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 and On-Time Delivery Rate gauges; reveals which DC is dragging the network.
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.
The chart shows three green bars and one red. Five things to notice:
- 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.
- The Cincinnati bar at 86.1% is the actionable signal. It dragged the aggregate fulfilment rate to 94.9% (see 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.
- 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.
- 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.
- 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 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:Reconciling against the vendor’s own dashboard
Where to look in ShipBob Merchant Portal: ShipBob Merchant Portal → 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:
Cross-connector reconciliation:
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 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). 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 throughPARTIALLY_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.