Vendor-reported figures — source: pando.ai
This 50-year-old pharmaceutical distributor serves more than 100,000 healthcare locations across North America, operating 20+ distribution centers and 200+ depots with $400M+ in annual freight spend across truckload, LTL, parcel, and courier modes. In pharmaceutical distribution, operational failures carry patient-level consequences — temperature-sensitive products, regulatory traceability requirements, and patient-facing last-mile delivery leave no margin for blind spots. The company ran on a Manhattan TMS in extended support, demanding daily manual workarounds that consumed hours of productive time. Procurement teams spent weeks per cycle building RFQs and reconciling rates across disconnected spreadsheets, with no intelligence on lane performance or carrier reliability. Once shipments left facilities, visibility ceased entirely until delivery confirmation. Five siloed systems — WMS, TMS, ERP, visibility, and freight audit — required constant data reconciliation, leaving management without a coherent view of network performance.
After evaluating and rejecting SAP TM and Oracle TMS — both too rigid and customization-heavy for healthcare logistics — the distributor deployed Pando's AI-powered freight management platform, which offered healthcare-specific functionality out of the box and integrated directly with existing ERP and WMS systems via API. The implementation introduced three AI-driven capabilities: an AI freight procurement analyst that auto-generates carrier RFQs with embedded performance intelligence and bundles complementary lanes into continuous-move opportunities; an AI transportation expert applying machine learning to load planning and route optimization, balancing cost, speed, and carbon emissions simultaneously; and an AI freight audit and pay specialist performing automated three-way matching across purchase orders, delivery confirmations, and carrier invoices. Real-time SKU-level shipment tracking — integrated with carrier systems and IoT devices — added temperature monitoring for pharmaceutical products. All rates, contracts, and performance data were centralized in a single platform with complete audit trails, eliminating the information silos that had fragmented operations.
Manual freight task time dropped 90%, compressing procurement cycles from weeks to hours and reducing planner workload by more than 80%. The company realized $15M+ in annual cost savings through smarter freight procurement and continuous network optimization. Additional outcomes:
Beyond the metrics, the operational character of logistics work shifted fundamentally: teams moved from daily system workarounds to proactive decision-making supported by live data. Carriers also benefited from faster automated payments, strengthening supplier relationships alongside internal gains.
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