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Analytics · Freight Forwarders

On-time in-full performance analytics

A 3PL measured OTIF by lane, carrier, and customer to see where service was failing and why.

Microsoft FabricPower BIAzure SQLDAX measures
OTIF
+9 pts
illustrative
Definition
Single
agreed
Miss cause
Attributed
per shipment
Scope
All lanes
and customers

Illustrative scenario · example figures

The challenge

Customers measured OTIF their own way and the 3PL had no matching view, so service disputes came down to whose spreadsheet to believe.

What we built

We defined OTIF consistently over shipment and delivery data and built a model that attributes every miss to a cause, by lane, carrier, and customer.

  • One OTIF definition applied across lanes and customers.
  • Miss attribution by cause: late, short, or both.
  • Carrier and lane performance ranked and trended.

Outcomes

  • Service conversations run on one agreed number.
  • The causes of failure are named instead of argued.
  • Carriers and lanes are managed on evidence.

Where the data came from

TMSCarrier EDICustomer delivery requirementsWMS

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

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