August 7, 2025

AI in Motion: The AI in Supply Chain & Manufacturing Podcast

Episode 5: Why ERP Failed and AI Will Succeed

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00:00 / 47:57

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In this episode of AI in Motion, host JP Morgenthal interviews Patrick Gaugahn, a supply chain and manufacturing veteran with 33+ years of Fortune 100 experience. The conversation explores the complex intersection of supply chain management, manufacturing processes, and the transformative potential of AI in these industries.

Patrick shares insights from his experience as one of the first Lean Six Sigma black belts in 1996, discussing the challenges of ERP implementations, the hidden factories of Excel-based shadow IT, and the promise of agentic AI to revolutionize how businesses manage their operations. The discussion covers real-world horror stories from the automotive industry, innovative approaches like DDMRP (Demand Driven Material Requirements Planning), and how AI can help solve age-old problems of inventory management and supply chain variability.

4 Key Highlights

1. The ERP Paradox: Traditional ERP systems promise efficiency but often force businesses to abandon the unique processes that made them successful, leading to costly failures like Hershey’s Halloween disaster. AI-powered solutions could enable customization at a fraction of traditional costs.
2. The Hidden Factory Problem: Most manufacturing companies run “hidden factories” of Excel spreadsheets and Access databases alongside their ERP systems. These shadow IT solutions handle the real complexity that rigid ERP systems can’t manage, creating both risk and opportunity for AI transformation.
3. Dynamic vs. Static Planning: The podcast reveals how static safety stock and lead time calculations in traditional systems create massive inefficiencies. AI can enable dynamic, real-time adjustments based on actual variance rather than fixed averages, dramatically reducing working capital tied up in inventory.
4. Agentic AI as the Future: Rather than monolithic solutions, the future lies in ecosystems of specialized AI agents that can adapt to specific business needs, potentially dropping system costs “through the floor” while delivering unprecedented flexibility.