CASE STUDY - FORTUNE 500 UTILITY
Knowing where the grid will actually break.
A Fortune 500 utility's forecast of storm outages, up to six days ahead. NEXUS built a solution in one week that beat the incumbent vendor forecast on accuracy at every horizon - so crews and equipment are staged where the grid will actually break.
The Task
Predict storm outage counts
Decision Enabled
Crew & equipment staging
Accuracy vs. Incumbent
85% vs 81%, built in a week
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Crews staged before the storm, not after
A Fortune 500 utility has to decide where to stage repair crews and materials before a storm arrives. It already relies on an outage forecast from an established vendor, delivered four times a day, up to six days ahead, company-wide and for each of its 13 service centers. The question: could NEXUS match that full scope and improve on its accuracy, quickly?
One week, the full forecasting scope
NEXUS's pre-trained foundation model identified outage signals in the utility's data, then was tested head to head against the forecast the utility uses today.
Same scope
Outages and customers out, company-wide and for each of 13 service centers, four times a day, same day to six days ahead.
Same rules
Only data available before each forecast was issued, so the backtest matches live use.
Same scoring
Scored on the same hold-out period, at the same issue times and horizons as the incumbent vendor forecast.
More accurate at every horizon, built in a week
Measured Outcome
85% vs 81%
company-wide outage forecast accuracy, issued at 18Z for the next day, with a solution built in one week
Measured Outcomes
0.79 vs. 0.74
accuracy six days out, where NEXUS's lead is widest (averaged across issue times). NEXUS holds close to its same-day accuracy of 0.85 across the whole week, giving planners a more dependable forecast further ahead
Accuracy is 1 minus the average percentage error; higher is better.
One week from raw data to a forecast ahead of the incumbent, on the same days, issue times and metric. NEXUS followed the actual outage curve more closely, month after month from February to July.
One week to value, with five more to follow.
The pipeline runs end to end - weather download, point-in-time checks, NEXUS, scoring - and can deliver the same daily forecast file at the four issue times, alongside the current one. Each new use case swaps the target and keeps the rest: restoration time per outage, which circuits fail next, substation peak load, daily gas demand, equipment failure risk.
