People Solve Problems

On this episode of People Solve Problems, host Jamie Flinchbaugh welcomes Matt Zayko, Senior VP and Head of the Global Lean Office at GE HealthCare. Matt brings one of the broadest lean backgrounds in the field, and the conversation traces how that breadth shaped his thinking about what makes change actually last. Matt describes his lean origin story as being in the right place at the right time. As a graduate student in industrial engineering at the University of Michigan in the early 1990s, his advisor connected him with John Shook, who had just arrived from Toyota. Surrounded by thinkers like Jeff Liker, Al Ward, and Durward Sobek, Matt studied how Toyota developed products in half the time and with better quality, then applied that learning in industry roles at Chrysler, Delphi, and Pall under Danaher. He later spent fifteen years with the Lean Enterprise Institute, including work on Jim Morgan's lean product and process development team, before joining GE in 2021 and ultimately leading lean for GE HealthCare. Jamie notes a shared concern from their parallel paths: too many practitioners lock in what they learned early and apply it as dogma. Matt agrees, calling the confusion of principles with dogma one of the lean community's real failure modes. Asked about a particularly difficult problem, Matt goes straight to a lesson from his early career. Being technically right, he explains, is only half right. As a young engineer, he was convinced his solution was correct, and on paper it was. But the same idea had been proposed before and never sustained, so people had lost trust that anything would stick. The deeper insight followed: the problem is rarely improving; it is sustaining. Ideas are often only 80% right, and without a management system that catches the remaining 20%, the old problems return, and the people who invested in the change lose hope. Matt calls this the go slow to go fast approach, and he argues the sustainment side of change still gets far less attention than it deserves. The conversation then turns to breaking down problems in complex environments like product development and healthcare, where feedback arrives slowly, and the consequences of decisions may not be felt for months. Matt's advice is to recreate the gemba. Because a development program is a learning cycle rather than a repeating system, teams have to deliberately reconstruct how the work really happened on something real, such as a recently launched product. Visualizing that work, he says, is one of the most powerful starting points available, and from there a team can diagnose, set a target condition, and run the play again. On collaboration, Matt is direct: problem solving is a team sport. He credits GE's consistent problem-solving process as a standard that lets everyone read a problem the same way, but he stresses that the paper only matters if people build it together. When colleagues see their fingerprints on the document, ownership replaces resistance, and implementation moves fast. Matt closes with what inspires him about GE HealthCare: proof that a company more than 125 years old can transform. If it can be turned around there, he says, it can be turned around anywhere, and the lean community needs more examples like it. Learn more about Matt's work at www.gehealthcare.com, connect with him on LinkedIn at linkedin.com/in/matt-zayko-b3522811, and find his book, The Power of Process: A Story of Innovative Lean Process Development, on Amazon at https://www.amazon.com/dp/0367690306.

On this episode of People Solve Problems, host Jamie Flinchbaugh welcomes Bob Rogers, Founder and Chairman of BRC Imagination Arts and author of the new book Deep Story: A Complete Guide to Creating Transformational Visitor Attractions. Bob has spent five decades building visitor experiences for some of the world's best-known brands and museums, work that has earned more than five hundred international awards. It started somewhere smaller. At eighteen, he performed magic in the Magic Shop at Disneyland, where the job was to amaze people and then sell them the trick while they were still amazed. The lesson that stuck came after a customer bought a trick, read the instructions, and returned to expose him. A senior magician he admired told him the shop was not a temple built to display his skill. People came not to admire him, but hoping he would help them find some magic in themselves. Bob has treated that ever since as the foundation of selling, of hospitality, and of any attempt to communicate. This is where he believes most business communication goes wrong. Organizations decide what they want to say and build outward from the message, but wanting to say something does not create anyone's desire to hear it. Deep story runs the other direction. You look far into the audience for an emotional truth that already moves them, and far into the brand for the same thing, and the part people miss is that you are not looking for two triggers. You want the one that already exists in both. He frames it with a formula he admits sounds silly for creative work. An audience, A, enters a triangle, the delta symbol of change, and comes out as A prime. A prime minus A is the whole assignment, and that difference is almost always a change of heart, not a change in what people know. The Johnnie Walker experience in Edinburgh shows what that looks like in practice. It runs nine stories, and most guests arrive believing they do not like whiskey. Rather than teaching them the correct way to drink it, the experience asks what flavors they enjoy and builds a first cocktail to match. Bob reports net promoter scores in the low to mid eighties and a brand conversion score of ninety-one. Bartenders are trained never to push their own tastes. When the Milwaukee Brewers wanted an experience honoring founder Bud Selig, the team passed over his complicated public record for something smaller. Selig fell in love with baseball because his mother took him to games, which is how much of the crowd came to the sport too. That, Bob says, is the trigger you cannot manufacture, only find. For listeners whose reach extends to rearranging conference room chairs rather than commissioning a building, Bob suggests finding someone who will guide the process rather than decorate it, and starting with the heart rather than the technology. Fifty years have convinced him that people settle on emotion first and arrange the facts to fit afterward. To learn more about Bob's work, visit BRC Imagination Arts  Connect with him on LinkedIn You can also follow BRC Imagination Arts on LinkedIn  and Instagram, and find the book at deep-story.com.

In this episode of People Solve Problems, Jamie Flinchbaugh steps up to the microphone without a guest to talk about a pattern he keeps seeing in organizations: leaders trying to solve big problems by pulling big levers. Whether the problem shows up first and the lever follows, or the lever is pulled in hopes of solving something, Jamie states the result is usually the same. The connection between cause and effect gets lost. Jamie starts with a distinction that frames the whole episode. Most big problems are not really single problems at all. A budget problem, he explains, is actually a thousand small budget problems: overspending here, under-earning there, all adding up to something that looks like one giant issue. That aggregate is a theme, not a problem, and themes cannot be solved with one sweeping move. Real progress comes from understanding the details underneath. The first big lever Jamie examines is AI, a topic he recently explored in his blog article titled “AI Fragility: Why I’m Not Pro-AI or Anti-AI, but Pro-Thoughtfulness.” He uses AI regularly and never presents its work as his own, but he sees organizations rushing into adoption without a clear problem statement. When he asks what problem an AI strategy is meant to solve, the honest answer is often fear of missing out. He points to Starbucks pulling out an inventory control AI after nine months of building, deploying, and training as an example of what happens when the lever comes before the problem. His counsel is reassuring: it is very hard to be truly left behind, the tools keep improving, and there is plenty of time to catch up. What matters is being specific about what each deployment is meant to accomplish and whether you can evaluate the result. The second lever is organizational design. Jamie offers two truths that apply every time. First, an org change is never the only way to solve a problem; process design, culture and behaviors, or new capabilities can usually address the same issue, and often better. Second, every org design creates new problems. He calls it the shell game: waste gets moved around rather than removed. Solid lines on an org chart do not equal control, and leadership and culture still have to do the real work after the boxes move. The third lever is the return-to-office policy. Jamie describes it as a generic solution to a generically defined problem, usually labeled culture. Bringing people back may make culture easier to observe, but it does not fix it. When employees commute in only to sit through a full day of video meetings, the experience undermines the policy. He points to the book “The Year Without Pants” as an example of a fully remote company that was deliberate about how people spent time together in person. Jamie closes with three questions worth asking before any big lever gets pulled:  What problem are you fundamentally trying to solve?  Are there other pathways to that result?  What new problems will this solution create?  The details, he reminds us, are where the work is done and where the results are found. Read Jamie's AI Fragility article at https://www.jflinch.com/ai-fragility-why-im-not-pro-ai-or-anti-ai-but-pro-thoughtfulness/ and learn more about his work at https://www.jflinch.com. Check out the book Jamie was referencing in this episode

On this episode of People Solve Problems, host Jamie Flinchbaugh welcomes Renee Kaspar, Author and Workplace Strategist at Renee Kaspar Labs. A thirty-year veteran of human resources and the author of the forthcoming book HR Confidential, Renee has spent her career in the rooms where the most significant decisions about people get made. She joins Jamie to talk about what she calls The Great Transition, the period we are all living through, in which the foundations of work are shifting beneath our feet. Renee describes The Great Transition as a systems change rather than a single event. When one part of the system shifts because of AI, she explains, everything connected to it shifts too, which is why changing work also means rethinking education, hiring, pay, benefits, and how performance is measured. She likens the experience to raising a child, terrifying and constantly changing, with one crucial difference: a new parent has some kind of roadmap, and right now, no one does. To navigate a system in motion, she suggests finding an anchor and working outward from it, asking what has to move freely for that anchor to reach its next stage. Much of the conversation circles around agency, and Renee is candid about what its absence feels like. Lost agency, she says, shows up as anxiety, fear, burnout, and a loss of trust, the sense that control over one's own way of being has slipped away. She traces part of that to a vanished kind of stability, the era when a single employer could anchor an entire career. Drawing on a conversation she had just before the interview, Renee shares an idea that clearly moved her: agency is learned, not given. It comes from quieting the fear, looking inward to understand your own value, and knowing what you can carry with you from one place to the next. Renee and Jamie examine how this fear varies across generations, and she is careful to say that every group is anxious for its own reasons. She sees a younger generation entering an uncertain world without a playbook their parents can hand down, a middle generation exhausted and worried about whether the next rung on the ladder will still exist, and her own peers more willing to embrace change yet uneasy about ageism. Understanding those reasons, Jamie notes, is itself a step toward reclaiming agency. On how to practice agency, Renee points to self-advocacy, resilience, and curiosity, the kind of steady learning that builds confidence to face the next challenge. Jamie adds that writing things down, breaking problems into smaller pieces, and honestly weighing what might actually go wrong tends to shrink anxiety down to a workable size. Renee builds on that with a habit she picked up secondhand from Warren Buffett: for anything you face, name three positive things that could come from it. She is careful to distinguish this from forced optimism, and she offers a pointed warning that fear sells, that it is being aimed at us constantly, and that consuming it without care is one of the fastest ways to lose your footing. In the final stretch, Renee turns to her own profession and makes the case that human resources needs to reinvent how it shows up. Rather than remaining the function people fear, she argues, HR can become the steward and conscience of the organization. This part recognizes that people are burnt out and helps build something more stable and more human. For those who want to continue the conversation, watch for Renee's forthcoming book, HR Confidential. You can learn more about Renee Kaspar at https://reneekasparlabs.com/ and connect with her on LinkedIn at https://www.linkedin.com/in/reneekaspar/.

On this episode of People Solve Problems, host Jamie Flinchbaugh welcomes Brittany Irwin, Applications and AI Engineering Manager at NFI Industries. With an industrial engineering degree from the University of Pittsburgh’s Swanson School of Engineering and a career spanning large-scale third-party logistics and fast-moving B2B SaaS startups, Brittany offers a grounded view of how people, processes, and technology fit together. The conversation centers on a theme she has presented publicly, including at the Lehigh CSCRL Spring Symposium: how organizations move AI from hype to habit. Brittany makes a case that runs counter to a common assumption. Most AI and automation efforts in logistics do not stall because the technology falls short, she explains, but because the business was never ready for it. The industrial engineering instinct to find waste and standardize it is the same discipline AI demands, since a tool can only return a reliable output when it is given a reliable input. So before moving any process toward automation, Brittany asks a pointed set of questions: where the process begins and ends, what the top exceptions are and why they happen, and whether any of it is actually written down. That last question leads to what Brittany finds most underestimated, which is language itself. Being on time, she notes, can mean leaving the dock to one team and reaching the customer to another, and AI cannot reconcile a definition that people have never agreed on. This is why she puts such weight on a single source of truth. Consistent data definitions, documented exceptions, and shared context are what let a team build trust, reduce rework, and prepare the ground before automation is switched on. Just as important, and far less often discussed, is the politics of change. Brittany asks two questions of every process: who gains power if it is standardized or automated, and who loses it. The first reveals a natural champion. The second reveals the person most likely to slow things down, and she reads withheld information and dragging feet as signs of exactly that. When the resistance outweighs what a project can overcome, she takes it as a cue to redirect her energy elsewhere. Brittany is also reassuring about the fear underneath that resistance. AI, she insists, belongs in the second chair, not the first. It will suggest a course confidently and sometimes be confidently wrong, which is why a human must stay accountable for every decision, approval, and exception. The real risk she sees is not the technology but the person who trusts it more than their own judgment and waves work through without reading it. When colleagues feel exposed, she reframes the change as something that lets them handle more, not something that erases their value. Asked how she balances speed with thoroughness, Brittany describes a patient crawl, walk, run approach, one bite of the elephant at a time. Her team automates a single painful workflow first, works to earn a positive reaction to it, and only then scales to the next phase. Adoption cannot be forced, she stresses; a technically flawless project still fails if people push back. It is a fitting throughline for someone who counts standardizing her own role until she was replaceable as a point of pride, then carrying the same playbook somewhere new. Throughout, Jamie keeps the spotlight on Brittany and the human ingredients that decide whether AI succeeds, which reach well beyond prompt engineering. To learn more about Brittany’s work, visit NFI Industries at nfiindustries.com and connect with her on LinkedIn.