Evaluate transit times to core customer zones, carrier pickup frequency, dock and yard capacity, WMS and integration capabilities, SLA performance history, and value‑add services such as kitting and returns. Model these factors against storage and per‑pick costs to determine total cost‑to‑serve.

Closer proximity reduces drayage and transit variability, increases carrier options, and often lowers parcel and LTL rates. That proximity improves lead‑time consistency for expedited eCommerce orders and JIT B2B deliveries while enabling more efficient routing and reduced fuel costs.

Prioritize temperature‑controlled bays, scalable pick‑and‑pack lines, efficient slotting, returns processing, kitting, and a modern WMS with API/EDI connectivity for marketplaces and carriers. Visibility, exception management, and SLA monitoring are critical for omnichannel consistency.

Break proposals into fixed and variable components—storage (pallet/cubic), receiving/putaway, picking/packing, labeling, and outbound charges. Run peak and returns scenarios, include onboarding and SLA penalties, and validate assumptions with prospective 3PL throughput and lead‑time metrics.

Assess available warehouse labor and skill levels, prevailing wage trends, industrial rental rates and vacancy, yard and trailer staging capacity, zoning and permitting timelines, and any local incentive programs. These influence operating cost, uptime, and speed‑to‑scale.