An American consumer health company operating over twenty global proprietary brands struggled with time-consuming, error-prone, and subjective spreadsheet-based forecasting for its over-the-counter products. To modernize this workflow, Sigmoid delivered a scalable, machine learning-based demand forecasting solution. Sigmoid’s advanced software automated category-level inventory predictions, replacing manual estimation processes and empowering the demand planning team with high accuracy. By reducing the Mean Absolute Percentage Error and eliminating operational bottlenecks, Sigmoid’s intelligent platform significantly improved supply chain planning, minimized forecasting discrepancies, and greatly enhanced the overall productivity of the organization's global demand planners.

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