Case Study: Kotahi achieves more accurate cargo demand forecasting with Microsoft Corporation

Kotahi - Customer Case Study

Kotahi, a New Zealand supply chain collaborator serving more than 40 exporters, importers, and logistics partners, needed a better way to forecast shipping-container demand for highly perishable exports. Its manual Excel-based process was time-consuming and only about 80% accurate, making it harder to match cargo with vessel capacity efficiently. Microsoft Corporation helped Kotahi address this challenge using Azure, Azure Machine Learning, Azure Data Factory, Azure SQL Database, Power BI, and the Microsoft Cortana Intelligence Suite.

Microsoft Corporation and UXC Eclipse implemented an automated demand-forecasting solution that pulled historical data from multiple systems and delivered forecasts through Power BI dashboards. The new approach cut the forecasting process from four days a month to about 30 minutes, improved forecasting accuracy to more than 90%, and is expected to save Kotahi over US$1 million annually in supply chain costs.

Kotahi

Neville Richardson

Group IT Manager