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Analytics · Customs Brokers

Entry throughput and clearance-time analytics

A customs broker measured entry volume, clearance time, and exceptions across the team to find where entries stalled.

Microsoft FabricPower BIAzure Data FactoryRow-level security
Clearance time
-22%
illustrative
Entries tracked
All
across ports
Exception reasons
Categorized
and trended
Operating view
Daily
for the team

Illustrative scenario · example figures

The challenge

Volume was growing but the broker could not see clearance time or where entries got stuck, so staffing and problem lanes were managed on instinct.

What we built

We pulled entry and status data from the filing system into a model that tracks throughput, clearance time, and exception reasons by team, client, and port.

  • Entry volume and clearance time by client, port, and filer.
  • Exception analysis by reason, with trend over time.
  • A daily operating view for the clearance team.

Outcomes

  • Clearance time is measured instead of estimated.
  • Problem ports and clients are visible and worked down.
  • Staffing follows real volume and complexity.

Where the data came from

Broker filing systemACE / ABIClient masterPort reference data

Data is drawn from the systems the operation already runs on and delivered in the client’s own tenant.

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