Case Study: AGCO Corporation achieves an 81% inventory reduction and 25% increase in plant capacity with Emcien

Automatic Pattern Detection Digs through Big Data to Identify Optimal Product Offerings

AGCO, a global manufacturer and distributor of agricultural equipment, struggled with overwhelming product complexity and fragmented sales data: thousands of possible configurations made it impossible to see what customers actually bought, leading to poor forecasting, extended planning cycles, long lead times, high costs, excess inventory and a very low repeat rate on builds.

Emcien’s pattern-based analytics processed AGCO’s retail history to identify six core base units that satisfy 90–95% of demand, enabling build-ahead manufacturing with modular add-ons. Implemented within a year, the solution cut product variety by 61%, reduced days of inventory by 81%, increased plant capacity by 25%, and improved dealer and customer satisfaction.

AGCO Corporation