Case Study: a cleaning products manufacturer improves forecasting and inventory planning with Columbus Advanced Analytics in Microsoft Azure AI

Cleaning Products Manufacturer Leverages Data to Meet Shifts in Market and Seasonal Demand

A medium-sized cleaning products manufacturer faced challenges in planning for market shifts due to its data being stored in multiple, disconnected systems, including having retail-sales data outside its core ERP. To overcome this, they partnered with Columbus, which utilized Advanced Analytics in Microsoft Azure AI.

Columbus consolidated the manufacturer's data into a data lake, enabling the creation of a reliable forecasting model based on historical sales, weather, and other factors. This solution delivered improved efficiencies from better raw-materials planning, increased revenue through optimized product distribution for seasonal demand, and the new ability to forecast inventory needs. Columbus enabled the manufacturer to base decisions on predictive analysis to supply future demand rather than relying solely on past data.