> ## 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. # SLA Compliance by Warehouse, ShipBob > SLA Compliance by Warehouse for ShipBob 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:** [Fulfilment & Logistics](/nerve-centre/connectors#connectors-by-type) ## At a glance > Per-DC breakdown of SLA-compliant orders, rendered as a horizontal bar chart with one bar per ShipBob distribution centre. The DC-level slice of the aggregate [Fulfilment Rate](/nerve-centre/kpi-cards/shipbob/fulfilment-rate) and [On-Time Delivery Rate](/nerve-centre/kpi-cards/shipbob/on-time-delivery-rate) gauges; reveals which DC is dragging the network. | | | | ----------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **What it counts** | For each DC: `COUNT(orders shipped from DC within SLA) / COUNT(orders received at DC)`. SLA is the merchant-contracted cutoff (typically same-day if received before 12:00 local DC time). | | **API endpoint** | `GET /order` and `GET /shipment` joined on `location_id`. The card groups by DC and applies the per-DC cutoff in the DC's local time. | | **DC scope** | **Per-DC, one bar per location.** Domestic US (Chicago, Cincinnati, Memphis, Moreno Valley, Bristol PA, Las Vegas, Pearl River MS) and international (Bristol UK, Toronto CA, Melbourne AU) all rendered. | | **Shipping-method scope** | All methods pooled per DC. Use [SLA by Method](/nerve-centre/kpi-cards/shipbob/shipping-method-performance) for method-level slice. | | **Inventory-split semantics** | **Each leg counts at the DC that handled it.** A multi-DC split order contributes to two bars, once at each shipping DC. Single-DC orders contribute to one bar only. | | **Perfect-order definition** | This card is on-time-shipping per DC. Perfect-order combines on-time-shipping + on-time-delivery + no damage + no return-error; not represented here. | | **SLA definition** | Per-DC contracted cutoff. Standard is 12:00 same-day, but some merchants negotiate 14:00 / 16:00 cutoffs and these vary per DC. The card reads cutoff configuration from the merchant manifest. | | **Peak-period seasonality** | **Q4 typically degrades all DC bars by 5 to 15 percentage points, but unevenly.** Coastal DCs (LAX, NJ) see worse degradation due to dock congestion; central DCs (Chicago, Cincinnati) hold up better. International DCs (Bristol UK, Melbourne AU) often show the largest peak swings due to local carrier capacity. | | **API rate limits** | 200 requests / minute / token, same shipment-payload as the rate cards; no additional API cost to render this view. | | **Time window** | `30D` (rolling 30-day) | | **Alert trigger** | `<90%` per DC, the `sla_by_warehouse` sentiment trips when ANY DC drops below 90 percent (configurable). | | **Roles** | owner, operations | ## Calculation Calculated automatically from your ShipBob 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 DTC apparel brand using ShipBob 3PL with 3 DCs. Reading taken at 09:00 ET on 12 Mar 26 for the trailing 30 days. | Distribution Centre | Orders shipped | Within SLA | SLA Compliance | Bar colour | | ------------------- | -------------- | ---------- | -------------- | ------------------ | | Chicago (CHI) | 9,840 | 9,496 | 96.5% | Green | | Moreno Valley (MOV) | 6,720 | 6,432 | 95.7% | Green | | Cincinnati (CIN) | 2,420 | 2,084 | 86.1% | Red, alert tripped | | Bristol UK (BRI) | 1,580 | 1,452 | 91.9% | Green | The chart shows three green bars and one red. Five things to notice: 1. **DC closest to customer ships fastest, and bars cluster at the top.** Chicago and Moreno Valley together do 78 percent of US volume and clear 95%; geographic match between DC and customer base is doing the work. The high-performing DCs are not "better" operationally, they are better-matched to demand. 2. **The Cincinnati bar at 86.1% is the actionable signal.** It dragged the aggregate fulfilment rate to 94.9% (see [Fulfilment Rate](/nerve-centre/kpi-cards/shipbob/fulfilment-rate) worked example). Action: rebalance inventory to reduce Cincinnati overflow volume, or staff up Cincinnati for current demand. Aggregate-level cards do not point to this; only per-DC does. 3. **Bristol UK at 91.9% is healthy by local standards.** UK DC SLA is computed against UK carrier transit-time tables (Royal Mail, DPD, DHL UK), which run looser than US peers. Comparing UK and US bars side-by-side without context is misleading; benchmark UK-vs-UK across periods. 4. **Q4 peak-period degraded all four bars together last December.** Reading from 5 Dec 25: Chicago 86%, Moreno Valley 84%, Cincinnati 71%, Bristol UK 78%. The 14 to 22 point uniform drop is the seasonal signal; reading bars in isolation against December numbers is not informative. 5. **A 1-bar-fail alert may be a routing problem, not a DC operations problem.** Cincinnati's 86.1% may be because too many far-zone orders were routed there (when Chicago lacked stock). Pair with [Warehouse Proximity](/nerve-centre/kpi-cards/shipbob/warehouse-proximity-performance) to confirm whether Cincinnati received proportionally more far-zone orders this period. ## Sibling cards merchants should reference together This card is a per-DC slice of fulfilment performance. Pair with these for diagnosis and action: | Card | Why pair it with SLA Compliance by Warehouse | What the combination tells you | | ----------------------------------------------------------------------------------------------------------- | --------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------- | | [Fulfilment Rate](/nerve-centre/kpi-cards/shipbob/fulfilment-rate) | The aggregate roll-up that this card breaks down. | One low bar dragging the aggregate is a single-DC fix; multiple low bars is a network-wide problem. | | [On-Time Delivery Rate](/nerve-centre/kpi-cards/shipbob/on-time-delivery-rate) | Customer-facing leg, also aggregated. | A low SLA bar with healthy delivery rate means the DC's late shipments still get there on time (carriers absorbing the slip). | | [Warehouse Proximity](/nerve-centre/kpi-cards/shipbob/warehouse-proximity-performance) | Per-DC closest-DC-ship rate. | Low SLA + low proximity at the same DC = inventory-allocation problem (DC is shipping far-zone orders). | | [Average Fulfilment Time by Warehouse](/nerve-centre/kpi-cards/shipbob/avg-fulfilment-time-by-warehouse) | Per-DC stopwatch. | Low SLA + high time-to-ship at the same DC = staffing or process problem on the warehouse floor. | | [Warehouse Backlog](/nerve-centre/kpi-cards/shipbob/warehouse-backlog) | Per-DC pending count. | Climbing backlog at the lagging DC predicts deeper SLA dips next week. | | Cross-connector: [`shopify.unfulfilled_orders`](/nerve-centre/kpi-cards/shopify/unfulfilled-orders) | Upstream order pressure (not DC-tagged in Shopify). | If Shopify unfulfilled spiked recently, expect 1 to 3 days of pressure on whichever DC handled the surge. | | Cross-connector: [`bigcommerce.unfulfilled_orders`](/nerve-centre/kpi-cards/bigcommerce/unfulfilled-orders) | Same upstream relationship for BC. | Same caveat. | | Cross-connector: customer NPS / returns rate | Downstream sentiment, lag 7 to 21 days. | Low-SLA DCs typically generate higher returns and lower NPS at the customer level, traceable through ship-from-DC tagging in Klaviyo flows. | ## Reconciling against the vendor's own dashboard **Where to look in ShipBob Merchant Portal:** [ShipBob Merchant Portal](https://merchant.shipbob.com/) → **Analytics → Performance → On-Time Shipping → DC breakdown**. The portal renders the same per-DC breakdown with toggles for date range and shipping method. Use *All Methods, Last 30 Days* to compare like-for-like. **Why our number may legitimately differ from ShipBob's portal:** | Reason | Direction | Why | | ------------------------------------------------------------ | ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **Timezone (UTC vs DC-local)** | Boundary days off | The card uses UTC for window boundaries and each DC's local time for cutoff calculation; portal uses the same. Merchants who switch portal to local will see day-edge shifts at the start and end of the window. | | **DC-level cutoff variance** | Either | Each DC may have a different contracted cutoff (e.g. Chicago 12:00, Cincinnati 14:00). The card reads cutoffs from the manifest; portal uses ShipBob's stored cutoff config. Mismatches require a manifest update. | | **SLA definition variance (carrier vs ShipBob vs merchant)** | Either | This card uses ShipBob's contracted cutoff as truth; merchants who quote tighter customer-facing SLAs in checkout will see a third number. | | **Peak-period batch-processing delays** | Ours lower for "today" | Q4 webhook lag of 4 to 12 hours; T-2 fully reconciles. | | **International DC carrier mix** | Either | Bristol UK uses Royal Mail / DPD / DHL UK which have different scan cadences than US UPS / FedEx; SLA computation accounts for this but portal-vs-card edge cases can occur. | **Cross-connector reconciliation:** | Card | Expected relationship | What causes legitimate divergence | | ------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------ | ------------------------------------------------- | | [`shopify.unfulfilled_orders`](/nerve-centre/kpi-cards/shopify/unfulfilled-orders) | Upstream pressure, not DC-tagged in Shopify, so cannot be split per-DC. ShipBob lag of 2 to 6 hours typical. | Webhook delivery failures, B2B / scheduled flows. | | [`bigcommerce.unfulfilled_orders`](/nerve-centre/kpi-cards/bigcommerce/unfulfilled-orders) | Same upstream relationship for BC. | Same caveat. | | Amazon FBA per-fulfilment-centre metrics | Peer 3PL with its own per-FC view. Independent population, not reconciled. | Different orders entirely. | | Customer NPS by ship-from-DC | Downstream sentiment per DC if Klaviyo flows tag DC. | Tagging completeness, sample size per DC. | ***
Documentation cross-reference (for agencies running multiple 3PLs) Per-DC SLA breakdown exists with conceptually similar definitions across other 3PLs. These are independent operations, not parallel measurements; the cross-link exists so multi-3PL agencies can navigate documentation. * Amazon FBA per-fulfilment-centre on-time shipping * Shopify Fulfillment Network historical per-DC metrics (legacy)
## Known limitations / merchant FAQs **ShipBob vs FBA, can I see a per-fulfilment-centre breakdown for FBA?** Yes, FBA exposes per-fulfilment-centre on-time shipping in Seller Central, but the populations are independent (Amazon orders vs DTC orders). Comparing a ShipBob DC to an FBA FC like-for-like is rarely useful; compare across periods within the same 3PL. **How does ShipBob choose which DC ships my order, and how does it skew this card?** The router picks the closest DC with full stock; if no single DC has stock, the order splits. Multi-DC splits create a leg per DC, each scored independently. The bar for the lagging DC is dragged not necessarily by floor inefficiency but by mis-allocated inventory pushing more far-zone orders to that DC. **SLA-vs-carrier-tracking discrepancy, why does my Bristol UK bar look bad while customer NPS is fine?** SLA definition variance. ShipBob's UK SLA is tighter than the carrier's posted transit-time tables; Royal Mail and DPD often deliver inside ShipBob's flagged-late window, so customers see "delivered on time" while ShipBob marks "shipped late". Three definitions (carrier, ShipBob, merchant) can give three numbers. Confirm with the per-DC late-shipment audit table in the portal. **Perfect-order vs on-time-shipping definitions per DC, what is the difference?** On-time-shipping per DC (this card) is one leg of perfect-order per DC. Perfect-order combines on-time-shipping + on-time-delivery + accuracy + no return. This card is the warehouse-floor leg only. **How do I plan for Q4 / BFCM peak using the per-DC view?** Look at last year's December bars. The DC that dropped least in 2025 should get more inventory in 2026; the DC that dropped most should get less. Pre-position by mid-October. Set the alert threshold lower temporarily (e.g. 80% instead of 90%) for December to avoid alert fatigue. **Multi-DC inventory split optimisation, how does this card help?** This card is the consequence, not the cause. Pair with [Warehouse Proximity](/nerve-centre/kpi-cards/shipbob/warehouse-proximity-performance) to see whether your inventory split forced too many far-zone orders into the lagging DC. Re-allocate stock per the portal's "Inventory Distribution" recommendation engine, then re-read this card 14 days later. **Returns flow, how do they appear in this card?** They do not. Returns are tracked separately ([Return Rate](/nerve-centre/kpi-cards/shipbob/return-rate)). The bar is outbound-only, scoring the original ship event. **Why does ShipBob show one DC as "shipped on time" but Shopify shows the order as still partial?** Multi-DC split sync. ShipBob's per-DC bar updates when the leg ships; Shopify's order status flips through `PARTIALLY_FULFILLED` until the LAST leg ships. The two systems will disagree for hours during multi-DC orders, especially when one DC ships morning and the other ships afternoon. **Why do my international DC bars (UK, AU) look so different from US bars?** Local carrier mix and SLA definition. UK uses Royal Mail / DPD / DHL UK with looser transit tables; AU uses Australia Post with often tighter cutoffs. Benchmark UK-vs-UK and AU-vs-AU across periods, not against US numbers. The card renders all DCs together for comparison but the absolute numbers are not apples-to-apples across regions. *** ### Tracked live in Vortex IQ Nerve Centre *SLA Compliance by Warehouse* is one of hundreds of KPI pulses Vortex IQ tracks across ShipBob 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.