Late Delivery
A late delivery occurs when freight arrives at the consignee's facility after the scheduled delivery date or outside the confirmed appointment window. It's one of the most common and most consequential exceptions in freight logistics – and one of the primary metrics shippers are measured on by their customers. Whether you're delivering to a retail distribution center with a two-hour appointment window or a restaurant chain expecting ingredients for tomorrow's menu, late means late, and the consequences are rarely forgiving.
Late deliveries stem from a wide range of causes: carrier transit delays due to weather, traffic, or breakdowns; missed pickups that push the entire timeline back; driver hours-of-service limits that force unplanned rest stops; dock congestion at origin or intermediate facilities; and inaccurate ETAs that masked the delay until it was too late to correct. The cascading nature of late deliveries makes them particularly expensive – a load that misses its delivery appointment may not get a new window until the next day, which means additional detention charges, an extra night of driver pay, and potentially a full day of delay for the end customer.
For shippers serving major retailers, late deliveries directly impact OTIF (On-Time In-Full) scores, which many retailers tie to vendor compliance programs with financial penalties. Walmart's OTIF program, for example, has been a defining force in how CPG shippers manage delivery performance. Beyond retail, late deliveries erode customer trust, increase inbound calls to customer service teams, and force reactive scrambling that pulls logistics coordinators away from planned optimization work. The most effective mitigation strategy is early detection – monitoring in-transit shipments against delivery windows and flagging loads that are trending late while there's still time to expedite, reroute, or at minimum notify the customer proactively.
Owlery monitors every shipment against its delivery window and triggers configurable delay alerts – so your team knows a load is trending late hours before the appointment, not after the customer calls to complain.
