Case Study: Kotahi achieves automated demand forecasting and optimized container capacity with Microsoft Power BI

Kotahi - Customer Case Study

Kotahi, a New Zealand supply-chain collaborator that plans and sources container capacity for more than 40 exporters and importers, faced a challenge: manually matching perishable exports to limited shipping capacity using Excel was slow and only about 80% accurate. To automate demand forecasting and give decision makers self-service reporting, Kotahi engaged UXC Eclipse and Microsoft Power BI, building on Microsoft technologies including the Cortana Intelligence Suite, Azure Machine Learning, Azure Data Factory, and Azure SQL Database.

Working with Microsoft data scientists and UXC Eclipse, Kotahi deployed an Azure Machine Learning web service and automated pipelines that pull historical orders, run hierarchical time-series forecasts, and write results to Azure SQL Database, with business users viewing forecasts and scorecards in Power BI dashboards. The Microsoft Power BI–centered solution cut monthly forecasting from four days to about 30 minutes, raised accuracy from ~80% to over 90%, enabled self-service analytics, and is expected to save more than US$1 million in annual supply-chain costs.

Kotahi

Neville Richardson

Group IT Manager