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Metrics type: Key Metrics • Category: Shipping & Courier

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At a glance

Absolute count of PostNord shipments delivered AFTER their service-code aim date in the trailing 7 days. The count behind OTD Rate’s percentage. A 95.7 percent OTD on 2,500 weekly parcels reads “fine”; the same OTD as 108 late deliveries reads “108 customer-service tickets in flight”. The percentage tells you about quality; the count tells you about workload.

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Calculation

Calculated automatically from your PostNord data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.

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Worked example

The Stockholm outdoor-apparel brand. Reading taken at 09:00 CET on 14 Mar 26 for the trailing 7 days (07 Mar to 13 Mar 26). What this tells the merchant:
  1. 108 late deliveries this week, alert at >5% (which is 121 late at this volume) is just clear. The team can absorb this; CS capacity is sized for 80 to 130 weekly late tickets.
  2. The 14 Feb week was the snowstorm spike. 286 late shipments, 4× the summer baseline. This is the kind of week that breaks CS workflows: WISMO ticket volume on Day 8 to Day 10 (when customers email) is roughly equal to the late-shipment count. 286 incoming WISMO tickets in a single week against a CS team sized for 100 means tickets sit in queue for 48 to 96 hours; customer satisfaction collapses.
  3. The summer baseline of 64 lates per 2,560 shipments (2.5 percent late, 97.5 percent OTD) is the achievable floor. Setting alert thresholds at “summer baseline + 50 percent” gives a more useful winter alert than the constant 5 percent threshold.
  4. The compounding workload. Each late shipment generates approximately 1.2 customer-service tickets (some customers email twice, some don’t email at all but lodge a complaint via review or social), 0.15 refund requests, and 0.4 reorder probability decline. 108 late shipments translates to ~130 tickets, ~16 refund requests, and ~43 customers less likely to reorder, roughly £3,000 of measurable revenue impact per 100 late shipments at this brand’s AOV and contribution margin.
  5. The “108 lates is fine but tickets are flooding” debug case. If late count is in healthy band but CS is overwhelmed, the cause is upstream of late delivery, often Exception Rate climbing (parcels stuck in transit-not-yet-late but customers worry about them) or warehouse-fulfilment delays (parcels labelled-not-shipped). The late-shipments count is the delivered-late signal, not the full anxious-customer signal.
  6. Recovery shape after weather events. After the 14 Feb snowstorm week (286 lates), the next week’s count was 142 (still elevated, recovery backlog draining); the week after was 96 (back near baseline). Plan CS capacity for a 2-week tail after major weather events.

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Sibling cards merchants should reference together

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Reconciling against the vendor’s own dashboard

Where to look in PostNord’s own portal: PostNord Business Portal → Reports → Service Performance, switch the view from “Rate” to “Count”. Filter to the trailing 7 days and outbound-only. The card’s headline count should agree with PostNord’s count to within 1 to 3 percent. Larger gaps trace to the same TZ / ingestion-lag / cross-border-attribution reasons documented on the OTD Rate card; the count and rate use the same underlying population. Why our number may legitimately differ from PostNord’s report: Cross-connector reconciliation:

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Known limitations / merchant FAQs

Why is the threshold 5 percent and not 3 percent? Calibrated against typical Nordic DTC volatility. 3 percent is achievable in summer baseline conditions; 5 percent is the realistic ceiling that accommodates winter weather and routine transit variability. Setting alerts at 3 percent produces 30+ percent false-positive rate during Nov to Feb. Tune in Settings → Alerts → PostNord Late Shipments if your operations expects tighter discipline (some Nordic merchants run 3 percent thresholds as service-level commitments to enterprise customers). My late count is high but my OTD rate looks fine. Which should I trust? Both, they tell different stories at different scales. OTD rate is a quality signal that’s stable across volume changes; late count is a workload signal that scales with shipment volume. A merchant going from 1,000 to 10,000 weekly parcels at constant 96 percent OTD has 10× the CS workload, which OTD’s percentage view hides. Use both: OTD for trend monitoring, late count for staffing decisions. How should I plan CS staffing against this card? Rule of thumb at typical Nordic DTC: each late shipment generates 1.0 to 1.4 customer-service tickets over the following 3 to 10 days, plus 0.10 to 0.15 refund requests, plus 0.30 to 0.45 eventual non-reorder probability. Capacity-plan CS for ~1.2× the card’s reading. For a brand running 100 weekly lates, plan ~120 weekly tickets of WISMO/late-related volume on top of baseline. Late count went up 4× during snowstorm week. Should we have done anything different? Three actions in retrospect: (1) Pre-emptive WISMO email to all in-transit parcels in affected zones acknowledging the weather delay; this typically reduces inbound ticket volume by 35 to 50 percent. (2) Bring or DSV failover for time-sensitive items shipped during the affected window. (3) Route halt for the worst-affected zones (e.g. Norrland during a major snowstorm) until the storm passes; the parcels arriving 5 days late from a halted route are worse than 5 days delayed dispatch. PostNord’s service-status feed publishes the zone codes; route on those. Does this card include cross-border lates differently? No, cross-border consignments count toward the same total. Cross-border has structurally higher late rates (typical 6 to 10 percent vs domestic 2 to 5 percent); if your shipment mix is cross-border-heavy, the headline rate runs higher. Use OTD by Route to separate domestic from cross-border for capacity planning. A late shipment finally delivered, does it stay in the late count? Yes, the count is “shipments that delivered after their aim date in the trailing 7 days”. Once delivered late, the shipment counts in the window; once it ages out of 7 days, it drops off. This is intentional: the count is the workload-trigger figure, and a parcel delivered 2 days late still triggers a WISMO ticket. What about parcels stuck in transit past their aim that haven’t been delivered yet? Not on this card. They’re tracked by Exception Rate until they finally deliver, at which point they shift to this card. Some merchants prefer a unified “late + stuck” view; that’s possible via the dashboard’s Stacked Panel feature, combining the two cards in the same panel. My count is consistently low (under 50) but the 7-day rate is high. Why? Volume. If you ship 600 weekly parcels, 50 lates is 8.3 percent rate, which is genuinely high. The 5 percent alert is a rate threshold, not a count threshold; small-volume merchants can trip it on absolute counts that look benign. The card surfaces the problem; the response is the same. Is there a per-country breakdown of the late count? Yes, via OTD by Route, which surfaces the rate per country / route. The headline late count on this card is the sum across countries; the breakdown lives on the OTD-by-route view. Does this card include MyPack Collect parcels that arrived at the pickup point on time but weren’t collected for days? The delivery scan for MyPack Collect is the pickup-point arrival, not the customer collection. So a parcel that arrived at the Pressbyrå on the aim date counts as on-time, even if the customer collected it 5 days later. This matches PostNord’s contractual definition; the customer-perception of “late collection” is a separate signal not tracked here.

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Tracked live in Vortex IQ Nerve Centre

Late Shipments is one of hundreds of KPI pulses Vortex IQ tracks across PostNord and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. Start for free or book a demo to see this metric running on your own data.