Inventory Optimisation


Need to reduce Work in Progress (WIP) levels by £6m a year at UK sites using data science-driven insights.


£1m savings in a single quarter, and potentially achieving the £6m savings within 18 months.

The How

  1. Understand the Value Stream Map of the factory
  2. Collate the data sources (including Machine, ERP, IT Breakdown, Supply, Human Resource etc…)
  3. Identify the bottlenecks using Supervised Machine Learning (Linear Regression in this case)
  4. Use the ML model to forecast lead times to plan inventory levels and control supply levels based on expected these lead times in the following months