Supply chain planners rely on statistical forecast models that use 12-24 months of historical shipment data, missing the real-time POS signals, promotional lift events, and new product introduction (NPI) patterns that actually drive near-term demand variability. The resulting forecast error cascades into either excess safety stock that ties up working capital or stockouts that trigger expedited replenishment at premium freight cost, often LTL spot rates 40-60% above contracted FTL lane rates.
Built For
Demand Planning Manager responsible for a 15,000 SKU forecast across 8 distribution regions with a 12-week rolling planning horizon
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Demand Planner
Integrates POS signals, promotional calendars, and seasonal decomposition into a consensus demand forecast with daily deviation alerts.
Inventory Planner
Translates demand forecast updates into safety stock adjustments and replenishment order recommendations by DC.
Transportation Planner
Connects demand surge signals to inbound freight mode decisions, switching from LTL to FTL or expedited when lead time compression is needed.
Multi-signal demand sensing that integrates POS data, promotional calendars, seasonal decomposition, and NPI ramp curves into a consensus forecast that updates daily and flags deviation alerts.
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Analyzing TMS data... Three lanes account for 68% of empty miles this month: Chicago-Detroit (31% deadhead), Dallas-Houston (24%), and LA-Phoenix (13%). Combined revenue loss from unloaded miles is estimated at $187,000. Backhaul matching opportunities exist on the Chicago-Detroit corridor based on shipper demand signals.
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