Case Study: Global Auto Manufacturer saves $10M in inventory costs with dotData

How A Global Manufacturer Lowered Inventory Costs by $10M Annually

The global auto manufacturer faced significant challenges in forecasting demand for its vast inventory of over 200,000 replacement parts. Their manual, expert-reliant process was slow, difficult to maintain, and resulted in inaccurate forecasts, making it impossible to optimize costly inventory levels. They engaged dotData and its AI platform to address this.

dotData implemented its proprietary AutoFE (Automated Feature Engineering) and AutoML technology to automatically analyze billions of data points. This provided highly accurate, explainable forecasts with far less reliance on human experts. The solution resulted in a 50% reduction in forecast error, enabling the manufacturer to achieve over $10 million in annual recurring cost savings.