured
Competition

Competitor density inside the trade-area radius. Lower saturation means more room to trade.

20%OpenStreetMap POI features, queried at report timeMeasured, coverage-dependent
Population growth

Annualised change in resident population across the most recent comparable periods.

15%US Census ACS; Statistics CanadaMeasured
Economic health

Spending-power proxy derived from market size, income and growth momentum.

15%US Census ACS income tables; Statistics CanadaModelled proxy
Climate & hazard risk

Exposure to flood, wildfire, earthquake and drought signals for the trade area.

10%Open-Meteo climate series and modelled hazard proxiesModelled proxy
Infrastructure

Density of the built environment and road network supporting trade and access.

10%OpenStreetMap; TomTom traffic flow (Professional and above)Measured

How to reproduce a score by hand

Each input is normalised to a 0–100 subscore, multiplied by its weight, and summed. There is no hidden term and no post-hoc adjustment.

score = 0.30 x opportunity
      + 0.20 x competition
      + 0.15 x population_growth
      + 0.15 x economic_health
      + 0.10 x hazard_risk
      + 0.10 x infrastructure

# rounded to the nearest integer, 0-100

Four standing commitments

Every figure names its source and its vintage

A number without a provenance tag is not evidence. Each input in a Georithm report shows which dataset it came from and which release year, so a reviewer can go to the source and check it.

Modelled inputs are labelled as modelled

Hazard exposure and spending-power are proxies, not insurer-grade or panel-grade measurements. They carry a confidence tag rather than being presented as observed fact.

The weights are published, not proprietary

The six weights above are the whole model. Take the input scores from any report, apply these weights, and you will reproduce the headline score to the same integer.

Stated limits, in the report itself

OpenStreetMap competitor coverage thins out in rural areas, ACS estimates lag by up to two years, and hazard scores are proxies. All three appear in the report, not just here.

See the method applied

The Georgetown, TX sample report shows this exact method on a real market: the map, the competitor list, the input subscores and the GO/NO-GO. No account needed.

Feedback