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W Company’s New Product Demand Forecasting Case Achieving 94–95% Accuracy in Top-Selling Segments Without Historical Sales Data

Achieved an average forecasting accuracy of over 96% for Rebar, Copper, Hot-Rolled Coil, and Coking Coal.

Dramatic Results: 14-49% Accuracy Improvement Depending on Data Inclusion

Recently, the use of AI technology in the pharmaceutical industry has been notable. It has achieved results that have been proven by specific figures, such as a 55.1% reduction in inventory costs and a 22.6% reduction in out-of-stock rates. In particular, it is notable that it predicted the number of patients with an accuracy of 96.5% and based on this, it predicted the sales volume of pharmaceuticals.

How did the AI demand forecasting system solve the chronic problems of the manufacturing site? And what changes did the site workers experience? This article contains vivid examples of how AI technology solved the problems of demand forecasting and inventory management that the manufacturing industry was struggling with.

Inventory management in the manufacturing sector has become a key factor in determining a company's competitiveness. The inventory management costs of global manufacturing companies account for an average of 32% of total operating costs, a trend that has been on the rise for the past five years.

Successful case of introducing AI inventory management in the manufacturing industry The inventory management method that relies on past experience and intuition is no longer competitive. The AI-based inventory management system can accurately predict demand by analyzing vast amounts of data in real time and automatically calculate the optimal inventory level.

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