> ## Documentation Index > Fetch the complete documentation index at: https://docs.vortexiq.ai/llms.txt > Use this file to discover all available pages before exploring further. # Late Shipments, PostNord > Late Shipments for PostNord stores. Tracked live in Vortex IQ Nerve Centre. How to read it, why it matters, and how to act on it. **Metrics type:** [Key Metrics](/nerve-centre/overview#metrics-types-explained) • **Category:** [Shipping & Courier](/nerve-centre/connectors#connectors-by-type) ## 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](/nerve-centre/kpi-cards/postnord/on-time-delivery-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. | | | | ------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **What it counts** | `COUNT(shipments WHERE delivered_at > aim_delivery_date)` over the trailing 7 days. The `aim_delivery_date` comes from PostNord's per-service-code aim, the `delivered_at` from the parcel's delivery scan. | | **Why a count not just a rate** | Customer-service workload scales with the count, not the rate. A merchant going from 1,000 to 10,000 weekly parcels at constant 96 percent OTD goes from 40 late tickets/week to 400, the team needs proportional CS capacity. The rate hides that scaling story. | | **Delivery success criterion** | A delivery scan exists at the recipient's address (POD scan for home delivery, pickup-point arrival scan for MyPack Collect). Parcels still in transit when the aim date passes are NOT counted as late on this card; they're counted in [Exception Rate](/nerve-centre/kpi-cards/postnord/exception-rate) until they finally deliver, at which point they shift to this card. | | **On-time threshold** | Same day as the service-code aim date, in the destination country's local timezone. PostNord publishes per-service-code aim dates; the card uses whatever PostNord returns at label-print time. | | **Service level scope** | All tracked services (MyPack Home, MyPack Collect, Express, Cross-Border, International Tracked). Untracked letter-mail excluded. | | **Climate impact** | Late count is climate-sensitive. A typical Nordic winter (Dec to Feb) produces 1.5 to 2.5× the summer-baseline late count even at the same shipment volume. Annotate seasonally; the alert threshold of 5 percent triggers in winter on weather-driven volatility, not on operational degradation. | | **Returns / RTO** | Excluded (outbound only). Late returns are tracked separately on the [Returned to Sender](/nerve-centre/kpi-cards/postnord/returned-to-sender) card. | | **Refresh cadence** | Hourly. Late status is computed at scan time; a parcel scanned as delivered at 14:00 against an aim of 13:59 the same day flips to "late" within the next hour's update. | | **Time window** | `7D` (rolling 7 days). The shorter window than OTD's 30-day reflects the operational use, this card drives this-week's CS staffing and this-week's WISMO email volume. | | **Alert trigger** | `>5% of total`. Equivalent to \<95 percent OTD; the count framing surfaces the workload reality. | | **Roles** | owner, operations | ## 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. ## 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). | Window | Total PostNord shipments | Late shipments | Late rate | OTD rate equivalent | | ------------------------------------- | ------------------------ | -------------- | --------- | ------------------- | | 07 Mar to 13 Mar 26 (this card) | 2,420 | 108 | **4.5%** | 95.5% | | 14 Feb to 20 Feb 26 (snowstorm week) | 2,180 | 286 | 13.1% | 86.9% | | 11 Jul to 17 Jul 25 (summer baseline) | 2,560 | 64 | 2.5% | 97.5% | 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](/nerve-centre/kpi-cards/postnord/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. ## Sibling cards merchants should reference together | Card | Why pair it with Late Shipments | What the combination tells you | | --------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------- | ---------------------------------------------------------------------------------------------------- | | [OTD Rate](/nerve-centre/kpi-cards/postnord/on-time-delivery-rate) | The percentage view of the same data. | Use percentage for trend, count for workload. | | [Exception Rate](/nerve-centre/kpi-cards/postnord/exception-rate) | Pre-late signal. | Rising exception rate predicts a rising late count at 24 to 48 hours lag. | | [Failed Deliveries](/nerve-centre/kpi-cards/postnord/failed-deliveries) | Hard-failure subset. | Late-but-eventually-delivered (this card) is recoverable; failed delivery (peer) is not. | | [First-Attempt Delivery Rate](/nerve-centre/kpi-cards/postnord/first-attempt-delivery-rate) | First-attempt success. | Late count rising while first-attempt holding equals transit-time issue, not delivery-attempt issue. | | [Avg Transit (days)](/nerve-centre/kpi-cards/postnord/avg-transit) | Speed correlate. | Transit days creeping up predicts late count rising next week. | | [Open Claims](/nerve-centre/kpi-cards/postnord/open-claims) | Downstream. | Late count this week predicts open-claim volume in 14 to 21 days. | | Cross-connector: [`shopify.refund_rate`](/nerve-centre/kpi-cards/shopify/refund-rate), [`bigcommerce.bc_refund_rate`](/nerve-centre/bigcommerce/bc_refund_rate) | Customer-impact correlate. | A 100-late spike typically drives a 0.3 to 0.8 point refund-rate uptick at 14-day lag. | | Cross-connector: [`shopify.support_ticket_volume`](/nerve-centre/shopify/support_volume) | CS workload correlate. | Late count of N typically generates 1.0 to 1.4 N WISMO tickets over the following 7 days. | | Cross-connector: [`bring.bri_late_shipments_count`](/nerve-centre/kpi-cards/bring/late-shipments) | Adjacent Nordic carrier peer. | Compare carrier-mix late counts to inform carrier-portfolio decisions. | ## Reconciling against the vendor's own dashboard **Where to look in PostNord's own portal:** [PostNord Business Portal](https://portal.business.postnord.com) → **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](/nerve-centre/kpi-cards/postnord/on-time-delivery-rate) card; the count and rate use the same underlying population. **Why our number may legitimately differ from PostNord's report:** | Reason | Direction | Why | | -------------------------------------- | ---------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Time zone** | Boundary days off | Portal uses local TZ; card uses UTC. Day-boundary parcels can shift count by a handful. | | **Tracking-event ingestion lag** | Ours lower for "today" | 30-min to 4-hour lag on scan ingestion means recently-late parcels may not yet be in the count. | | **In-transit edge case** | Either | A parcel scanned as delivered at 23:55 local on the aim date, against an aim ending at 23:59 local, is on-time in the local view; if our UTC conversion bumps it past midnight the card flips it to late. Matters only for late-day deliveries. | | **Cross-border last-mile attribution** | Either | Cross-border consignments use destination-carrier scans; the destination-carrier's lag is independent of PostNord's, leading to brief count drift. | | **Excluded vs flagged** | Different | The card excludes parcels still in transit past their aim date from the *late count* (they're in [Exception Rate](/nerve-centre/kpi-cards/postnord/exception-rate)); the portal sometimes shows them in both views. | **Cross-connector reconciliation:** | Card | Expected relationship | Causes of legitimate divergence | | -------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------- | | [`shopify.support_ticket_volume`](/nerve-centre/shopify/support_volume), [`bigcommerce.bc_support_ticket_volume`](/nerve-centre/bigcommerce/bc_support_volume) | Late count drives WISMO ticket volume at 1.0× to 1.4× lag of 3 to 7 days. | Customer-side variability: some merchants get 0.5× per-late ticket rate, some 1.8×; depends on checkout-promised-date discipline. | | [`shopify.refund_rate`](/nerve-centre/kpi-cards/shopify/refund-rate) | Late count of N typically drives \~0.005×N refund requests at 14-day lag. | Refund rate has many drivers; this is one input. | | [`bring.bri_late_shipments_count`](/nerve-centre/kpi-cards/bring/late-shipments) | Adjacent carrier peer. | Different populations; the comparison informs carrier-mix decisions. | | [PostNord OTD Rate](/nerve-centre/kpi-cards/postnord/on-time-delivery-rate) | Identity: `late_count = (1 − OTD_rate) × total_shipments`. | The two should agree to 1 to 2 percent; larger gap is a data sync issue. | ## 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](/nerve-centre/kpi-cards/postnord/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](/nerve-centre/kpi-cards/postnord/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](/nerve-centre/kpi-cards/postnord/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. *** ### 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. 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