The global manufacturer struggled with predicting lead times and costs accurately in their teams across the world. Less than half of their non-stockable items arrived on time. Estimating supplier costs and delivery times manually was slow and often inaccurate. This caused delays, increased costs, and unhappy customers.

We studied the client's supply chain to find the best ways to use AI. We then developed machine learning models to solve their biggest challenges. These tools predict supplier lead times, estimate purchasing costs, and forecast customer delivery dates more accurately. Eventually we connected the company's business needs with the technical AI development.

The AI solutions delivered significant improvements:

• Supplier lead time predictions are now 39% more accurate
• Purchasing cost estimates improved by 80%
• Promised delivery times for key items are 13% more accurate

The company replaced slow manual estimates with faster, data-driven AI predictions. This improved operational efficiency and customer satisfaction.