Jay and Andrew begin with a deceptively simple question: what actually makes a company “lean”? Starting with a quote from Shigeo Shingo, they challenge the common misconception that lean is just Kanban, and explore the deeper reality that lean is less about specific tools and more about principles, tradeoffs, and context.

From there, Andrew shares a deep dive into labor tracking and ERP data, uncovering how much work was happening that never made it into cost calculations, and why “door-to-door” time matters more than overly segmented tracking. Jay pushes back with the tension every shop feels: data is only valuable if it leads to action, and too much friction in systems can break team buy-in entirely.

The episode then shifts into Andrew’s current challenge: producing tight-tolerance parts that his team can’t fully verify in-house. They take a candid look at outsourcing vs. vertical integration, the true cost of CMM capability, and the uncomfortable position of shipping parts you can’t independently validate. Jay talks about why he bought a CMM earlier than expected, what he regrets, and how fast feedback loops can change everything.

Andrew shares insights with Jay from a recent lean-focused shop tour with Paul Akers. The conversation goes to the hidden dangers of batch processing vs. one-piece flow, why takt time can matter more than cycle time, how to identify and eliminate waste at the micro-task level, and why “don’t solve problems until they exist” is often the best strategy They also explore practical challenges like line balancing, inspection differences (CMM vs. vision systems), and the surprising complexity of measuring quality in manufacturing.

Plus, a candid discussion on whether shop tours actually scale, charging for tours vs. giving them away, and turning knowledge into a valuable product instead of a free commodity.

Why do some people naturally notice problems while others don’t? Andrew introduces ideas from the book Living Sensationally, exploring how different sensory personalities affect how workers perceive disorder and opportunities for improvement.

Andrew also shares the results of his shop’s first full week of 8 a.m. morning meetings followed by shop-wide 3S, complete with funky music and a noticeable surge in improvement activity. Jay and Andrew discuss how creating space for small improvements can build momentum, and why the real goal of cleaning isn’t cleanliness, but exposing hidden problems.

They also compare notes on using AI in manufacturing environments, including Andrew’s first experiments with Claude to automate CNC workflows and program an Andon status light for his workstation. Does AI have a lot of promise as a technical collaborator? Does it also have a lot of frustrations? You bet.