> ## 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. # Pending Shipment, JD.com > Pending Shipment for JD.com stores. Tracked live in Vortex IQ Nerve Centre. How to read it, why it matters, and how to act on it. **Card class:** [Hero](/nerve-centre/overview#card-classes-explained) • **Category:** [Marketplace](/nerve-centre/connectors#connectors-by-type) ## At a glance > **Pending Shipment** counts orders that buyers have paid for but you have not yet dispatched. On JD this number is not just a to-do list, it is a live risk gauge. Every paid order sits against a JD ship-deadline window, and a backlog that climbs above roughly twice your 30-day average is the clearest leading indicator that fulfilment is bottlenecking and the Logistics DSR is about to take a hit. Chinese buyers expect movement fast, so an unshipped pile turns into late dispatches, then negative Logistics ratings, then lost search ranking. This is a hero card in the Fulfilment family and reads best beside the dispatch-rate, SLA, and late-dispatch cards below. | | | | --------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **What it counts** | The number of orders that are paid but not yet dispatched at the moment of reading. | | **Sample type** | Backend API data from JD.com, refreshed on the standard data refresh. | | **Why it matters** | A growing backlog is the earliest warning of a fulfilment bottleneck. Left unaddressed it breaches the JD ship-deadline, drags down the Logistics DSR, and demotes listings. Catching the spike while it is still a backlog, before it becomes late dispatches, is the whole point. | | **Reading the value** | Read it against your 30-day average. At or near average is normal; a value above twice the average trips the alert and means dispatch is not keeping pace with intake. Pair with orders-per-day to confirm whether intake spiked or dispatch stalled. | | **Currency** | count | | **Time window** | `RT` | | **Alert trigger** | `>2x 30D avg` | | **Sentiment key** | `jd_pending_ship` | | **Roles** | owner, operations | ## Calculation A real-time count of orders in the paid-but-not-dispatched state at the moment of reading. The alert compares this live count to the trailing 30-day average backlog: crossing twice that average trips it. Orders move out of the count the instant a dispatch scan is recorded, so the figure falls as you ship. Cancelled-before-dispatch orders drop out without counting as shipped. Both JD Logistics handover-pending and POP self-fulfilled pending orders are included, since both face a ship-deadline. ## Worked example *A representative reading of **Pending Shipment** for a typical merchant on JD.com.* Suppose your 30-day average backlog is about 60 orders. This morning the card reads 145, well past the 2x line of 120, and the alert is red. Checking orders-per-day shows a flash promotion doubled intake yesterday, while the dispatch rate held flat, so the backlog is an intake spike the warehouse has not absorbed. The clock matters: several of those orders are within hours of their JD ship-deadline, and missing it would hit the Logistics DSR. The action is immediate, surge dispatch capacity onto the oldest orders first to clear the at-deadline ones, then plan staffing against the next promotion's expected peak. For deeper investigation, use Vortex Mind to rank pending orders by time-to-deadline; for natural-language exploration, ask Ask Viq "how many pending orders are within four hours of their JD ship-deadline". ## Sibling cards merchants should reference together | Card | Why merchants reach for it | | ---------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------- | | [`jdc_pop_dispatch_rate`](/nerve-centre/kpi-cards/jd-com/pop-self-fulfilled-dispatch-rate) | Fulfilment sibling: the dispatch speed that clears this backlog. | | [`jdc_late_dispatch_dsr`](/nerve-centre/kpi-cards/jd-com/late-dispatches-risking-dsr-logistics) | Fulfilment sibling: the late dispatches a backlog turns into if unaddressed. | | [`jdc_logistics_sla`](/nerve-centre/kpi-cards/jd-com/jd-logistics-sla-compliance) | Fulfilment sibling: the delivery promise a backlog ultimately threatens. | | [`jdc_orders_per_day`](/nerve-centre/kpi-cards/jd-com/orders-day) | Fulfilment sibling: daily intake that explains whether a spike or a stall caused the backlog. | | [`jdc_dsr_threshold`](/nerve-centre/kpi-cards/jd-com/dsr-brand-auth-logistics-sla-threshold-crossed) | Reputation sibling: the DSR threshold a sustained backlog can breach. | ## Reconciling against the vendor's own dashboard **Where to look in JD.com's own dashboard:** JD's Seller Centre order-management view lists orders by status, and the pending-shipment or to-be-shipped queue is the direct equivalent. The count there should match this card at the same moment, allowing for refresh lag. **Why the Vortex IQ value may legitimately differ:** | Reason | Direction | What to do | | ------------------------------------------------------------------------------------------------------------------------------------ | --------- | -------------------------------------------------- | | **Refresh timing.** This is a live count; orders shipped between refreshes still show until the next sync. | Variable | Force a manual refresh for a current-second count. | | **Status definition.** Vortex IQ counts paid-but-undispatched; JD's queue may include or exclude awaiting-payment or on-hold orders. | Variable | Confirm which statuses the vendor queue includes. | | **Fulfilment scope.** This card includes both JD Logistics handover-pending and POP pending; JD may split them. | Variable | Sum both queues if the vendor separates them. | | **Time zone.** Deadlines compute in China Standard Time; confirm profile alignment. | Marginal | Confirm time zone match. | **Cross-connector reconciliation:** read with orders-per-day to separate an intake spike from a dispatch stall, and with the dispatch-rate card to confirm capacity. For divergence investigations, use Vortex Mind. ## Known limitations / merchant FAQs **Q: How often does Pending Shipment update?** It is a real-time count, recomputed on every refresh (typically every 30-60 minutes for live integrations). Because it changes as you ship, force a manual refresh during a busy dispatch run for an up-to-the-second figure. **Q: Why does my JD.com dashboard show a different number?** The usual causes are refresh timing (orders shipped between syncs still show here), the status definition (whether awaiting-payment or on-hold orders are counted), and fulfilment scope (JD Logistics vs POP queues). Match those before assuming a real divergence. **Q: The backlog spiked but my team shipped normally. What happened?** Almost always an intake spike rather than a dispatch stall. Check orders-per-day: a promotion or festival can double intake overnight, so a steady dispatch rate still leaves a temporary pile. Prioritise the orders closest to their ship-deadline first. **Q: Can I customise the alert threshold?** Yes, the multiple of the 30-day average (default 2x) is configurable per profile in the Sensitivity tab. Lower it if your ship-deadlines are tight, or raise it for categories with naturally lumpy intake so routine promotion spikes do not over-alert. *** ### Tracked live in Vortex IQ Nerve Centre *Pending Shipment* is one of hundreds of KPI pulses Vortex IQ tracks across JD.com 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](https://app.vortexiq.ai/login) or [book a demo](https://www.vortexiq.ai/contact-us) to see this metric running on your own data.