Inventory Management & Forecasting - Capacity Planning

Determining the production capacity to meet customer demand in a timely manner is a challenge. This challenge is made even greater when serving an international market with a premium product. Not getting the tradeoff between cost of excess inventory and responding to customer needs in a prompt fashion can be damaging for a firm’s bottom line and brand image.

Meeting increased demand for timely spare part delivery at a luxury car manufacturer using Machine Learning to identify service patterns.

Machine Learning algorithms trained on historical transaction data can be applied to demand forecasting problems in order optimize inventory management and ensure optimal capacity levels for manufacturers.

When faced with increasing expectations in international markets for timeliness of delivery of spare parts, the luxury car maker Aston Martin brand turned to Tools Group’s SO99+ engine to help increase stock availability targets without increasing inventory1. By applying machine learning to Aston Martin’s historical data, SO99+ was able to identify 8 new service patterns that allowed the optimization of over 80,000 stock keeping units (SKUs). Using this information, replenishment plans were created to meet new service target levels without increasing stock levels.