# Len Pannett

Len Pannett writes and speaks about supply chain management, manufacturing operations, and innovation. Recent posts discuss practical uses of AI in supply chains, innovation awards, and additive manufacturing for spare parts.

- Profile: https://b2binfluencer.marketing/creators/len-pannett/
- LinkedIn: https://www.linkedin.com/in/lenpannett
- LinkedIn followers: 5,380
- Topics: artificial-intelligence, supply-chain, supply-chain-management, inventory-management, manufacturing-operations, data-quality
- Based on 12 dated posts, latest 2026-10-07

## Summary

They are most useful for grounded supply chain technology discussion tied to operational problems.

- Best for: A UK supply chain software brand planning a co-marketing webinar on AI readiness and data quality.
- Not for: A US software vendor seeking paid posts with tracked demo signups and cost per lead.
- Check first: Confirm audience breakdown by employer, occupation and seniority, and results from comparable work.

### Takeaways

- AI use cases in forecasting, inventory, supplier risk and MRO are real.
- Teams should start with the priority problem, then choose a tool.
- Clean, structured data is a must-have before a strategic pilot begins.

## Main ideas

- **Choose the tool after you name the problem**: Pannett argues that decision makers now have more technology options than they can usefully absorb. Teams should identify their priority problems first, then select the right tool—AI or otherwise. The difficulty has shifted from finding technology to applying it with purpose.
- **Clean data is a prerequisite, not a later phase**: Pannett treats data quality as a prerequisite for AI adoption, not a task to tackle alongside deployment. AI succeeds or fails on clean, structured data, as with any digital transformation, so data work should begin before a strategic pilot launches—ideally before the decision to run one.
- **AI adoption is becoming an expectation, and it will reshape operations**: Pannett argues that pressure to adopt AI comes from outside the firm as much as from within: customers and suppliers increasingly expect companies to use it. That is no reason to remove people from the loop. Human-in-the-loop oversight will remain essential for the foreseeable future, they say, even as operations and headcount change. Firms that do not adapt fall behind.
- **Innovation is now a must-have, and awards should reward measured results**: Drawing on several years of judging the CSCMP Supply Chain Innovation Award, Pannett argues that innovation has moved from a nice-to-have to a must-have in practically every company and sector. They say awards should recognise entries that demonstrate real innovation delivering measurable results in practice, not novelty for its own sake.
- **The engineering case is often settled; adoption stalls on everything around it**: Assessing a technology case, Pannett looks beyond whether the technique works to what is holding it back. On additive manufacturing for spare parts on long-lived assets, they conclude that the engineering case is clear and the remaining obstacles are organisational and broader than engineering. They extend the argument from one company to whole sectors, a recurring move in their writing.

## Work to read

- [Chairing a manufacturing supply chain forum: four AI takeaways for UK manufacturers](https://www.linkedin.com/posts/lenpannett_manufacturing-supplychain-inventorymanagement-activity-7509256104317595648-RA6Y)
- [Judging the CSCMP Supply Chain Innovation Award](https://www.linkedin.com/posts/lenpannett_cscmp-supplychain-awards-activity-7510667998031126530-0ERW)
- [Additive manufacturing for spare parts: lessons for UK rail, defence and energy](https://www.linkedin.com/posts/lenpannett_wabtec-leverages-additive-manufacturing-to-activity-7513611955769626624-lPXK)

## Brand relationships

- **CSCMP (Council of Supply Chain Management Professionals)** (disclosed_partnership)
- **The Manufacturer** (disclosed_partnership)

## Partnerships

No partnership or sponsorship offering is documented in the material reviewed. Len Pannett's posts show industry-event roles rather than a commercial format a brand can book: chairing CSCMP's Manufacturing Supply Chain & Inventory Forum in Birmingham and judging the CSCMP Supply Chain Innovation Award, with a post promoting the EDGE 2026 finalist sessions. Neither post describes sponsorship inventory, audience specifications, deliverables, pricing or an inquiry process. The third post points to an outside article on additive manufacturing for long-life spare parts. For the proposed co-marketing webinar on AI readiness and data quality, the subject matter aligns with what they discuss publicly, including a session on AI readiness and data quality in manufacturing supply chains, but the format remains an open question, not a rejected one. Ask them directly about sponsorship terms and the webinar format.

## Alternatives

- Imran Choudhery: Consider Imran Choudhery if the webinar should focus less on AI readiness and more on the practical boundary between demand planning and supply planning. A post explains how the functions differ, from forecasting requirements to balancing demand against inventory and suppliers, and names consequences such as stockouts, expediting and excess inventory. That gives a software company a concrete operational discussion to build around.
- Kevin Jordan: Consider Kevin Jordan if the campaign’s main goal is to connect manufacturing operations with management systems, energy performance or ISO 50001. One post frames energy as a business risk and describes structured energy management; another argues that management systems need to keep pace with changing products and processes. Those themes could support a session about operational discipline around digital change.
- Jonathan Walters: Consider Jonathan Walters if the need shifts from a manufacturing-focused AI-readiness webinar to a discussion of freight-market conditions and logistics resilience. A post connects weak manufacturing demand, excess truckload capacity and inverted spot and contract rates, then recommends tracking effectiveness alongside efficiency and resilience measures.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/