Managing data against shortage
How the automotive chip shortage came about, and how better use of existing data can mitigate against supply chain disruption. Featuring original research from the University of Bath.
The chip shortage exposed just how fragile lean supply chains are when demand patterns shift suddenly and lead times stretch to a year or more. In this session, QR_ and the University of Bath explore both the structural causes and the data-driven mitigations available to manufacturers now.
The third QR_ Insightinar brings together QR_ practitioners and academic research on supply disruption risk mitigation, drawing on a Ford Motor Company case study and two decades of automotive PDM experience.
Download machine transcript ↓Chapters
What this session covers
Root cause of the shortage
A perfect storm of pandemic-driven demand shifts, lean inventory practices, and semiconductor lead times stretching to 52+ weeks.
Data as a mitigation tool
Manufacturers with better parts data visibility could identify exposure earlier and prioritise re-sourcing efforts more accurately than those flying blind.
Model outcomes
The University of Bath study demonstrated measurable risk reduction from proactive inventory positioning — even without perfect demand forecasts.
Practical starting point
Existing Plan for Every Part (PFEP) data, used with discipline, provides a strong foundation for supply disruption modelling without a major new system investment.
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