Prioritize metrics that reflect operational capacity and reliability: dock-door count and throughput, order accuracy and pick-pack rates, SLA on order lead time and on-time delivery, WMS/API integration maturity, chargeback and claims rates, and peak handling capacity. Use these to model cost per order and service risk against demand variability.

Carrier density and direct transit lanes reduce handling and mileage costs. If Rinconada offers good LTL, TL, and intermodal options plus proximity to ports or airports, you lower transit time and freight spend. Limited carrier access increases reliance on feeder services and surcharges; quantify transit times and lane rates when modeling landed cost.

Require a modern WMS with API or EDI connectivity to your OMS, real-time inventory feeds, barcode/RFID scanning, batch and lot tracking, exception reporting, and support for returns and kitting. Verify sandbox integrations, SLA for data sync, and reporting cadence to ensure accurate omnichannel fulfillment.

Model total landed cost, not just rent: include freight spend, transit time impact on service levels, inventory carrying costs from longer lead times, and labor productivity. Run scenario analysis (cost per order, days of inventory, late-delivery penalties) and apply weighted service targets to balance rent savings against fulfillment performance.