How we calculate PressurePoint Scores and what the data means.
The PressurePoint Score quantifies rate-increase vulnerability for a utility's residential customers by combining two core factors: the utility's effective rate and the fuel-weighted poverty rate of its service territory.
A higher score indicates greater regulatory exposure — customers are paying elevated rates in areas where more households both rely on that fuel for heating AND live below the federal poverty line. Scoring is fuel-specific: the same geographic area can have different electric and gas scores depending on which fuel the poor households use to heat their homes.
| Tier | Percentile Range | Interpretation |
|---|---|---|
| Most Exposed | Top 20% of cohort | Maximum regulatory exposure — high rates meet high poverty |
| At Risk | 60th–80th percentile | Significant exposure requiring proactive action |
| Watch List | 40th–60th percentile | Moderate exposure — defensible with demonstrated action |
| Defensible | Bottom 40% | Below-average regulatory exposure |
PressurePoint analyzes two parallel datasets:
For utilities that serve both fuels in the same territory (64 combination utilities, e.g., ConEd, BGE, PG&E), each fuel's score is calculated independently and displayed on a single utility page with a fuel toggle.
Excluded: Cooperatives, Retail Power Marketers, State-owned, Federal, Behind the Meter, Community Choice Aggregators, and Political Subdivisions. These categories are excluded because the tool's framing around rate-regulated customer relationships doesn't apply cleanly (853 electric utilities and 2 gas cooperatives excluded).
Utilities are grouped into six cohorts by ownership type and customer count. Ranking is done within each cohort, so an IOU Large score is not directly comparable to a Muni Small score in absolute terms.
The gas dataset has no Muni Major utilities (no municipal gas distributor meets the Major threshold); the JSON ships the key with an empty list to keep the frontend schema stable.
The estimated monthly residential bill is calculated from each utility's own reported revenue, sales, and customer count — so the bill reflects both the local rate and local consumption patterns (dense urban markets like ConEd have lower per-household consumption than high-AC Southern markets).
For utilities that report across multiple service types (bundled and delivery-only for electric; firm residential for gas), all filings are aggregated to produce a single utility-level figure per state. Gas consumption is reported in Mcf (thousand cubic feet); electric in kWh.
This is the single most important input to the score. We report a fuel-weighted, territory-weighted poverty rate derived from household-level Census microdata.
The poverty rate we report is not "all poor households in the area." It's the share of households in the territory that both:
This matters because a utility's real rate-case exposure comes from customers who must use that fuel. In a region where most poor households heat with propane or oil, a gas utility's score appropriately reflects a smaller at-risk population. In regions where gas-heating is dominant, gas-weighted poverty closely tracks overall poverty.
Poverty is computed from the actual geography a utility serves. The method varies by utility type:
(county occupied housing units) × (tract share of PUMA). Summed across all counties in the territory and divided by total weight. Result: a county-household-weighted mean of PUMA-level fuel-weighted poverty, scoped precisely to the utility's service area.Because PUMAs can differ substantially from surrounding regions, a utility's territory-weighted poverty can diverge sharply from broader geographic averages:
Percentage change in the utility's residential rate from 2019 to 2024. This trajectory metric highlights utilities facing accelerating regulatory exposure, even if their current score is moderate. Displayed-only — does not enter the pressure score formula.
The "vs national average" callouts on utility pages use customer-weighted means across all scored utilities in the relevant fuel dataset, not unweighted averages. This prevents a handful of tiny munis from dragging the reference figure in either direction.
Each utility is ranked against same-type peers (IOU or Municipal) within its state, providing local context for the national score.