Lane Optimization Business Overview
Last updated: August 15, 2025
Lane (Origin to Destination Pairs) Aggregate Insights & Recommendations Surrounding Performance & Risk of Completed Shipments

The Problem:
Visibility alone is not enough.
Control Towers lack business context and organizational lane data required to make intelligent and timely decisions leading to lane optimization.
Aggregating data from multiple platforms and comparing to organizational standards is expensive and time consuming.
External events impacting lane performance may not be communicated, or it may be manual and time consuming to understand which routes, stops, or segments may be impacted.
IoT data can be complicated and time consuming to analyze by development teams, leading to long development times for analytics
Lane Analytical tools that do exist lack to the ability to drill from lane level, to route level, to shipments level - making investigating root cause a difficult time consuming task.
Features:
Features: | Details: |
All Lanes View |
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Athena Summary |
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Lane Perfomance Metrics |
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Lane External Impact Metrics |
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Lane Device Performance Metrics |
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Lane CO2 Emissions Metrics |
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Lane Packaging Performance Metrics |
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All Routes View |
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Verified Route Badge |
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Route Details |
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Shipment View |
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π Lane Optimization Overview & User Guide
Value:
Aggregate Insights and instant tradeoff decisions to drive savings.
Continuous monitoring of lane performance across origin β destination pairs (lanes)
Aggregated performance and risk scoring of LSPs, packages, waypoints, routes, IoT (active & passive) & milestone
ATHENA enabled insights to summarize origin β destination pair (lane) andΒ route performance with hyper-contextualized ML and AI-generated recommendations taking into consideration historical performance and external risk factors.
Compare and review historical lane risk and performance. by routes taken to unlock network optimization opportunities.
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