Forecast on real filings, not on vibes
Every rate component’s history, preserved and exportable, the raw material for budgets, trend analysis, and defensible rate forecasts.
The same job, two ways
Reconstructing history
Dig through utility archives → find superseded filings → hand-build a time series → hope you didn’t miss a mid-year change.
Query the archive
Pick the schedule and the date range → export the component time series → feed the model. Every change point carries its effective date.
Component history, ready for your model
Trace any component (energy, demand, riders) across years of filings in one query. Change points carry effective dates, so your series is exact, not interpolated.
- Component-level history, not averages
- Effective dates on every change point
- Excel (.xls) downloads for your models
How it runs
Select
Schedule, components, and date range.
Export
The exact time series with change points.
Model
Trend, regress, or scenario-test in your tools.
Refresh
Re-run on data that is updated continuously.
What you’ll use, in the portal or the API
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Common questions
How far back does history go?
Years of history. Depth varies by utility, and the archive keeps growing with every filing.
Is history normalized too?
Yes, the same component structure applies across the whole series, so models run without re-mapping.
Can forecasts refresh automatically?
Yes, pull history through the API; the underlying data is monitored daily and updated continuously.