Data coverage and latency are essential metrics for evaluating the reliability and timeliness of event-driven insights in supply chain operations. This article will explain these concepts, how they are measured, and their importance for optimizing logistics workflows.

What is Data Coverage?

Data Coverage refers to the percentage of records (containers) that have key events captured and reported. Key events include:

• Pickup at POL (Port of Loading)
• Gate in at POL
• Load at POL
• Depart at POL
• Arrive at POD (Port of Discharge)
• Unload at POD
• Gate out at POD
• Return at POD

A high coverage rate ensures that a greater proportion of shipments are tracked throughout the journey, providing a complete and reliable picture of logistics operations.

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If you’re looking for carrier-specific coverage per event, please refer to the carrier coverage by event/location section of our Knowledge Base article on Carrier tracking coverage.

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What is Data Latency?

Data Latency measures the timeliness of event updates, specifically the time delay (in hours) between when an actual event occurs and when the corresponding timestamp is provided to the user.

There are two key metrics for data latency:

1. Median Latency: The median time (in hours) it takes for an event to be reported after it occurs.