Build an OTIF risk heatmap for consolidated and multi-stop loads, identifying drivers such as appointment density, dwell at [PrimaryDCs], consignee unload rates, and seasonal congestion across [Region]. Use historical actuals from [HistoricalShipmentsFile] and service targets [TargetOTIF] to quantify risk by lane and stop count.
Output requirements: (1) A heatmap-ready table (Lane, Stop Count, Avg. Early/Late Minutes, Risk Score 1–5, Root Cause, Mitigation). (2) A mitigation playbook with tiered actions (expedite, resequence, partial drop, split-load). (3) A control chart specification for weekly monitoring.
Highlight trade-offs between consolidation depth and appointment adherence. Provide “red flag” rules that auto-prevent over-consolidation during peak windows.