> ## 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, DHL InExpress > Late Shipments for DHL InExpress 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 DHL InExpress shipments that delivered after their carrier-promised date in the last 7 days. The angry-customer gauge: each unit on this card is one customer who didn't receive their parcel when you said they would. Companion metric to [On-Time Delivery Rate](/nerve-centre/kpi-cards/dhl-inexpress/on-time-delivery-rate), which measures the same population as a percentage. | | | | ------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **What it counts** | `COUNT(shipments WHERE actualDeliveryDate > estimatedDeliveryDate)` over a rolling 7 days. Closed shipments only, in-transit parcels are not counted until they deliver. | | **Delivery success criterion** | A POD scan timestamp greater than the DHL-issued `estimatedDeliveryDate`. No grace period. A POD at 18:01 on the promised date is on-time; 00:01 the following day is late by one count. | | **On-time threshold** | The per-shipment `estimatedDeliveryDate` from DHL's quote at label generation. Includes customs leg for cross-border traffic. | | **Returns / RTO** | Returned-to-sender shipments are NOT counted as late on this card, they never tried to deliver to the customer in time. They count instead on [Returned to Sender](/nerve-centre/kpi-cards/dhl-inexpress/returned-to-sender). | | **Service level scope** | All InExpress tiers pooled (Economy Select, Express Worldwide, InExpress Domestic). Each shipment is judged against its own promise. | | **Multi-carrier opacity** | The trunk leg is DHL but the final-mile carrier varies (Yodel, Evri, DPD, GLS). The card scores the customer-perceived outcome regardless of which sub-carrier handled the last mile; if you need to attribute, slice by [Shipments by Service](/nerve-centre/kpi-cards/dhl-inexpress/shipments-by-service). | | **Brexit / customs** | Customs-hold time is included in the transit clock. A UK to FR shipment quoted 72h that took 96h with 36h held at customs counts as one late shipment on this card. | | **Currency** | This card is unitless (count). Cost impact is on [Avg Shipping Cost](/nerve-centre/kpi-cards/dhl-inexpress/avg-shipping-cost). | | **Time window** | `7D` rolling. Daily numbers can be noisy on small volumes; the 7D rollup smooths spikes. | | **Alert trigger** | `>5% of total shipments` over the same 7-day window. A 4% miss is acceptable for InExpress; 6% is a structural problem. | | **Roles** | owner, operations | ## Calculation Calculated automatically from your DHL InExpress data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading. ## Worked example A UK homewares merchant shipping \~2,500 parcels per week via DHL InExpress, mostly to UK + IE + DE. Reading taken at 09:00 GMT on 12 Mar 26 for the trailing 7 days (06 Mar 26 to 12 Mar 26). | Lane | Shipments | Late | Late % | | ------------------------- | --------- | ------- | -------- | | GB → GB (domestic) | 1,180 | 24 | 2.0% | | GB → IE | 540 | 18 | 3.3% | | GB → DE | 460 | 56 | 12.2% | | GB → FR | 220 | 31 | 14.1% | | GB → other EU | 100 | 12 | 12.0% | | **All lanes (this card)** | **2,500** | **141** | **5.6%** | The card reads **141** with the percentage in parentheses **(5.6%)**. The alert at `>5% of total` is **tripped**. Five things to notice: 1. **141 means 141 customers got a slip-of-paper "where is my order" email.** That's roughly 30 to 50 support tickets at the brand's typical 25 to 35% complaint rate. Plan support-team capacity around the count, not the rate. 2. **Two cross-border lanes are doing all the damage.** GB to DE and GB to FR together account for 87 of the 141 late shipments (62%) on only 27% of volume. The cross-border-customs story dominates: the customs leg is the differentiator, and the [Customs Dwell Time by Lane](/nerve-centre/kpi-cards/dhl-inexpress/customs-dwell-time-by-lane) card will tell you which side (UK export filing or destination clearance) is dragging. 3. **The 7-day window catches issues 30D smooths over.** A burst of 60 late shipments on Tuesday 9 Mar (a customs-IT outage at Roissy, perhaps) is visible here; on the 30D card the same burst would barely move the needle. 4. **Compare to last week.** If last week's count was 88 (3.5%), this week's 141 is a +60% jump. That's the operational signal: investigate Tuesday 9 Mar specifically. Any sudden week-on-week jump >40% with the rate above 5% is worth a half-hour of root-cause work. 5. **141 / 2500 = 5.6%, but 1 - 0.943 = 5.7% on the OTD card.** Rounding artefact, the two are the same population. If they disagree by more than 0.5% the indices are out of sync; recheck period boundaries. ## Sibling cards merchants should reference together Late count is a volume number; it pairs naturally with the rate and the cause: | Card | Why pair it with Late Shipments | What the combination tells you | | ---------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------- | | [On-Time Delivery Rate](/nerve-centre/kpi-cards/dhl-inexpress/on-time-delivery-rate) | The same population expressed as a percentage. | Use the rate for trend tracking, the count for support-team capacity planning. They should always reconcile to within 1%. | | [Customs Dwell Time by Lane](/nerve-centre/kpi-cards/dhl-inexpress/customs-dwell-time-by-lane) | Largest single driver of late counts on UK to EU lanes post-Brexit. | If 60% of late shipments cluster in 1 to 2 lanes, customs dwell is the cause and the fix is documentation, not network. | | [Exception Rate](/nerve-centre/kpi-cards/dhl-inexpress/exception-rate) | Upstream signal. Exceptions become late deliveries 24 to 72h later. | A spike in exceptions on day T predicts a late-count spike on day T+2. | | [Avg Transit (days)](/nerve-centre/kpi-cards/dhl-inexpress/avg-transit) | The mean of the timing distribution; late shipments are the tail. | If transit-days inflated by 0.4 day and late-count tripled, the distribution stretched: more shipments crossed the late line. | | [Open Claims](/nerve-centre/kpi-cards/dhl-inexpress/open-claims) | Downstream symptom. \~5 to 15% of late shipments turn into a claim if the parcel is also damaged or missed a deadline. | Climbing late count predicts a 1 to 3 week delayed claim spike. Watch the leading indicator. | | Cross-connector: [`shopify.refund_rate`](/nerve-centre/kpi-cards/shopify/refund-rate) | Downstream impact. Late deliveries drive refunds at 7 to 14 days lag. | Each late shipment is a 5 to 10% probability of a refund request, depending on customer expectations and the order value. | ## Reconciling against the vendor's own dashboard **Where to look in DHL InExpress's own dashboard:** [MyDHL+ portal](https://mydhl.express.dhl/) → **Track → Detailed View → Filter "Late deliveries"** → set date range to last 7 days. Each row is one late shipment with its `estimatedDeliveryDate`, `actualDeliveryDate`, and the gap. The portal does not surface a single "late count" tile; the count comes from the row count of the filtered view. For UK exporters, the *Customs & International* report has a per-lane delay breakdown that is useful for diagnosing the cluster pattern this card surfaces. **Why our number may legitimately differ from MyDHL+:** | Reason | Direction | Why | | -------------------------- | ----------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Time zone** | Boundary days off | MyDHL+ uses billing-country time zone (typically GMT for UK accounts). The card uses UTC. The 7D window is large enough to absorb most of the gap; daily counts can drift by one row. | | **Customs hold inclusion** | Either | MyDHL+ has a "Transit-only late" view that excludes shipments late solely because of customs hold time. The card counts customs delays as late, in line with the customer's own perception. | | **POD scan delay** | Ours higher in last 24h | Driver handheld batch syncs delay POD timestamps by 2 to 6 hours. A shipment that delivered on-time at 17:00 but POD-scanned at 22:00 may appear to cross the line. T-2 days fully reconcile. | | **In-transit scope** | Either | MyDHL+'s "Late" view sometimes includes in-transit shipments where the `estimatedDeliveryDate` has already passed but no POD yet. The card excludes in-transit shipments entirely until they close. The portal count can run higher mid-week. | **Cross-connector reconciliation:** | Card | Expected relationship | What causes legitimate divergence | | ------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- | | [`shopify.unfulfilled_orders`](/nerve-centre/kpi-cards/shopify/unfulfilled-orders) (if connected) | Indirectly upstream. Orders never handed to DHL on time can't deliver on time. | Webhook lag, B2B flows, weekend cutoff misses. Not a 1:1 reconciliation; use as a leading indicator. | | Customer service ticket volume | Downstream count. Each late shipment tends to generate 0.25 to 0.5 support tickets ("where is my order"). | Customer expectations, communication quality (proactive update emails reduce inbound contacts), order value (high-value orders have higher contact rates). | **Internal identity (within DHL InExpress):** `dhl_late_shipments_count = (1 - dhl_otd_rate) × dhl_shipments_total` over the same window. If this card reads 141 over 2,500 shipments, [On-Time Delivery Rate](/nerve-centre/kpi-cards/dhl-inexpress/on-time-delivery-rate) should be 94.4%. Discrepancies >1% indicate a sync gap. ## Known limitations / merchant FAQs **My late count tripled this week. What do I check first?** In order of likelihood: 1. **One bad lane.** Slice by destination on [OTD by Route](/nerve-centre/kpi-cards/dhl-inexpress/otd-by-route). 80% of the time a single Brexit-era lane (UK to FR or UK to DE) caved while the rest held up. 2. **Customs documentation regression.** A new SKU with missing HS codes, or a description-line change, can trigger holds for that SKU on every cross-border shipment. Check [Duty-Billing Mismatch Rate](/nerve-centre/kpi-cards/dhl-inexpress/duty-billing-mismatch-rate). 3. **Carrier capacity.** Pre-Christmas, pre-Easter, post-strike days run slow. Check the calendar, if it's a known peak window, the dip is structural. 4. **Promised-date tightening.** DHL revises transit-time tables periodically. If `estimatedDeliveryDate` is now tighter for the same lanes, late count rises mechanically. **Should I count "delivered late by 1 hour" the same as "late by 5 days"?** The card scores both as 1. It does not weight by severity. For high-value shipments where a 1h slip is acceptable but a 5-day slip is a refund, look at the per-shipment audit table in MyDHL+. The card is the executive scoreboard, not the diagnostic deep-dive. **Why is my late count higher in November and December every year?** Q4 / Christmas peak puts customs queues, carrier networks, and DC operations all under simultaneous strain. UK to EU lanes typically run 2 to 3x the late count of a calm February week. Plan support-team capacity accordingly; don't expect to clear the alert during peak. **Is the count exclusive of cancellations?** Yes. Cancelled shipments (intercepted before delivery, recipient refused at the door) are not counted as late. Returned-to-sender shipments are also excluded, they have their own card. **What's the difference between late shipments and failed deliveries?** **Late** = delivered after the promised date. **Failed** = first delivery attempt failed (recipient not home, address invalid). A failed-delivery shipment usually delivers late on the second attempt; it then counts on both [Failed Deliveries](/nerve-centre/kpi-cards/dhl-inexpress/failed-deliveries) and this card. **Does the card count B2B shipments?** Yes. DHL InExpress is used for both DTC and B2B in many merchants' setups. The card pools both. If you want to slice, the workspace admin can enable a `customer_segment` filter. **Should I be worried if late count drops sharply with no operational change?** Usually no, it tracks volume. A quiet week (post-promo, pre-launch) will have fewer total shipments and fewer late ones. Pair with [On-Time Delivery Rate](/nerve-centre/kpi-cards/dhl-inexpress/on-time-delivery-rate), if the rate held steady while count dropped, it's a volume effect, not a performance change. *** ### Tracked live in Vortex IQ Nerve Centre *Late Shipments* is one of hundreds of KPI pulses Vortex IQ tracks across DHL InExpress and 70+ other ecommerce connectors. 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