> ## 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. # Fulfillment Rate Over Time, Adobe Commerce > Fulfillment Rate Over Time for Adobe Commerce stores. Tracked live in Vortex IQ Nerve Centre. How to read it, why it matters, and how to act on it. **Metrics type:** [Supporting Metrics](/nerve-centre/overview#metrics-types-explained) • **Category:** [Ecommerce Platform](/nerve-centre/connectors#connectors-by-type) ## At a glance > Daily fulfillment rate over trailing 90 days, expressed as % of orders shipped within the merchant's promised SLA. The trend chart for [Fulfilment Rate](/nerve-centre/kpi-cards/adobe-commerce/fulfillment-rate). Captures multi-week patterns (3PL queue depth, holiday-season backlog, seasonal staffing changes) that point-in-time fulfillment metrics miss. | | | | ------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **What it counts** | Per day: `COUNT(orders shipped within SLA hours of payment) / COUNT(orders that should have shipped that day)`. SLA is configurable per merchant (default 48h consumer, 72h B2B). The chart is the percentage series; companion absolute count series available. | | **API field** | `state`, `created_at`, `updated_at` from `GET /rest/V1/orders`; shipment existence via shipment index. | | **VAT / tax treatment** | n/a, time-and-count metric. | | **Shipping inclusion** | n/a. | | **Discounts** | n/a. | | **Credit Memo refund treatment** | An order shipped within SLA then later refunded still counts as "shipped on time". | | **`state` machine inclusion** | `processing` and beyond count toward the denominator; orders with at least one shipment count toward the numerator. | | **`pending_payment` quirk** | Excluded; SLA clock only starts when payment captured. | | **Multi-currency `grand_total` vs `base_grand_total`** | n/a. | | **Store View scope (`store_id`)** | All Store Views; per-Store-View overlays useful when warehouses serve different regions independently. | | **Time window** | `90D` daily granularity. | | **Alert trigger** | None by default; pair with [Fulfilment Rate](/nerve-centre/kpi-cards/adobe-commerce/fulfillment-rate) for alerts. | | **Roles** | owner, operations | ## Calculation ``` DATE_HISTOGRAM rate(state=complete) WHERE date BETWEEN [period_start, period_end] ``` ## Worked example A nutritional supplements brand on Adobe Commerce 2.4.6, US ShipBob and UK Huboo 3PLs, B2B in-house fulfillment from HQ. SLA: 48h consumer, 72h B2B. 90-day window ending Monday 4 May 26. **90-day fulfillment overview:** | Metric | Value | | -------------------------- | ----------------------------------- | | Average daily on-time rate | 94.2% | | Standard deviation | 3.4 pts | | Lowest day on-time rate | 78% (single bad day, Friday 22 Apr) | | Highest day on-time rate | 99% (typical Tuesday) | | Days below 90% threshold | 9 of 90 | **Notable dips in the 90-day series:** | Period | Median rate | Cause | | ---------------------- | ----------- | ------------------------------------------------ | | 18-22 Apr 26 (5 days) | 84% | UK warehouse staffing dip (packer absent) | | 5-7 Mar 26 (3 days) | 82% | US warehouse stock-recount disruption | | 12 Feb 26 (single day) | 73% | UPS pickup truck delay; backlog cleared next day | What this is telling operations: 1. **94.2% average is in the healthy range.** Best-in-class is 96%+; below 90% sustained needs intervention. 2. **The 9 below-90% days cluster around 3 incidents**, not random variance. Each had an identifiable operational cause. 3. **The 18-22 Apr UK staffing dip** is the single largest issue; 5 days at 84% means roughly 16% of orders breached SLA across that week. Cross-check with [Fulfilment Delay Alert](/nerve-centre/kpi-cards/adobe-commerce/fulfilment-delay-alert) firings for that period. 4. **The Mar 5-7 stock-recount disruption** is a known operational cost; if recounts happen quarterly, the fulfillment dip is predictable. Communicate proactively to customers in advance to manage expectations. 5. **The 12 Feb single-day dip (73%)** was a pure carrier issue (UPS pickup missed), self-resolved next day. Acceptable, no systemic action needed. 6. **The 7-day moving average shows a slight upward trend** from 93.8% (12 weeks ago) to 94.6% (latest week). Operational-maturity gain, possibly from the merchant's recent introduction of pre-pick batching at Huboo. 7. **Action**: review UK warehouse staffing-flex policy (the Apr staffing dip would have been caught earlier if the planner had access to forecast volume); consider proactive customer-comms for known disruption days. The point: the 90-day chart shows the difference between a single bad day (carrier issue, weather) and a multi-day systemic issue (staffing, integration). The pattern shape determines the operational response. ## Sibling cards merchants should reference together | Card | Why pair it with Fulfilment Over Time | | --------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------- | | [Fulfilment Rate](/nerve-centre/kpi-cards/adobe-commerce/fulfillment-rate) | Single-period summary. | | [Fulfilment Delay Alert](/nerve-centre/kpi-cards/adobe-commerce/fulfilment-delay-alert) | Real-time alerting for breaches. | | [Unfulfilled Orders](/nerve-centre/kpi-cards/adobe-commerce/unfulfilled-orders) | Current-state pipeline. | | [Fulfillment Breakdown](/nerve-centre/kpi-cards/adobe-commerce/fulfillment-status) | Cross-state distribution. | | [Total Orders](/nerve-centre/kpi-cards/adobe-commerce/total-orders) | The volume context (a 90% rate on a busy day is more material than on a quiet one). | | [Refund Rate](/nerve-centre/kpi-cards/adobe-commerce/refund-rate) | Lagging effect; sustained SLA breaches drive refunds. | | [Cancellation Rate](/nerve-centre/kpi-cards/adobe-commerce/cancellation-rate) | Lagging effect on customer-cancels. | | [`shopify.fulfillment_over_time`](/nerve-centre/kpi-cards/shopify/fulfillment-rate-over-time) | Cross-platform peer. | ## Reconciling against the vendor's own dashboard **Where to look in Adobe Commerce Admin:** > **Reports > Sales > Shipping** for shipment counts and aggregates. Adobe doesn't natively compute on-time rates; manual computation requires per-order time-since-payment vs SLA. > **Sales > Orders** with state filter and date range; manual export and analysis for SLA breach detection. > **Sales > Shipments** lists every shipment created in the period. **Why our number may legitimately differ from a manual Admin computation:** | Reason | Direction of divergence | | ------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------- | | **SLA threshold**. Card uses a configurable threshold (default 48h consumer, 72h B2B). Manual analysis using a different threshold gives different results. | Material if thresholds differ | | **Time-zone**. Admin in Store View timezone; card UTC. Day-bucket assignment can shift by ±1. | Negligible at 90D | | **`pending_payment` exclusion**. SLA clock only starts at payment capture. Admin export may include pending-state in the count. | Card rate higher than naive admin computation | | **Partial shipments**. Adobe allows partial shipments. Card treats any shipment as fulfillment-started. Stricter SLAs (all items shipped) yield lower rates. | Card rate higher than strict definition | | **Sync lag**. Card uses OpenSearch sync; Admin live. | Negligible at 90D | **Cross-connector reconciliation (when these connectors are connected for this merchant):** | Pair | Expected relationship | What divergence tells you | | ---------------------------- | -------------------------------------------- | ----------------------------------------------------------------------------------------- | | 3PL on-time-shipment reports | Should align within sync lag | Material divergence indicates either off-platform shipments or SLA-definition difference. | | Carrier API tracking | First-scan timestamp ≈ Adobe shipment-create | Lag indicates carrier handover delay. | ***
Same-metric documentation cross-reference (for agencies running multiple platforms) * [`shopify.fulfillment_over_time`](/nerve-centre/kpi-cards/shopify/fulfillment-rate-over-time) * [`bigcommerce.fulfillment_over_time`](/nerve-centre/kpi-cards/bigcommerce/fulfillment-rate-over-time)
## Known limitations / merchant FAQs **Why does the chart use 48h consumer SLA, my promise is 24h?** Configure the manifest to your actual SLA. The 48h default is industry-norm; merchants with same-day or 24h promises should configure tighter. Per-Store-View thresholds are also supported (B2B 72h, consumer 48h, premium 24h on the same merchant). **Adobe Commerce vs Magento Open Source: difference?** None at the calculation. Both editions have the shipment entity and state machine. **My multi-store, can I overlay Store Views on the chart?** Yes, configure per-Store-View series. Useful when each warehouse serves a specific Store View; per-warehouse trend shows operational health independently. **A single bad day (carrier issue) tanks my 7-day moving average; how to filter?** Use the per-cause analysis. The card surfaces the dips; the operational team annotates known causes. The Vortex IQ workspace allows incident annotations against the chart so the dip explanation is preserved. **Why include `pending_payment` orders in the denominator?** They're not in the denominator on this card. Only orders that have entered `processing` (paid) count toward the SLA-eligible denominator. `pending_payment` is excluded because SLA hasn't started. **Why does the on-time rate sometimes spike to 99%+?** Quiet days (single-digit order count) can show 100% on a single shipment. The 7-day moving average smooths this; raw daily numbers can be volatile. **Partial shipments confuse the metric, how does the card handle them?** Default: any shipment for an order moves it to "fulfillment-started" and counts as on-time if within SLA. For stricter "all items shipped" measurement, configure the manifest. The default is operational-pragmatic; the strict view is service-promise-rigorous. **Why does my customer service team see different SLA breach numbers?** Customer service usually counts breaches as "customers contacted us about a delay", which understates breach count (most customers don't complain on day 3, only on day 5+). The card counts SLA breaches by definition (over the threshold), regardless of customer notification. *** ### Tracked live in Vortex IQ Nerve Centre *Fulfillment Rate Over Time* is one of hundreds of KPI pulses Vortex IQ tracks across Adobe Commerce 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.