Glass is one of the most complex materials to allocate freight costs for. Mixed loads, A-frame constraints, high insurance premiums, and multiple drops make standard per-pound or per-mile models wildly inaccurate. AI is now automating freight cost allocation down to the SKU and order level—giving glass distributors precise visibility into landed costs and margin per transaction.
Why Freight Allocation Fails in Glass
Most ERP systems distribute freight costs:
Proportionally by order weight or value
Evenly across all lines in a load
Manually based on rule-of-thumb methods
This fails when:
A single oversized IGU takes up half the trailer
Different delivery zones are served in one run
Some SKUs require special crating, padding, or escorts
The result? Mispriced deals, distorted margin reporting, and undercharging repeat clients.
How AI Models Allocate Freight Intelligently
Load Geometry + Cost Impact
AI analyzes the physical cube, weight, and protection requirements of each order. It calculates how much space and cost each SKU actually consumed on the truck.
Route Cost Attribution
AI considers drop sequencing, regional fuel costs, tolls, and delay factors. A shipment to a downtown jobsite gets a higher proportional cost than one to a dock-accessible contractor.
SKU Sensitivity Weighting
Heavier or oversized glass panels may incur surcharges or packaging premiums. AI ensures these costs are assigned to the correct order—not spread across unrelated items.
Dynamic Cost Forecasting
During quoting, AI can estimate freight cost per item based on current route density and truck availability—supporting real-time pricing decisions.
Strategic Value to the Business
More accurate gross margin reporting at line-item level
Better pricing guidance for freight-sensitive products
Transparent freight cost recovery for clients with custom logistics terms
Reduced margin erosion in multi-stop regional deliveries
With freight costs rising and clients demanding clarity, AI-driven cost allocation gives distributors a defensible, scalable way to protect profitability.
