Multi-Location Fulfillment: $20–30K in Annual Savings From a Split-Shipment Strategy
Platform: BigQuery + Looker
Start a Similar ProjectWhat We Were Solving
An apparel retailer was fulfilling orders from 7–8 locations simultaneously: a third-party logistics provider, brick-and-mortar stores, and a central warehouse. Each location ran its own system — the 3PL had its own proprietary platform, stores had separate POS and shipping data, the warehouse used Shopify and ShipStation — with no shared reporting layer. Orders shipped from wherever stock was available, with no analysis of whether that was the cheapest or most logical choice. There was no cost-by-origin view, no threshold logic for when splitting a shipment actually saved money, and no way to quantify any of it.
How We Built It
We built a unified data pipeline ingesting from all source systems: Shopify, ShipStation, the 3PL's proprietary platform, and each store's fulfillment and shipping data. Everything landed in BigQuery, normalized into a common schema. Looker dashboards surfaced true shipping cost by origin, cost per order by weight and destination zone, and a split-shipment analysis — modeling when splitting an order across two origins (based on weight, distance, and carrier rates) was cheaper than a single full-location shipment. The threshold logic was validated against historical order data before operational rollout.
What We Delivered
$20–30K/yr
Annual savings from split-shipment strategy
7–8 locations
Unified into one fulfillment view
3 source types
3PL, retail stores & warehouse
Data-driven
Split-shipment threshold logic
The split-shipment strategy, driven entirely by the unified data model, identified $20–30K in annual savings. Fulfillment decisions shifted from reactive stock-based routing to cost-aware origin selection. The ongoing dashboard continues to surface cost-per-origin as carrier rates change.
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