Before
Need to reduce Work in Progress (WIP) levels by £6m a year at UK sites using data science-driven insights.
After
£1m savings in a single quarter, and potentially achieving the £6m savings within 18 months.
The How
- Understand the Value Stream Map of the factory
- Collate the data sources (including Machine, ERP, IT Breakdown, Supply, Human Resource etc…)
- Identify the bottlenecks using Supervised Machine Learning (Linear Regression in this case)
- 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
