Analytics · Manufacturers & Distributors
Cross-border inventory positioning analytics
A distributor with stock on both sides of the border analyzed where to hold inventory to balance duty, freight, and service.
Microsoft FabricPower BIAzure Machine LearningSemantic model
- Positioning
- Optimized
- cost vs service
- Freight and duty
- Lower
- illustrative
- Service
- Held
- with less stock
- Network
- Both sides
- of the border
Illustrative scenario · example figures
The challenge
Inventory was positioned by habit, so the business paid duty and freight to move stock that would have served the customer better from a different location.
What we built
We modeled demand, duty, freight, and service by location to recommend where each product should be held across the cross-border network.
- Demand and service modeled by location and product.
- Duty and freight cost of each positioning option.
- Positioning recommendations that balance cost and service.
Outcomes
- Stock is positioned on cost and service, not habit.
- Duty and freight spent moving the wrong stock is cut.
- Service levels hold with less inventory in the network.
Where the data came from
NetSuiteDemand dataDuty tablesFreight rates
Data is drawn from the systems the operation already runs on and delivered in the client’s own tenant.
Want this on your trade data?
Tell us where your numbers live and what leadership needs to see. You get a scoped plan and a quote within one business day.
Request a quoteMore case studies
ImportersLanded cost analytics by SKU and supplierAn importer moved landed cost off a monthly spreadsheet into a model that allocates freight, duty, and fees to every unit as goods arrive.ImportersTariff and duty exposure modelingWith tariffs shifting, an importer needed to see duty exposure by product and country and model the cost of a rate change before it landed.ImportersSupplier performance and lead-time analyticsAn importer consolidated supplier data to see lead-time reliability, defect rates, and total cost by vendor in one place.