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Customer stories / Highway interchange

Highways
Acceleration

66% of lost time back from 2 of 16 bridges.

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66%
of the recovery
32%
of the effort
$50K
a day in compression costs
Use case
Acceleration
Models used
Schedule OptimizerPAD Prediction
The challenge

“Which structures should we accelerate first?”

Sixteen delayed bridges, with compression costing around $50K a day.

16
delayed bridges competing for recovery effort
The solution

From analysis to a clear decision

The team used Schedule Optimizer and PAD Prediction to get to the answer, with every result traceable to the schedule.

  1. Analyze: with Schedule Optimizer and PAD Prediction

    The analysis showed which structures held the most recoverable time.

The result

Targeting 2 of 16 structures delivered 66% of the recovery.

66%of the recovery32%of the effort$50Ka day in compression costs
Take it further

Ask it across every project, and run it on every update

The same acceleration analysis, available to every team. Shown here as examples, not part of this story’s results.

Most of the recovery, a third of the effort.

Effort
32%
Recovery
66%
Show your working

Every answer, explained

An answer is only useful if it holds up. Nodes & Links records the reasoning and model outputs behind every answer, so the team can see each step, check the math and share a recommendation that’s traceable.

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FAQ

Questions, answered.

About this customer story.

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