A multinational healthcare conglomerate specializing in pharmaceuticals, medical devices, and consumer healthcare products, with a strong focus on research and development to drive medical innovation.

Inaccurate demand forecasting led to inventory management challenges, including stockouts, overproduction, and customer dissatisfaction. The client required an AI-powered solution to optimize demand forecasting and align production schedules with inventory needs.

The client, with Turing's support, implemented a comprehensive AI-powered demand forecasting solution:

• Data collection and preprocessing: Turing collaborated with the client to gather historical sales data, including product-specific sales, promotional campaigns, and pricing strategies. Rigorous data cleaning was performed to remove inconsistencies and outliers.
• Model development: Various machine learning techniques, including Random Forest and ARIMA, were explored to identify the most accurate demand forecasting model. The best-performing model was deployed to predict future demand, aligning inventory levels with production schedules to reduce costs and improve efficiency.

• 30% reduction in stockouts: Optimized inventory levels led to fewer stockouts.
• 25% reduction in overstock situations: Improved demand forecasting minimized excess inventory.
• 15% reduction in inventory holding costs: Optimized inventory management reduced costs.