Inventory Management through Intelligent Material Matching and Forecasting
Client Overview
A leading US wood product distributor managing over 7,500 item codes and $100 million worth of monthly inventory across their distribution network.
Business Challenge
High inventory holding costs, suboptimal inventory turns, and inaccurate forecasting led to higher inventory carrying costs and inefficiencies in inventory management and capital utilization. Difficulty in identifying similar or duplicate parts further complicated inventory management.
Solution Impact
AI-Powered Similar Parts Identification and Scoring: Identified 3,300 material pairs with 100% match and Implemented a sophisticated scoring system to rank material similarities.
Dynamic Inventory Parameter Calculation: Developed AI algorithms for real-time calculation of: Reorder Points (ROP) & Safety Stock levels and Adjusted calculations based on changing demand patterns and lead times.
Inventory Optimization: Analyzed first consumption patterns from procurement quantities and Identified excess inventory worth USD 710K.
Our Approach
Genesis AI implemented an advanced AI-driven solution Featuring:
Intelligent similar parts identification and scoring
Dynamic calculation of inventory parameters (ROP, Safety Stock, Min-Max levels)
Demand forecasting and inventory optimization
Genesis AI drives innovation in manufacturing with AI and machine learning, optimizing processes and boosting productivity across industries like chemical, petrochemical, and automotive.
