AI DRIVEN SUPPLIER SELECTION AND TAM ALLOCATION

摘要

A machine learning (ML) module that can continuously learn from the market data and historical orders to dynamically recommend an optimum supplier portfolio to the manufacturer for a specific product. Using artificial intelligence, this analytical tool automates the supplier selection process based on evaluation of each supplier against a number of business features. The limitations of a manual selection of suppliers are substantially alleviated when each supplier is rigorously and automatically evaluated against a well-designed set of business features. For each supplier, the ML module generates a set of feature-specific scores for the business features used in evaluating the supplier. All scores are then combined to generate a supplier-specific final score for each supplier. The ML module uses the supplier scores to dynamically allocate Total Available Material (TAM) percentages to a pre-defined number of top-ranked suppliers to assist the manufacturer in the selection of best suppliers for the desired product.