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

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A manufacturer that makes and distributes industrial and consumer cleaning products stored data on their various product SKUs in multiple locations; retail-sales data lived outside of their core ERP solution. That made it difficult for the company to plan for expected – and unexpected – changes in the market.

Using Advanced Analytics in Microsoft Azure AI, Columbus Global worked with the company to consolidate data in a data lake to build a reliable forecasting model based on historical sales, weather and other factors. As a result, this company could improve the distribution of products for better use of inventory and improve decision-making overall.

Benefits included:

  • Improved efficiencies and savings from better raw-materials inventory planning
  • Increased revenue due to better product distribution and readiness for seasonal demand
  • Enabled forecasting of needs driven by market trends and weather forecasts to ensure they have the proper inventory to supply demand.

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