The solution worked because it joined matching and allocation into one flow, rather than leaving margin analysis to disconnected records. ¹

WorkedDid not

Data foundation

Warehouse implemented ¹

Fragmented source conditions ¹

Matching

POs matched to SOs near real time ¹

Three prior attempts ¹

Allocation

Revenue and costs by delivery ¹

Delivery margin undetermined ¹

Visibility

99% accuracy ¹

About 70% accuracy ¹

The architecture combined a data warehouse with a data matching engine and an allocation engine. ¹ The matching layer connected purchase orders and sales orders in near real time. ¹ The allocation layer then assigned revenue and costs at customer, SKU and delivery level. ¹

This produced real-time gross margin per delivery and raised profit visibility from approximately 70% accuracy to 99% accuracy. ¹ The company could understand each deal more accurately, manage pricing and customer discounts, and make logistics decisions using profit per delivery. ¹ The important design choice was to make the allocation logic part of the operating data flow, not merely an explanatory report.

Fuel logistics firm improved delivery-level margin visibility with near-real-time cost allocation