Orders downloaded from /download/orders that haven’t been dispatched yet.
At a glance
Live count of Alibris orders downloaded from /download/orders that haven’t yet been dispatched (no confirm-shipment event recorded). The workload view: how many books are queued for picking, packing, and shipping right now. Alerts when the count exceeds 2x the 30-day average, signalling either a volume spike or a fulfilment-team capacity problem.
| What it counts | COUNT(orders WHERE status='CONFIRMED' AND dispatch_confirmed_at IS NULL AND status NOT IN ('CANCELLED', 'REFUNDED')). Includes orders within their dispatch_due_by budget (typical state) and orders past their deadline (which also appear on Late Order Processing Queue). |
| API endpoint + report | Computed locally from the Alibris Inbound Orders feed. Recomputes every 4 hours; updates in real time as confirm-shipment events land. |
| Severity | P2 baseline, P1 above 2x avg. Normal operating queue is healthy; a 2x spike means workload exceeds team capacity. |
| Why it differs from Late Order Processing Queue | Pending Dispatch shows ALL undispatched orders (most still within their budget). Late Order Processing Queue shows ONLY orders past their deadline. The two together: this is the workload view; Late Order is the alert view. |
| Fees / commission | Not applicable directly. Indirect: undispatched orders represent gross-of-commission revenue not yet earned. |
| Refunds / cancellations | Cancelled and refunded orders excluded. Cancellation moves the order to Cancellation Rate. |
| Currency | Not applicable. |
| Healthy ranges | A bookseller doing 22 orders/day with 2-business-day handling typically carries 35 to 55 orders pending at any time (roughly 2.5x daily volume). Above 110 (2x average) is the trigger. |
| Common causes of spikes | (1) Volume surge (back-to-school, holiday, promotion), ~30%. (2) Staff absence / illness, ~28%. (3) Confirm-shipment cron broken, dispatched-but-not-confirmed orders inflate the count, ~22%. (4) Inventory mismatch caused order-acceptance backlog, ~12%. (5) Other, ~8%. |
| Multi-marketplace overlap | Per-marketplace queue. The same fulfilment team handles all marketplaces; spikes here often correlate with AbeBooks Pending Dispatch. |
| Time window | RT (live count, refreshed every 4 hours). |
| Alert trigger | >2x 30D avg, the threshold where capacity is exceeded. |
| Roles | owner, operations. |
Calculation
Calculated automatically from your Alibris 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 US bookseller, 22 orders/day average on Alibris, 2-business-day handling. Snapshot 01 May 26 09:00 UTC.| Bucket | Orders | Notes |
|---|---|---|
| Within 0 to 50% of dispatch budget | 28 | Healthy, just-arrived orders |
| Within 50 to 75% of dispatch budget | 22 | On-track, workload normal |
| Within 75 to 100% of dispatch budget | 38 | At-risk, prioritise today |
| Past dispatch_due_by | 8 | Already late (also on Late Order Processing Queue) |
| Total Pending Dispatch (this card) | 96 | (30D avg = 48; ratio 2.0x) |
>2x 30D avg = 96).
Six things to notice that are specific to Alibris and the book trade:
- The 38 at-risk orders are the urgent action set. Each one is within 6 to 12 hours of becoming an SLA breach. Triage today’s work to clear this bucket first; the on-track and just-arrived buckets can wait until tomorrow.
- The 8 already-late orders are the highest-cost work. Each one is dragging Dispatch SLA Compliance. Expedite-ship them with courier upgrade today; the SLA hit per order outweighs the courier cost.
- The 2.0x ratio is right at the alert threshold. Investigate cause: was Friday a volume-spike day with 35+ new orders? Did a staff member call in sick on Monday? The 30-day average represents normal workload; sustained 2x means underlying capacity issue.
- Confirm-shipment cron is the most under-suspected cause of inflated counts. If the cron fails or runs too infrequently, dispatched orders linger in the “pending” bucket for 6 to 24h longer than reality. Check Last Successful Upload for the outbound-confirm side.
- Cross-marketplace correlation matters. The same bookseller’s AbeBooks Pending Dispatch on the same date shows 78 (2.0x avg). Co-spiking on both AbeBooks and Alibris confirms a fulfilment-team capacity issue, not a marketplace-specific problem.
- Library Services orders extend the window. Alibris Library Services (institutional buyers) often have longer-than-standard dispatch windows (3 to 5 business days). Listings tagged
buyer_type=INSTITUTIONfall into the longer bucket; their presence inflates the count without inflating risk. Filter to non-institutional for a sharper view.
Sibling cards merchants should reference together
Pending Dispatch is the workload view. Pair with these:| Card | Why pair it with Pending Dispatch |
|---|---|
| Late Order Processing Queue | The breach view. Pending Dispatch + Late together: workload AND breach. |
| Dispatch SLA Compliance | The aggregate metric. A spike here precedes SLA decline by 24 to 72h. |
| Avg Time to Process (hrs) | Distribution view of fulfilment latency. |
| Inbound Orders File Lag | If feed is slow, your dispatch budget is already eroded when orders appear. |
| Last Successful Upload | Confirm-shipment failures inflate this card; check both. |
| Cancellation Rate | Companion budget. Cancellations clear orders from this queue but cost on the cancellation metric. |
| AbeBooks Pending Dispatch | Sibling marketplace; co-spike confirms capacity issue. |
Reconciling against the vendor’s own dashboard
Where to look in the Alibris seller dashboard:- Sellers → Manage Orders → filter by Pending. Per-order detail with dispatch_due_by deadline.
- Sellers → Performance Dashboard. The aggregate fulfilment view.
| Reason | Direction | Why |
|---|---|---|
| Refresh cadence | Ours updates every 4h | Alibris UI is real-time; this card recomputes on the inbound feed cadence. |
| Time zone | Boundary effects | Alibris uses US Pacific Time on .com; the connector uses UTC. |
| Outbound-confirm latency | Ours can show pending even when Alibris shows shipped | Confirm-shipment events delayed by cron schedule inflate this count. |
| Institutional handling window | Different bucketing | Library Services orders have longer dispatch windows; not all UIs surface this clearly. |
| Card | Expected relationship | What causes legitimate divergence |
|---|---|---|
abebooks.ab_pending_dispatch | Co-correlated when fulfilment team is shared. | Marketplace-specific dispatch windows differ slightly. |
amazon.amzn_pending_orders | Different tracking, similar concept. | Amazon’s clock starts at payment, Alibris at confirmation. |
Known limitations / merchant FAQs
The card just hit 96, double the average. What do I do today? Three actions: (1) Drain the at-risk bucket (orders within 75 to 100% of dispatch budget) first. (2) Verify confirm-shipment cron is running; if dispatched-but-unconfirmed orders are inflating the count, that’s a feed issue not a workload issue. (3) If genuine workload spike, add capacity (overtime, extend handling time temporarily, or pause new listings until queue drains). Why does this card differ from Alibris’s pending-orders count? Alibris UI is real-time; this card refreshes every 4h. Confirm-shipment latency (your cron schedule) can show “pending” here for up to 4 hours after Alibris UI shows shipped. Run cron every 15 minutes to minimise. ISBN match quality, can it cause inflation here? Indirectly. Books that staff can’t find on the shelf (because the inventory ISBN doesn’t match the physical book) sit in the pending queue longer while staff search or escalate. Better intake-ISBN-capture reduces this latency. Multi-marketplace, should I drain Alibris first or AbeBooks first when both queues spike? Drain by financial impact: rare-book orders first regardless of marketplace, then by hours-to-deadline ascending across both. Don’t bias by marketplace; bias by per-order penalty. Library Services / institutional buyers, do they need different treatment? Yes. Their longer dispatch windows mean less urgency, but their high AOV and feedback weight mean higher per-order reputational stakes. Treat institutional orders as P2-but-handle-carefully; they don’t drag your average dispatch but they DO drive the high-value cohort. Listing-quality / Buy Box impact, when does the queue spike hurt my ranking? When pending dispatch correlates with rising late-dispatch ratio. The queue itself isn’t visible to Alibris’s ranking system; the SLA breach downstream is. Watch Dispatch SLA Compliance as the actual ranking input. Inventory-sync lag, can it inflate this card? Yes. Stockout orders (book sold elsewhere first) sit in the pending queue until the seller cancels them. Real-time inventory sync prevents the order from being accepted in the first place. Rare books vs commodity, queue treatment difference? Rare books require longer pick-and-pack time (find in rare-book room, condition-check, careful packaging). Most booksellers run a single 2-day handling time which is tight on rare. Settinghandling_time=3 on rare-tagged listings absorbs 90% of the rare-book queue pressure.
Why doesn’t Alibris show me this view?
Alibris’s pending-orders page exists but lacks the 30-day-baseline comparison. The “2x average” alert is a Vortex IQ-derived threshold; Alibris’s own UI shows count without trend context.
When does the alert auto-clear?
When the count drops below 2x 30D average. The 30D average updates daily, so the alert may persist through a sustained higher-volume period until the average rises to match.