Course Objective & Scope
Logistics, fulfillment, and last-mile delivery operations run on tight margins, volatile demand spikes, heavy documentation, and constant field exceptions. This 1-2 day sector-focused workshop bridges predictive AI (forecasting and optimization) with generative AI and workflow automation to solve high-friction operational challenges across the supply chain.
Participants work through practical logistics cases across four core domains: volume and capacity forecasting, dynamic route and dispatch decision support, proactive control-tower exception handling, and intelligent document processing for bills of lading, customs paperwork, invoices, and proof-of-delivery (POD) records.
Who Should Attend?
- Logistics, transportation, warehouse (WMS/TMS), and last-mile delivery operations leaders
- Supply chain planning, fleet management, control tower, and operational excellence managers
- Digital transformation, product, and data/IT teams in 3PL, retail, e-commerce, and manufacturing organizations
Key Takeaways
- Match specific logistics pain points to the right technology: predictive ML, mathematical optimization, vision/IDP, or LLM workflows
- Structure data inputs and operational KPIs for depot volume forecasting, shift staffing, and fleet capacity planning
- Design proactive exception-management workflows that detect ETA drift, failed-delivery risks, and SLA breaches before customers complain
- Automate extraction and reconciliation of shipping documents (waybills, PODs, customs forms, freight invoices) into TMS/ERP systems
- Build a prioritized logistics AI roadmap anchored in OTIF, cost-per-drop, fleet utilization, and manual touch-time reduction
Curriculum
Mapping AI Across the Logistics and Last-Mile Value Chain
- Pinpointing margin erosion and friction across first-mile pickup, sortation hubs, linehaul, and last-mile delivery
- Combining the triad: Predictive ML + Mathematical Optimization + Generative AI / Workflow Automation
- Bridging data silos across TMS, WMS, ERP, telematics, and carrier portals
Demand Forecasting, Volume Spikes, and Capacity Planning
- Forecasting regional parcel/freight volumes and return flows using promotions, weather, and seasonal signals
- Translating demand forecasts into warehouse shift scheduling and fleet capacity commitments
- Managing forecast uncertainty and peak-season buffer strategies
Dynamic Routing, Dispatch, and Last-Mile Execution
- Moving from static route plans to dynamic dispatch with time windows, vehicle constraints, and live ETA updates
- Reducing failed first-attempt deliveries through AI address cleansing, recipient coordination, and smart rerouting
- Field and driver copilot workflows for faster drop-offs and issue reporting
Logistics Document Automation and Freight Audit (IDP + LLMs)
- Extracting structured data from multi-format waybills, bills of lading, customs declarations, and carrier invoices
- Automating 3-way reconciliation (PO, rate card, invoice) and flagging accessorial charge discrepancies
- Streamlining Proof of Delivery (POD) verification and damage claim triage using multimodal AI
Agentic Control Tower, Exception Handling, and Action Plan
- Designing proactive exception workflows that detect ETA drift, summarize root causes, and trigger mitigation options
- Automating proactive customer notifications and carrier follow-ups with human-in-the-loop escalation for high-value shipments
- Workshop sprint: scoping and prioritizing the top 3 logistics AI use cases with OTIF and cost-per-shipment KPIs
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