Track late-delivery rates by route and customer group | AIGP
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Track late-delivery rates by route and customer group: Which missing metric most directly tests the observed

AIGP Understanding How to Govern AI Deployment and Use Easy

Uptime is a service metric; route- and group-specific late-delivery rates measure the deployment harm identified.

The question

A logistics company’s scheduling model meets its 98% uptime target, yet late deliveries have increased for rural routes. Other deployment prerequisites are satisfied. Which missing metric most directly tests the observed harm?

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  1. Compare average planning runtime across versions.
    Runtime comparison may identify efficiency changes, but it does not measure whether rural routes experience more harmful delivery outcomes.
  2. Review vendor incident reports alongside quarterly availability summaries.
    Those records may reveal operational events, but they do not directly quantify the route-specific delivery harm described.
  3. Track system uptime by month.
    Uptime measures availability, but the system is already meeting that target and the observed problem concerns delivery outcomes.
  4. Track late-delivery rates by route and customer group. ✓
    This outcome metric directly tests whether scheduling errors disproportionately affect rural routes or particular customer groups.
The trap
Match the metric to the observed harm, not merely to the system’s technical availability.

How to remember it

Uptime is a service metric; route- and group-specific late-delivery rates measure the deployment harm identified.

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