AI System for Preparing Delivery Delay Explanations

The problem

In day-to-day operations, teams may assume that a delay has a single cause. When plans, warehouse departures, GPS, traffic, vehicle events, deliveries and customer communication records are scattered across sensors, documents, field records or team files, issues may not become visible in time.

This fragmented data delays preparation of the delay explanation draft and forces teams to search manually for supporting evidence again. The transport operations manager must complete missing records and verify each conflict before making a decision.

A common exception is that several simultaneous factors may contribute to a delay. Incomplete or incorrect automation that fails to check this context could attribute responsibility to the wrong party, so no physical or operational action can be carried out directly.

What we set out to improve

• Proportion of explanation drafts corrected by operations
• Proportion of outputs corrected or rejected by the transport operations manager
• Time between the source event and the review output

How the system works

1. 01 Define the review scope and the role of the authorised transport operations manager
2. 02 Retrieve the inputs: plans, warehouse departures, GPS, traffic, vehicle events, deliveries and customer communication records
3. 03 Check source identity, date, calibration or version, and data recency
4. 04 Arrange the events chronologically
5. 05 Link deviations from the plan to source records
6. 06 Check for exceptions: several simultaneous factors may contribute to a delay
7. 07 Place low-confidence or conflicting records in a separate specialist queue
8. 08 Write the source identity, rule, output and timestamp to the audit trail
9. 09 Have the transport operations manager approve, correct, defer or reject the output

Methods we used

• A source-linked event chronology without attributing fault
• Source, format, timing and required-field checks for plans, warehouse departures, GPS, traffic, vehicle events, deliveries and customer communication records
• A missing-data warning instead of an estimate when inputs are incomplete or conflicting
• A separate exception check outside the main rule
• Combined retention of the source, rule result, delay explanation draft and human decision

Where people stay involved

Data and security

Access to plans, warehouse departures, GPS, traffic, vehicle events, deliveries and customer communication records is restricted to the minimum permissions required for the task. Commercial, location and employee information is masked where possible, and only the necessary portion of the dataset is sent to the model. Access, outputs and the transport operations manager's decision are logged; production use does not begin until the organisation has approved the retention period and data location.

Who this suits

Frequently asked questions