Throughout the supply chain, analytical models are used to identify demand levels for different marketing strategies, sale prices, locations and many other data points. Ultimately, this predictive analysis dictates the inventory levels needed at different facilities. Data scientists constantly test different scenarios to ensure ideal inventory levels and improve brand reputation while minimizing unnecessary holding costs.

After analyzing the gap between current and predicted inventory levels, data scientists then create optimization models that help guide the exact flow of inventory from manufacturer to distribution centers and ultimately to customer-facing storefronts.