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Analytics · Importers

Import demand and reorder analytics

An importer with long lead times built a forecast that accounts for transit and customs so reorders happen before stock runs out.

Microsoft FabricPower BIAzure Machine LearningSemantic model
Stockouts
-31%
illustrative
Excess stock
-18%
working capital freed
Lead time
Real
transit and customs
Forecast
Per SKU
and lane

Illustrative scenario · example figures

The challenge

Reorder points assumed domestic lead times, but goods took weeks in transit and days at customs, so the business swung between stockouts and overstock tying up cash.

What we built

We built a demand forecast tied to real transit and clearance times, with reorder recommendations that factor in the full import lead time by supplier and lane.

  • A demand forecast by product with seasonality and trend.
  • Reorder points set from real transit and clearance times.
  • Stockout and overstock risk flagged per SKU.

Outcomes

  • Reorders are placed in time for the full import lead time.
  • Stockouts and overstock both fall as the forecast reflects reality.
  • Working capital tied up in excess stock is freed.

Where the data came from

Microsoft Dynamics 365Historical salesForwarder transit timesACE clearance

Data is drawn from the systems the operation already runs on and delivered in the client’s own tenant.

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