Small Problems, Big Levers: Lean, AI, and Growing Pains with Jamie Flinchbaugh cover art

Small Problems, Big Levers: Lean, AI, and Growing Pains with Jamie Flinchbaugh

Small Problems, Big Levers: Lean, AI, and Growing Pains with Jamie Flinchbaugh

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Episode SummaryMost big problems in a manufacturing business started out as small ones that nobody solved. In this episode, Justin sits down with Jamie Flinchbaugh, founder of JFlinch and author of People Solve Problems. They talk about why leaders keep reaching for big levers like AI, reorgs, and acquisitions, when the real momentum usually comes from breaking problems down and understanding cause and effect.Jamie explains how to connect daily huddles to monthly KPI reviews so leaders can trust that their teams have the ball. He also explains why process metrics invite curiosity while output metrics drive accountability. The two dig into a practical approach to AI for mid-market manufacturers, what breaks first when a company doubles in size, and how to bring skeptical veterans along on standardization. They close on how operations leaders can translate lean gains into the language boards and PE owners care about.About the GuestJamie Flinchbaugh is the founder of JFlinch, where he works as an advisor, coach, and board member to leaders building organizations that hold up. He started on the plant floor at Chrysler and went through MIT’s Leaders for Manufacturing program. He spent 15 years co-founding and building the Lean Learning Center into one of the top lean transformation firms in the country. More recently he served as Corporate Vice President of Qorvo’s Lean Journey.Jamie has worked with more than 300 companies, including Harley-Davidson, Intel, Mars, Amazon, and Whirlpool. He has helped build close to 20 companies as a co-founder, board member, or investor, and he serves on the boards of Robinson Fans, York Container, S&S Cycle, and Orion Fleet Intelligence. He wrote People Solve Problems: The Power of Every Person, Every Day, Every Problem, co-wrote the lean bestseller The Hitchhiker’s Guide to Lean, and hosts the People Solve Problems podcast.Key TakeawaysBig levers are often an act of desperation. Buying a company, replacing the CEO, or launching an AI program can feel like progress. Jamie sees more momentum in breaking a big problem into medium-sized pieces you can confidently move, then working out cause and effect on each one.Structure matters more than systems. Every metric should answer three questions: how are we performing, why are we performing there, and what are we doing about it. When a red metric shows up in a monthly review with the “why” and the countermeasure already attached, leaders can trust the team instead of jumping in from the top.Every injury started as a trip hazard. You can’t predict which small problem will become the big one, so solve them while they’re small. Smaller problems also give your people more repetitions, which builds problem-solving capability faster.Process metrics drive curiosity, output metrics drive accountability. Measuring diet and exercise tells you far more about what to change than waiting to measure heart attacks. The same logic applies on the shop floor.Start AI with a nagging problem. Skip the AI strategy. Pick a messy problem that has sat in the back of your mind, run a small experiment, and learn what the tools can do. Treat it like pruning a growing tree, because nobody knows where the tools will be in 18 months.Know which kind of AI fits the job. Machine code and other work that needs consistency calls for deterministic tools. Generative AI is better suited to finding patterns in handwritten quality reports or normalizing customer specs. Jamie ranks efficiency gains last, behind making the team smarter and doing work you never had time for before.AI always sounds confident. Challenge its output the way you would an intern’s work. And ask whether you would have spent three days helping an employee succeed the way you spent three days on the tool.Growth breaks at the connections. Every person you add creates new handoffs, and every handoff is a chance for delay or error. Activities and flows tend to hold up as a company grows. The connections between people and departments change the most and are the hardest to get right.You already had a standard. A great chef doesn’t measure, and they are still remarkably consistent. Small teams have standards embedded in a few experienced people. Scaling means giving that consistency tools that work across the whole enterprise.Standardize to solve a problem. Ask why this standard, why now, and how far to take it. Standardizing scheduling across three acquired plants matters if they share a supply chain. Standardizing their food service probably doesn’t. Writing a process down is what lets you troubleshoot it when it fails.Know your board before you pitch to it. Some PE firms are full of operators who understand cause and effect, while others are purely financial. Family-owned businesses usually care most about sustaining the company for the next generation. Interest rates are unlikely to return to zero, so operations leaders need to learn capital efficiency, return on assets, and ...
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