Matthew Spooner - Planning research, industrial supply chains, and the AI hype cycle

In this episode, ⁠⁠⁠⁠⁠⁠⁠⁠⁠Ben⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Wim⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ talk to ⁠Matthew Spooner⁠, currently leading global planning at ⁠Hitachi Energy⁠, with over 30 years of experience across industry, consulting, and software.

Matthew has had a rare journey: from operational roles at Ericsson and ABB, to Research Director at Gartner, to thought leadership at Kinaxis. This wide-angle view gives him a sharp perspective on how planning tools are chosen, what makes supply chains tick, and where AI is pushing us next.

We discuss the real differences between industrial and consumer goods supply chains, and how too often, tools are designed for one and forced onto the other. Matthew also shares his view on why Gartner Magic Quadrants are losing relevance, what agentic AI can really replace, and why even advanced companies may be back at square one when it comes to maturity in the AI era.

Key topics covered include:

• • From Royal Navy to supply chain consulting and Gartner
  • How industrial vs. CPG supply chains differ in BOMs, variability, and tool needs
  • Demand vs. supply planning: where the focus should shift
  • Gartner’s evolution, Magic Quadrants, and transparency issues
  • The hype cycle of GenAI and why most pilots fail
  • Agentic AI: automating spreadsheets vs. revolutionizing planning
  • Rethinking optimization with AI and planning data layers
  • How AI resets maturity and levels the playing field

Key timestamps:

• (01:00) – Getting into supply chain via Excel and consultancy
• (03:00) – What really differs between industrial and CPG supply chains
• (05:45) – BOM variability vs. demand variability
• (08:10) – Engineering collaboration in industrial planning
• (10:00) – Planning tools: why most are built for CPG
• (12:15) – Inside Gartner: how it's evolved and the role of peer learning
• (13:30) – Magic Quadrants and why they’re less relevant now
• (17:00) – Transparency issues in vendor scoring
• (18:00) – AI’s hype cycle, pilot failures, and the reset on maturity
• (24:30) – Agentic AI: rebranded RPA or planning revolution?
• (29:00) – Network optimization and future use cases
• (33:00) – Final takeaways: peer networking, trusted content, and mindset shifts

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