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The Manufacturers Network

Lisa Ryan

The Manufacturers’ Network is where manufacturing leaders, plant managers, and industry innovators come to talk straight about what’s working and what’s not, on the shop floor and beyond.

Each week, host Lisa Ryan sits down with people who live and breathe this business: operations executives, HR directors, engineers, and founders who are building stronger teams and smarter systems in the face of nonstop change.

Listeners gain real-world insights on:
• Employee retention and workforce engagement
• Automation, AI, and the future of skilled trades
• Supply chain and operations leadership
• Safety, sustainability, and company culture that lasts

If you’re tired of generic “leadership talk” and want practical conversations from people who get it, this podcast is for you.

New episodes drop every Monday and are short enough for your commute, sharp enough to shape your week.

Subscribe and be part of the conversation that’s connecting manufacturers across industries, one story at a time.

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  • 29 episodes
  • weekly
  • Avg 28 min
  • English

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  • S5 · E35
    Thursday · 28 min

    Manufacturing Leadership: How Culture, Accountability, and AI Drive Growth with Tim Beatty

    What happens when a manufacturer nearly quadruples its revenue without quadrupling its workforce? And how can manufacturing leaders introduce robotics and artificial intelligence while actually improving employee engagement, quality, and morale? In this episode of The Manufacturers Network Podcast, host Lisa Ryan welcomes Tim Beatty, President of Bullen Ultrasonics, a third-generation, family-owned precision manufacturing company specializing in machining ceramics, glass, and other advanced materials. Tim shares how Bullen Ultrasonics transformed its manufacturing operations by combining a people-first workplace culture, stronger accountability, robotic automation, continuous improvement, and emerging AI technology. The results? Record sales, profits, quality, efficiency, and employee morale, along with an employee engagement score that increased from approximately 83% to 90%. But the most interesting part of Bullen's transformation isn't just the technology. It's how the company created opportunities for employees to develop new skills, contribute innovative ideas, and grow into positions that might otherwise have required outside hiring. For manufacturing executives navigating workforce shortages, automation investments, employee retention, and AI adoption, this conversation offers practical lessons from a manufacturer putting these strategies into action. What You'll Learn in This Episode 1. How Manufacturing Culture and Accountability Work Together Many manufacturing leaders worry that increasing accountability will damage employee morale. Tim discovered that the opposite can happen when accountability is introduced thoughtfully. At Bullen Ultrasonics, leadership began by examining how employees interacted with one another and how managers demonstrated accountability themselves. Tim describes workplace culture as the sum of the quality of daily interactions throughout an organization. By combining supportive leadership with clear expectations, the company strengthened its culture while improving operational performance. Key insights: Why accountability should begin with leadership How support and challenge can coexist Why respectful workplace interactions influence manufacturing performance How the Entrepreneurial Operating System (EOS) helped connect company objectives to individual employee responsibilities What manufacturing leaders can learn from Bullen's improvement in employee engagement from approximately 83% to 90% 2. Using Robotics and Automation Without Replacing Manufacturing Employees How should manufacturers decide which production processes to automate? Tim explains how Bullen Ultrasonics invested in robotic automation to address labor shortages, improve workplace safety, reduce errors, and increase production efficiency. Rather than approaching automation as a way to eliminate positions, the company focused on helping its existing workforce accomplish more. One example involved automating the handling of heavy, complicated tooling that previously required significant manual effort. Robots now perform demanding loading and machining sequences while experienced employees focus on troubleshooting, inspections, preventive maintenance, and maintaining production quality. Tim also explains how connected inspection equipment, grinding machines, and ultrasonic machining systems exchange information and automatically adjust manufacturing parameters. Key insights: How to identify manufacturing processes suitable for robotic automation Why highly customized work still requires skilled human judgment How automation can improve employee safety and manufacturing quality Why communicating the purpose of automation helps build employee trust How employee profit sharing connects productivity improvements with workforce benefits 3. How to Build a Manufacturing Culture of Continuous Improvement Bullen employees submitted more than 120 continuous improvement ideas in a single year. Tim explains how the company encourages employees at every level to identify problems, recommend solutions, and participate in improving manufacturing operations. Ideas are documented during department meetings, tracked through monday.com, and evaluated by engineering teams. One employee-generated idea led to a redesign of a machine component that significantly reduced the use of a critical raw material. The employee worked directly with designers, participated in 3D printing and testing, helped implement the improvement, and monitored the results. Key insights: How to encourage frontline manufacturing employees to submit improvement ideas Why employees need feedback about what happens to their suggestions How engineering teams can collaborate with production operators Why recognizing employee ingenuity strengthens ownership and engagement How continuous improvement supports manufacturing efficiency and cost reduction 4. Why Manufacturers Must Learn to Fail Fast Without Sacrificing Quality Innovation requires experimentation, but manufacturing customers depend on consistent quality and reliable processes. Tim explains how Bullen Ultrasonics separates experimentation from established production processes. The company documents and protects approved manufacturing processes, which Tim compares to following a trusted family recipe. New ideas are tested outside production, allowing engineers and employees to identify potential failures before implementing changes that could affect customers. Key insights: How manufacturers can encourage innovation while protecting customer quality Why production processes must be documented and consistently followed How early testing can reduce expensive engineering mistakes Why employees should feel comfortable reporting errors instead of hiding them How learning from failure can accelerate manufacturing innovation 5. Developing Manufacturing Talent Through Internal Career Pathways With specialized equipment and a limited local labor market, Bullen Ultrasonics cannot rely exclusively on hiring experienced employees from outside the company. Instead, the manufacturer has made internal employee development a priority. Tim describes technical career pathway presentations that introduce employees to opportunities in engineering, business intelligence, and other specialized roles. The company also launched a junior engineering program in partnership with Ivy Tech, providing employees with opportunities to pursue technical education and potentially advance into engineering positions. Bullen offers full tuition reimbursement and has promoted employees from entry-level roles into technical and leadership positions. One employee began in facilities-related work and shipping and receiving before eventually becoming a controls engineer. Key insights: How internal career development can support manufacturing employee retention Why technical training matters as manufacturing technology changes How manufacturers can build their own engineering talent pipeline Why employee development should be part of automation planning How career mobility helps manufacturers retain institutional knowledge 6. Practical Applications of Artificial Intelligence in Manufacturing Artificial intelligence is often discussed as a transformative manufacturing technology, but Tim explains how Bullen is approaching AI through specific operational challenges. The company's connected manufacturing equipment has collected approximately two billion data points. Bullen is using that information to develop a proprietary AI system capable of identifying and helping solve complex manufacturing problems. Tim describes an early application in which AI helped develop a self-correcting algorithm for a manufacturing issue that had previously been difficult to identify. Rather than implementing AI simply because the technology is available, Bullen begins with problems that require better solutions. Key insights: How manufacturers can identify meaningful AI use cases Why connected equipment and manufacturing data create opportunities for process improvement How AI can support quality control and automated process correction Why experienced operators remain important in increasingly automated factories How manufacturing leaders can combine human expertise with machine intelligence Key Takeaways for Manufacturing Leaders The conversation with Tim Beatty demonstrates that successful manufacturing transformation requires more than investments in new equipment. It requires a leadership strategy that connects operational performance with employee development. Manufacturers can strengthen performance by creating accountability without sacrificing respect, involving employees in continuous improvement, using automation to support rather than simply replace workers, and developing internal career pathways that preserve valuable knowledge. Perhaps most importantly, Tim's experience illustrates why AI adoption should begin with a clearly defined manufacturing problem, not simply the desire to implement new technology. For manufacturing leaders facing labor shortages, rising production demands, and rapid technological change, Bullen Ultrasonics offers an example of how operational excellence and a people-first culture can reinforce one another. About Tim Beatty Tim Beatty is President of Bullen Ultrasonics, a family-owned manufacturer specializing in precision machining of ceramics, glass, and specialty materials. Tim began his career with the company in 1999, working in customer service before helping establish and manage its manufacturing operations in China. After working through a business transition and pursuing other professional interests, Tim returned to the family business as president in 2014. His leadership focuses on manufacturing innovation, employee engagement, operational accountability, workforce development, robotic automation, and the application of artificial intelligence to complex manufacturing challenges. Under his leadership, the company has experienced significant revenue growth, strengthened employee engagement, and achieved record operational performance. Connect with Tim Beatty and Bullen Ultrasonics Tim Beatty President, Bullen Ultrasonics LinkedIn: Search for Tim Beatty and Bullen Ultrasonics on LinkedIn. Tim regularly shares updates on manufacturing technology, employee development, and innovations within the company. About Your Host, Lisa Ryan Lisa Ryan, CSP, is a manufacturing keynote speaker, author, and host of The Manufacturers Network Podcast. Through her company, Grategy®, Lisa helps manufacturers strengthen workplace culture, retain experienced employees, develop better leaders, and prepare their people for AI and automation without losing the human judgment and critical knowledge that keep operations running. She is the author of Smart Plant™: Why Human Leadership Still Matters in an Automated World. Through keynote presentations, leadership training, and consulting, Lisa helps manufacturing organizations connect technological advancement with the people who make that technology successful. Connect with Lisa Ryan: Website: https://lisaryanspeaks.com LinkedIn: https://www.linkedin.com/in/asklisaryan/ Speaking and consulting inquiries: https://bookme.name/Grategy About The Manufacturers Network Podcast The Manufacturers Network Podcast features conversations with manufacturing executives, industry innovators, and leadership experts who are shaping the future of manufacturing. Hosted by Lisa Ryan, CSP, the podcast explores manufacturing leadership, employee retention, workplace culture, automation, artificial intelligence, workforce development, continuous improvement, and the human side of industrial transformation. Each episode provides practical insights and real-world examples to help manufacturing leaders build stronger teams, improve performance, and prepare their organizations for the future. Subscribe to The Manufacturers Network Podcast for more conversations about the people, leadership strategies, and innovations driving manufacturing forward.

  • S5 · E34
    Monday · 22 min

    Why Manufacturers Can’t Find Workers: Fixing the Frontline Recruiting Process with Sam Beiler

    TL;DR Manufacturers struggling to hire frontline workers may not have an applicant problem. They may have a recruiting process problem. Sam Beiler, co-founder and CEO of Boostpoint, joins Lisa Ryan to break down how manufacturers can reach machine operators, welders, CNC machinists, maintenance technicians, warehouse employees, and other frontline workers who aren't actively searching job boards. They discuss social media recruiting, passive candidates, pay transparency, applicant screening, text-message follow-up, interview no-shows, and why speed matters once someone applies. The big takeaway: Before spending more money to generate applicants, make sure your recruiting process can convert the applicants you already have. Episode Description “We can't find people.” Manufacturers have been saying it for years. But what if the problem isn't simply a shortage of workers? In this episode of The Manufacturers Network Podcast, Lisa Ryan talks with Sam Beiler, co-founder and CEO of Boostpoint, about what manufacturers may be missing when recruiting frontline and skilled-trades employees. Sam grew up around a small- to midsize manufacturing business before building his expertise in social media advertising and recruitment marketing. That combination gives him an interesting perspective on the hiring problem: Manufacturers are often trying to recruit today's workforce using channels and processes built for a different kind of job seeker. Reaching Frontline Workers Beyond Traditional Job Boards Job boards can reach active candidates who are already looking for work. But many potentially strong employees already have jobs and aren't spending their evenings searching Indeed, LinkedIn, or ZipRecruiter. They are spending time on social media. Sam explains how platforms such as Facebook and Instagram can put manufacturing job opportunities in front of passive candidates, including CNC machinists, welders, machine operators, maintenance technicians, and warehouse employees who might consider a better opportunity even though they aren't actively job hunting. The goal isn't to abandon job boards. It's to stop relying on a single recruiting channel to reach everyone. Why More Applications Don't Automatically Mean Better Hiring Generating applicants is only the beginning. Manufacturers also need to look at cost per qualified candidate, candidate quality, response time, interview show rates, and what actually happens after someone raises their hand. Sam also discusses how AI-assisted job applications are adding more noise to the recruiting process. Candidates can apply to far more positions with far less effort, which makes the employer's process increasingly important. Getting 100 applications isn't much of a win if nobody has a good system for turning the right applicants into conversations, interviews, and hires. How Quickly Should You Respond to a Manufacturing Job Applicant? As quickly as possible. The longer an employer waits to contact an applicant, the harder that person can be to reach. Sam recommends automating the first text message so candidates receive an immediate response while the opportunity is still fresh. That doesn't mean handing the entire recruiting process over to automation. Use technology for speed. Then get a human involved. For manufacturers competing for skilled workers, waiting several days to contact a qualified applicant can mean losing that person before the conversation ever starts. What Should Manufacturers Put in a Job Ad? What does a frontline candidate want to know when a job opportunity appears in their social media feed? Pay. Location. Benefits. Sam explains why manufacturers shouldn't bury that information beneath paragraphs about company history or generic descriptions of the organization. Give candidates enough information to determine whether the opportunity fits their lives. Additional context can come later. Lisa and Sam also discuss pay transparency and why clearly communicating compensation can save time for both employers and candidates. Qualify Candidates Before You Add More Noise More applicants aren't necessarily better applicants. For manufacturing positions requiring specific skills or experience, employers can use screening questions early in the application process. If a welding position requires two years of previous experience, for example, that requirement can be addressed before a recruiter spends time pursuing someone who doesn't qualify. Done well, screening makes the process easier for both the employer and the applicant. Social Media Recruiting vs. Job Boards The choice isn't necessarily Facebook versus Indeed. Sam recommends thinking about two different candidate populations. Traditional job boards help employers reach active job seekers. Social media can help manufacturers reach passive candidates who aren't currently searching for another job. A stronger manufacturing recruiting strategy may use both instead of expecting one channel to solve the entire hiring problem. Before You Spend More Money on Recruiting, Fix the Process One of the most useful takeaways from the conversation comes down to a simple question: What happens if 50 qualified candidates show up tomorrow? Who contacts them? How quickly? How are they screened? What happens next? Who owns the process? When a plant needs people, the immediate reaction is often to spend more money generating applicants. But if those questions don't have clear answers, more recruiting spend may simply pour more candidates into a broken system. Before increasing the recruiting budget, examine what happens to every applicant you're already receiving. In This Episode, You'll Learn • Why manufacturers may be solving the wrong recruiting problem • The difference between active and passive job seekers • Where frontline and skilled-trades candidates spend time online • How Facebook and Instagram recruiting can reach manufacturing workers • Why cost per qualified applicant matters more than raw application volume • Why candidates disappear or don't show up for interviews • How quickly employers should respond after someone applies • How automated text messages can improve the first recruiting touchpoint • Why automation shouldn't replace the human conversation • How to screen candidates before the interview • What hourly workers want to see in manufacturing job ads • Why pay, location, and benefits should be easy to find • How pay transparency is changing recruiting • When social media recruiting makes sense versus traditional job boards • How manufacturers can build a more repeatable recruiting system • What to examine before increasing your recruiting budget About Sam Beiler Sam Beiler is the co-founder and CEO of Boostpoint, a recruitment marketing platform that helps employers reach frontline workers through social media. His background combines manufacturing with years of experience in social media advertising and marketing. Boostpoint helps organizations use platforms including Facebook and Instagram to reach and recruit frontline employees. Learn more about Boostpoint at Boostpoint.com. You can also connect with Sam Beiler on LinkedIn or reach him directly at sam@boostpoint.com. About The Manufacturers Network Podcast The Manufacturers Network Podcast, hosted by Lisa Ryan, CSP, features conversations with manufacturing leaders and industry experts about the people, technology, leadership, and workforce challenges shaping manufacturing. From employee retention and frontline leadership to AI, automation, recruiting, knowledge transfer, workplace culture, and the skilled workforce, the show focuses on practical ideas manufacturers can actually use. Topics Manufacturing recruiting, frontline recruiting, manufacturing workforce, skilled trades recruiting, manufacturing hiring, social media recruiting, recruiting manufacturing employees, CNC machinist recruiting, welder recruiting, passive candidates, Facebook recruiting, Instagram recruiting, manufacturing job ads, employee recruitment, pay transparency, applicant screening, recruiting automation, AI job applications, recruiting process, manufacturing labor shortage, frontline workers, skilled workforce, employee hiring, manufacturing HR

  • S5 · E33
    November 2 · 24 min

    You Bought It. Why Aren’t They Using It? with Rich Thomas

    Your company bought the equipment. Paid for the program. Made the benefit available. So why aren’t employees using it? That question shows up everywhere in manufacturing, from PPE and safety programs to training, technology, employee benefits, and tools. And sometimes the problem isn’t the employee. It’s the way the program was designed, introduced, communicated, or reinforced. In this episode of The Manufacturers’ Network Podcast, Lisa Ryan talks with Rich Thomas, co-founder of CHAOS Supplies, about what more than 30 years in industrial supply and thousands of prescription safety eyewear users have taught him about employee adoption, workplace safety, and the friction that keeps good programs from actually working. Rich has spent his career supplying safety products to tire and automotive service organizations, manufacturers, utilities, and field crews. His experience with employer-paid prescription safety eyewear programs provides a surprisingly useful case study in a much bigger manufacturing leadership question: Why do employees ignore something that was specifically provided to help them? The answer often has less to do with employee resistance than leaders think. The central takeaway: If employees aren’t using a program, benefit, tool, or piece of safety equipment, don’t immediately assume you have an employee problem. Look for friction in the system. Employees are far more likely to adopt something when it fits their needs, is easy to use, is reinforced by their managers, and is part of the normal way work gets done. Why Employees Don’t Always Use the PPE You Give Them Safety glasses sound pretty straightforward. Buy them. Put them on. Protect your eyes. Except humans have this annoying habit of being human. Rich explains that style, comfort, and fit are major reasons employees may avoid wearing safety eyewear, including prescription safety glasses. Glasses that fog up, slide down, pinch, feel cumbersome, or make it difficult to see can create enough friction that employees simply stop wearing them. That creates an important distinction for manufacturing leaders: availability isn’t adoption. An employer can technically provide PPE and still have a workforce that isn’t consistently using it. The same principle applies far beyond safety glasses. Companies spend money on training platforms nobody logs into, benefits employees barely understand, software people work around, tools that stay in the crib, and safety programs that look terrific on paper. Buying something is the easy part. Getting people to use it consistently is where leadership begins. Is It an Employee Problem or a System Problem? When a program isn’t being used, it’s tempting to blame the people. Rich challenges that assumption. If employees aren’t wearing required safety glasses and management routinely allows it, the organization has helped create that norm. A written safety policy matters, but employees also watch what supervisors tolerate, what coworkers actually do, and what happens when someone ignores the rules. Lisa connects this to the difference between policies and norms. The policy may say safety glasses are required beyond a certain point on the plant floor. But if employees routinely walk past that point without them and nobody says anything, the real rule becomes obvious: We say you have to wear them, but apparently you don't. Until somebody gets hurt. Then suddenly everybody cares again. That gap between the written policy and everyday behavior is where safety culture is actually created. Start With the People Who Are Using It One of Rich’s most practical recommendations is refreshingly simple. If you want to understand why employees aren’t using something, start by talking to the employees who are. What works for them? Why do they use it? What do they like about it? Then talk to the people who aren’t using it. Maybe the glasses slide off their face. Maybe they’re too tight and cause headaches. Maybe they fog up. Maybe the employee doesn’t know a prescription eyewear benefit exists. Maybe nobody explained how to get it. That information is far more useful than sitting in a conference room deciding employees “just don’t care about safety.” Rich points out that one-size-fits-all safety glasses don’t actually fit everyone. Lisa takes the point further: one size fits all doesn’t work particularly well for much of anything in the workplace. It doesn’t work for PPE, recognition, training, or many of the other programs companies expect employees to embrace. Safety Culture Is What Happens When Nobody Is Watching Manufacturing safety culture isn’t created by posters, policies, or an annual training session alone. It shows up in everyday behavior. If one employee sees a coworker operating equipment without the proper eye protection, do they feel comfortable saying something? Can a coworker say, “Dude, you gotta put your safety glasses on,” without it becoming a confrontation? Lisa and Rich discuss how psychological safety can support physical safety. Employees need to know that speaking up about unsafe behavior is part of looking out for each other rather than policing each other. That changes the conversation from “Wear these because OSHA says so” to “Wear these because we’d really like you to go home with the same number of functioning eyeballs you brought to work.” That’s a different kind of safety culture. PPE Compliance Gets Easier When the PPE Actually Works Employees are more likely to use protective equipment when it doesn’t make their job harder. Rich discusses prescription safety eyewear that employees can wear throughout the workday rather than constantly switching between regular glasses and safety glasses. He also explains why anti-fog properties, fit, comfort, and style can affect whether employees keep their glasses on. That raises a useful question for any manufacturing leader evaluating PPE or another employee program: Are employees resisting the program, or are they resisting unnecessary friction? Those are two very different problems. Near Misses Aren’t Proof the System Worked The conversation also turns to near misses and the danger of treating “nobody got hurt” as proof that everything is fine. Sometimes nobody got hurt because the safety system worked. Sometimes nobody got hurt because they got lucky. Lisa shares the example of a former colleague in the welding industry who lost an eye when a bungee cord snapped. Rich shares a near miss from welding when a spark traveled inside his helmet and came dangerously close to his eye. Those experiences reinforce why eye protection and other forms of PPE can’t become something employees think about only after an incident. Near misses should create conversations before luck runs out. Make Safety Visible Without Making It Miserable Rich suggests that manufacturers make safety initiatives visible, positive, and even fun instead of introducing them as another compliance mandate. Lisa, naturally, immediately goes to a safety-glasses fashion show. And why not? If one reason employees avoid safety glasses is that they still picture the ugly, clunky shop glasses they wore decades ago, showing them better options can change perceptions. A launch, demonstration, employee challenge, safety month, or yes, even a ridiculous runway through the shop can get employees talking about the program. The point isn’t the gimmick. The point is making the desired behavior visible enough that it starts becoming normal. Key Questions Answered in This Episode Why don’t employees always use PPE their employer provides? How can manufacturers increase safety-glasses compliance? What causes employees to stop wearing prescription safety eyewear? How do comfort, fit, style, and anti-fogging affect PPE adoption? How can plant managers tell whether they have an employee problem or a system-design problem? What’s the difference between a written safety policy and the actual safety norms on the plant floor? How can manufacturers create a stronger workplace safety culture? Why should leaders talk to employees before buying or rolling out new programs? How can psychological safety support physical safety? What can near misses teach manufacturing teams about risk? How can manufacturers improve employee adoption of programs, tools, training, and benefits? What Manufacturing Leaders Can Do This Week Don’t start by asking why employees aren’t complying. Start by watching what’s actually happening. Find employees who consistently use the PPE, tool, training, benefit, or program you’re evaluating and ask what works for them. Then find employees who don’t use it and ask what gets in the way. You may discover a motivation problem. You may also discover something much easier to fix: poor fit, confusing communication, an inconvenient process, lack of awareness, inconsistent supervisor behavior, or a program designed without enough input from the people expected to use it. That’s useful information. In This Episode, You’ll Learn Why providing PPE doesn’t guarantee employees will use it How comfort, style, fit, and usability influence safety compliance Why prescription safety eyewear can improve the employee experience How managers unintentionally create unsafe workplace norms Why employee adoption problems may actually be system-design problems How frontline conversations reveal friction leaders may never see Why one-size-fits-all approaches fail in safety, training, and other workplace programs How near misses can reveal risks before someone gets hurt Why consistent management behavior matters to manufacturing safety culture How manufacturers can make safety initiatives more visible and engaging What plant managers can look for when an employee program isn’t getting used About Rich Thomas Rich Thomas co-founded CHAOS Supplies in Phoenix, Arizona, and has more than 30 years of experience in industrial supply. His company serves tire and automotive service organizations, manufacturers, utilities, and field crews with safety-related products and industrial supplies. Rich has developed particular expertise in prescription safety eyewear programs and has studied years of program usage to better understand what drives employee adoption and what gets in the way. His work focuses on helping employers make eye protection easier, more comfortable, and more practical for the people expected to wear it. Connect with Rich Thomas Learn more about Rich and prescription safety eyewear programs at CHAOS RX Optics. Website: CHAOSRXOptics.com Topics and Keywords Manufacturing safety, workplace safety, safety culture in manufacturing, PPE compliance, personal protective equipment, prescription safety glasses, prescription safety eyewear, industrial safety glasses, eye protection, OSHA safety, ANSI safety glasses, employee safety, manufacturing PPE, PPE adoption, employee adoption, safety program implementation, manufacturing leadership, plant managers, frontline supervisors, psychological safety, physical safety, workplace norms, safety policies, near misses, eye injury prevention, industrial supply, employee training, manufacturing training, safety training, workplace compliance, safety program participation, system design, employee behavior, manufacturing workforce, automotive service safety, utility worker safety, welding safety, industrial eye protection, PPE fit and comfort, anti-fog safety glasses. About The Manufacturers’ Network Podcast The Manufacturers’ Network Podcast, hosted by Lisa Ryan, CSP, features practical conversations with manufacturing leaders, experts, and practitioners about the issues affecting the industrial workforce. Topics include manufacturing leadership, AI and automation, human judgment, employee retention, knowledge transfer, workforce development, workplace culture, employee engagement, safety, and the future of manufacturing. Lisa Ryan is a manufacturing keynote speaker, author of Smart Plant: Aligning AI, Automation, and People, and founder of Grategy. Her work helps manufacturing leaders prepare their people for AI and automation while protecting the human judgment, critical knowledge, and workplace practices their operations depend on. Because sometimes the problem isn’t getting employees to comply. It’s figuring out what’s making the right behavior harder than it needs to be.

  • S5 · E32
    October 26 · 25 min

    When the Data Says One Thing and Your Operator Says Another with Michael Dorman

    What happens when your digital record says one thing, but the experienced operator standing on the plant floor says something else? Who do you trust? As manufacturers invest in AI, automation, digital twins, sensors, and increasingly sophisticated data systems, that question will matter a lot more. Technology can capture an extraordinary amount of information about a manufacturing facility. But data doesn’t automatically replace the experience of the people who know what’s behind the walls, where the undocumented repair was made, why that machine was moved six years ago, or when something simply doesn’t look right. In this episode of The Manufacturers’ Network Podcast, Lisa Ryan talks with Michael Dorman, co-founder and CFO of Primera Works, about what happens at the intersection of manufacturing data, facility knowledge, technology, and human judgment. Michael brings more than 27 years of experience in reality capture, LiDAR, building information modeling (BIM), digital twins, construction documentation, and technology for the built environment. Together, Lisa and Michael explore what technology can preserve, what still lives in the heads of experienced employees, and what manufacturers risk losing when those people walk out the door. The central takeaway: Manufacturing technology works best when accurate facility data and experienced human judgment work together. Digital twins, BIM, LiDAR, AI, and automation can preserve and organize information, but manufacturers still need experienced employees who can interpret that information, challenge it when something doesn’t look right, and add the institutional knowledge that technology alone can’t capture. Manufacturers are investing heavily in AI, automation, sensors, digital twins, and data systems. But more technology doesn’t automatically create better institutional knowledge. If the underlying information is incomplete, outdated, locked inside proprietary systems, or disconnected from what experienced employees know, technology can simply make bad information easier to access. And there’s another problem: employees may be reluctant to share decades of hard-earned knowledge when “knowledge transfer” sounds suspiciously like “teach us everything you know so we can replace you with somebody cheaper.” Lisa and Michael discuss why psychological safety matters in knowledge transfer and how leaders can change that conversation. Instead of treating experienced employees as databases waiting to be downloaded, organizations can position knowledge capture around legacy, expertise, and making the operation stronger for the people who come next. When Experience Challenges the System One of the most important questions in the episode is simple: If the digital record says one thing and the experienced employee standing on the plant floor says another, who wins? Michael’s answer is clear: experience still matters. The goal isn’t to choose between technology and people. It’s to reduce the gap between what the system says and what experienced people know by giving employees relevant, accurate information they can actually use. That becomes increasingly important as manufacturers adopt artificial intelligence, automation, digital twins, BIM, reality capture, and other Industry 4.0 technologies. A sophisticated system isn’t automatically a useful system. Michael points out that manufacturers can invest in technology packed with functionality while employees use only a fraction of it. Lisa brings that down to a much more practical starting question for plant leaders: “What sucks about your job? How can we make it better?” Sometimes the smartest digital transformation strategy starts there. The Knowledge Hidden Inside Your Facility Institutional knowledge isn’t limited to how employees run equipment or make the product. Experienced maintenance technicians, operators, engineers, facilities leaders, and other longtime employees may know: what’s actually behind the walls where repairs and modifications were made which drawings and as-builts are no longer accurate why equipment was moved or changed which workarounds became part of everyday operations what has changed since the facility was originally designed which conditions matter even though they were never formally documented When those employees retire or leave, that knowledge can disappear with them. Michael explains why manufacturers need an ongoing process to document and digitize facility conditions, rather than treating reality capture or BIM as a one-time project. Plants change. Equipment changes. Processes change. Even seemingly minor facility changes can eventually matter to maintenance, safety, construction, risk management, and future capital projects. A Digital Twin Doesn’t Need to Be Rocket Science Digital twin has become one of those phrases that can mean almost anything depending on who’s selling it. Michael offers a much more practical definition: determine which information the owner actually cares about and which needs to move from the physical environment to the digital environment. That’s the digital twin that matters. Manufacturers don’t necessarily need the most sophisticated model available. They need accurate facility information that employees can understand, trust, update, and use. For organizations beginning this process, Michael recommends starting with something far less glamorous than AI: Accurate as-built information. If you don’t have reliable drawings of your current facility, start there before worrying about creating an elaborate 3D digital environment. Human Judgment Still Has a Job Technology can capture enormous amounts of information. It can speed up decisions, organize data, create digital representations of physical environments, and make facility information easier to retrieve. But it doesn’t eliminate the value of experience. That matters when an operator notices something that doesn’t look right, a maintenance technician knows the drawing doesn’t reflect reality, or an experienced employee challenges what the system is telling them. Lisa connects this to another manufacturing leadership problem: the employee who stops a machine because something feels wrong takes a visible risk. If they’re wrong, everyone sees the downtime. If they’re right and prevent a failure? Nothing happens. Nobody walks through the plant announcing, “Hey, at 2:17 this afternoon, nothing happened.” That’s exactly why manufacturers need cultures where employees are willing to speak up, question the data, report near misses, and use their judgment instead of automatically deferring to the system. Facility Data Is Also a Business Risk The conversation also explores the connection between accurate facility information and capital expenditure, construction, safety, and operational risk. When manufacturers build, expand, renovate, or modernize facilities, owners often rely heavily on architects, engineers, contractors, and technology vendors to manage information. Michael argues that manufacturers need to take ownership of the data they expect to retain. After all, when the project ends, the manufacturing company is the one left operating the facility. Clear data specifications, accurate documentation, current as-builts, and usable asset information can help manufacturers protect the long-term value of their capital investments and reduce the risk of having to reconstruct their own facility history years later. Key Questions Answered in This Episode What should manufacturers do when data conflicts with an experienced operator’s judgment? What institutional knowledge is most likely to disappear when experienced manufacturing employees retire? What should manufacturers capture before creating a digital twin? How can manufacturers use AI and automation without losing human judgment? Why are accurate as-built drawings important for manufacturing facilities? How can BIM, LiDAR, and reality capture help preserve institutional knowledge? How can manufacturers encourage experienced employees to share what they know? Why does data quality matter when manufacturers invest in AI and automation? How can better facility information reduce risk during plant expansions and capital projects? In This Episode, You’ll Learn Why retiring employees can take critical facility knowledge with them How manufacturers can improve knowledge transfer without making experienced employees fear they’re documenting themselves out of a job Why psychological safety matters when capturing institutional and tribal knowledge What BIM, LiDAR, reality capture, and digital twins can preserve Where human judgment and experience still matter Why accurate data matters more than simply collecting more data How outdated as-builts create problems for maintenance, construction, safety, and capital projects Why manufacturers should own and specify the facility data they expect to retain How overly sophisticated technology can create more friction instead of more value Why plant leaders should start with the information employees actually need How manufacturers can begin documenting their physical facilities before experienced employees retire Why AI and automation work better when human expertise remains part of the decision-making process About Michael Dorman Michael Dorman is co-founder and CFO of Primera Works and has more than 27 years of experience in reality capture, LiDAR, BIM, digital twins, construction documentation, and technology for the built environment. His career has included helping scale Multivista, working within Hexagon, and working with Leica Geosystems and scanning technologies used to create digital representations of physical environments. Today, his work focuses on helping owners better understand, retain, and use information about their facilities instead of losing valuable data during construction, renovation, technology implementation, or workforce transitions. Connect with Michael Dorman Michael welcomes conversations with manufacturers and facility owners looking to better understand and protect their facility data. Email: mdorman@primeraworks.com Phone/Text: 919-802-0254 LinkedIn: Search for Michael S. Dorman at Primera Works Topics and Keywords Manufacturing knowledge transfer, institutional knowledge, tribal knowledge in manufacturing, manufacturing workforce retirement, skilled workforce knowledge loss, human judgment in manufacturing, AI in manufacturing, artificial intelligence in manufacturing, manufacturing automation, Industry 4.0, smart manufacturing, digital transformation in manufacturing, digital twins for manufacturing, building information modeling, BIM for manufacturing facilities, LiDAR scanning, reality capture, plant documentation, facility management, manufacturing facility data, as-built drawings, manufacturing construction, plant expansion, capital projects, CapEx risk, asset information management, operational risk, manufacturing safety, near-miss reporting, psychological safety in manufacturing, maintenance knowledge transfer, manufacturing leadership, workforce development, plant managers, operations leaders, facilities managers, maintenance leaders, manufacturing technology, industrial AI, human-in-the-loop decision making, experienced workers, retiring manufacturing workforce, data quality, manufacturing data strategy. About The Manufacturers’ Network Podcast The Manufacturers’ Network Podcast, hosted by Lisa Ryan, CSP, brings manufacturing leaders, experts, and practitioners together for practical conversations about the issues affecting the industrial workforce, including AI and automation, human judgment, knowledge transfer, leadership, employee retention, workforce development, workplace culture, and the future of manufacturing. Lisa Ryan is a manufacturing keynote speaker, author of Smart Plant: Aligning AI, Automation, and People, and founder of Grategy. Her work helps manufacturing leaders prepare their people for AI and automation while protecting the human judgment and critical knowledge their operations still depend on. Because the smartest plant in the world still needs people who know when something isn’t right.

  • S5 · E31
    October 19 · 28 min

    Industry 4.0: How Manufacturers Can Combine AI, Lean and Human Expertise with Mike Ungar

    How can manufacturers adopt AI, automation, and Industry 4.0 technology without leaving their people behind or investing in technology that doesn’t solve the right problems? In this episode of The Manufacturers Network Podcast, Lisa Ryan talks with Mike Ungar, CEO of the Industry 4.0 Club and a FocalPoint Master Business and Executive Coach, about smart manufacturing, Lean, AI adoption, workforce knowledge transfer, frontline engagement, and the leadership required to make digital transformation stick. Mike spent nearly five years in the Army and 35 years with Michelin in continuous improvement, operations, finance, and HR. Today, he helps manufacturing leaders connect technology investments with business strategy and the people responsible for making those investments work. What Is Industry 4.0? Industry 4.0 brings together smart manufacturing, data analytics, connected technology, and people to improve manufacturing performance. Mike explains that many of the principles aren’t new. Lean manufacturing has long focused on eliminating waste, using data, solving problems, and engaging employees. What has changed is the technology available to do those things faster and more effectively. Connected systems and AI can capture information that operators once recorded manually, freeing experienced employees to provide context, troubleshoot problems, and use the human judgment technology can’t replace. Why Do Digital Transformations Fail? Mike identifies two differences between manufacturers making progress and those stuck in endless pilots: they engage their people, and they have a strategy. Technology shouldn’t be the strategy. Manufacturing leaders should begin with their business goals and then determine where AI, robotics, automation, analytics, digital twins, or other Industry 4.0 technologies can create value. How Do Lean Manufacturing and Industry 4.0 Work Together? Mike separates Lean into culture and tools. A strong Lean culture includes understanding customer needs, engaging employees, respecting standards, eliminating waste, and using visual management. Those principles don’t disappear when a plant becomes more digital. Technology expands the toolbox. The question is: What is the right tool for the problem we’re trying to solve? How Can Manufacturers Reduce Employee Resistance to AI? Employees may worry about AI, robotics, and automation changing or eliminating their jobs. Mike recommends giving people opportunities to experience AI and understand how it can help them before expecting them to embrace a major transformation. He also recommends starting with problems frontline employees want solved. Operators often know about “hidden problems” that don’t appear clearly in production reports: recurring interruptions, frustrating workarounds, inefficient tasks, and obstacles that make every shift harder. Solve one of those problems with technology and employees can experience its value firsthand. AI and Manufacturing Knowledge Transfer As experienced manufacturing employees retire, companies risk losing decades of troubleshooting knowledge and operational expertise. Instead of asking a 30-year employee to sit down and document everything they know, Mike explains how manufacturers can use voice recordings and AI-enabled tools to capture knowledge while experienced employees work. That knowledge can become a resource newer employees can use when troubleshooting equipment or learning a process. But capturing knowledge isn’t enough. Human judgment still matters. The next employee needs to recognize when the situation in front of them doesn’t match what the system describes. Mike and Lisa also discuss employees who may resist sharing what they know because they believe their knowledge provides job security. Mike emphasizes that leaders can’t suddenly expect trust at retirement if they haven’t built it throughout the employee’s career. Creating a culture where experience is respected and knowledge is valued has to start much earlier. In This Episode: • Industry 4.0, smart manufacturing, and AI adoption • Connecting technology investments to business strategy • Lean manufacturing and digital transformation • Frontline engagement in automation projects • Reducing workforce fear around AI and robotics • Finding hidden shop-floor problems • Capturing tribal knowledge before experienced workers retire • Using AI for manufacturing knowledge transfer • Why human judgment still matters in automated plants • Building trust with experienced employees • Preparing manufacturing workforces for continuous change • Why adaptability matters as manufacturing technology evolves For Mike, preparing manufacturing for the next three to five years starts somewhere less flashy than the latest AI platform: culture. Technology will keep changing. Manufacturers need people who can adapt, learn, solve problems, share what they know, and use technology without surrendering the human judgment that keeps operations running. Guest: Mike Ungar CEO, Industry 4.0 Club FocalPoint Master Business and Executive Coach #Manufacturing #Industry40 #SmartManufacturing #AIinManufacturing #LeanManufacturing #DigitalTransformation #Automation #ManufacturingLeadership #KnowledgeTransfer #HumanJudgment #ManufacturersNetwork

  • S5 · E30
    October 12 · 33 min

    Manufacturing Economic Outlook: Recession Risk, Tariffs, Labor, AI, and Supply Chains with Bill Conerly

    What should manufacturers prepare for as tariffs, labor shortages, AI, supply chain risks, and economic uncertainty reshape the industry? Economist Dr. Bill Conerly joins Lisa Ryan on The Manufacturers Network Podcast to break down the manufacturing economic outlook and the practical decisions manufacturing leaders should be making now. Bill does not currently see a recession ahead under his base-case assumptions, but that doesn't mean manufacturers shouldn't prepare for one. He explains how to build a recession contingency plan that goes beyond cutting costs and considers opportunities to gain customers, hire hard-to-find talent, acquire capabilities, and strengthen the business when competitors pull back. Lisa and Bill also explore how tariffs are changing supply chain decisions. The lowest-cost supplier isn't always the best choice when reliability is uncertain. Manufacturers need to understand where critical components come from, identify alternative suppliers, and consider where reshoring or domestic production may make economic sense. The labor conversation goes deeper than hiring. An aging workforce means manufacturers risk losing decades of knowledge as experienced employees retire. Bill and Lisa discuss the "silver tsunami," skilled labor shortages, stay interviews, employee retention, and why manufacturers need to preserve the knowledge experienced workers carry before it disappears. They also tackle AI in manufacturing. Bill suggests starting with individual processes where AI can remove repetitive work or improve information flow. Then, as the organization gains experience, ask a bigger question: If we designed this process from scratch with AI available, would we build it the same way? In this episode: • How manufacturers can prepare for recession risk without assuming one is coming • Why tariffs are changing the economics of supply chain resilience • Where reshoring opportunities may emerge • How workforce demographics are affecting manufacturing labor shortages • Why retiring workers create a critical knowledge-transfer challenge • How stay interviews can help manufacturers retain skilled employees • A two-step approach to evaluating AI investments in manufacturing • How an economic downturn can create opportunities to hire, acquire, and gain market share • Why manufacturing executives should focus on the economic indicators that actually affect their businesses instead of reacting to every headline • How aging business owners may create acquisition opportunities for manufacturers looking to grow The future can't be forecast perfectly. The better question is whether your manufacturing operation is prepared to respond when conditions change. #Manufacturing #ManufacturingLeadership #ManufacturingIndustry #Economy #AIinManufacturing #SupplyChain #Tariffs #Reshoring #Workforce #ManufacturersNetwork

  • S5 · E29
    October 5 · 32 min

    Manufacturing Traceability: Fighting Counterfeit Parts with AI | Roei Ganzarski

    What if every manufactured part could be identified and traced using nothing more than a photograph? In this episode of The Manufacturers Network Podcast, Lisa Ryan talks with Roei Ganzarski, CEO of Alitheon, about manufacturing traceability, counterfeit parts, quality control, AI, automation, and technology that gives physical objects something similar to their own unique fingerprint. Roei's background includes Boeing, aviation, software, electric aircraft, and manufacturing technology. Throughout his career, he kept encountering the same problem: manufacturers rely on paperwork, serial numbers, barcodes, QR codes, labels, and tags to prove that a physical part is the part everyone thinks it is. But what happens when the label falls off, a serial number is copied, a QR code is moved, or a counterfeit part looks almost identical to the original? Can a Manufactured Part Have a Fingerprint? Alitheon's technology, called FeaturePrint, uses photographs to identify individual physical items without adding a barcode, tag, sticker, RFID chip, or other marker. Manufacturing processes produce parts within allowable tolerances, but seemingly identical parts still have tiny physical differences. FeaturePrint uses those variations to create what Roei describes as "biometrics for things." That means a manufacturer can potentially identify whether a specific item has been seen before, trace it through production, or determine that an item isn't the one it claims to be. Counterfeit Parts Are a Manufacturing and Safety Problem Counterfeiting isn't limited to fake watches and designer bags. Roei discusses counterfeit and gray-market products involving pharmaceuticals, automotive brake pads and airbags, healthcare products, military components, and other high-consequence applications. For manufacturers, the risk extends in both directions. Incoming counterfeit tooling, components, filters, or materials can affect production and quality. Outgoing counterfeit products can create safety risks, warranty problems, financial losses, and damage to brand reputation and customer trust. Traceability Can Improve Manufacturing Quality Traceability becomes especially valuable when something goes wrong. Imagine parts begin drifting toward the edge of an acceptable tolerance. If individual parts can be traced through production, leaders may be able to identify what the affected parts have in common, such as a specific machine, production line, shift, or point in the process. The same principle applies when products come back for warranty claims or service. Instead of wondering whether there's a quality problem across the entire operation, better manufacturing traceability can narrow the investigation and give people better information for making decisions. AI, Automation and Industry 4.0 As manufacturers pursue Industry 4.0, smart factories, AI, and greater automation, Roei argues that companies need visibility into more than what their machines are doing. They also need reliable information about the physical products moving through those machines. Technology can provide data. Human beings still need to interpret it, question assumptions, investigate problems, and decide what to do. For Roei, that makes critical thinking increasingly valuable as factories become more automated and data-driven. How Should Manufacturers Evaluate AI Technology? Manufacturers are being flooded with AI pitches. Roei recommends asking practical questions before investing: • Does the technology solve an expensive, high-consequence problem? • Can the vendor demonstrate it live using your products? • Who owns the intellectual property behind the solution? • Is the AI proprietary technology or primarily built on someone else's platform? • Does it solve the physical problem or only manage the data around it? • What happens if the label, barcode, identifier, or underlying assumption is wrong? Roei also challenges manufacturers to distinguish between protecting data and protecting physical products. Blockchain may protect digital records, for example, but accurate data can still be connected to the wrong physical item if the identifier itself is compromised. In This Episode • Manufacturing traceability without barcodes, labels, or serial numbers • How digital fingerprints can identify individual manufactured parts • Counterfeit and gray-market risks in manufacturing • Quality control and product serialization • AI-powered physical item identification • Supply chain traceability and authentication • Warranty fraud and product returns • Industry 4.0 and smart manufacturing • Human judgment and critical thinking in automated factories • How manufacturers should evaluate AI vendors and technology investments • Why better data can help people make better manufacturing decisions As manufacturing becomes more automated, knowing what a machine did is only part of the story. Manufacturers also need confidence that the physical part in front of them is exactly the part they think it is. Guest: Roei Ganzarski CEO, Alitheon #Manufacturing #ManufacturingTechnology #AIinManufacturing #Traceability #CounterfeitParts #Industry40 #SmartManufacturing #QualityControl #SupplyChain #Automation #HumanJudgment #ManufacturersNetwork

  • S5 · E28
    September 28 · 31 min

    Manufacturing Insurance: The Coverage Gaps That Can Cost You with Michael Senderovich

    Your manufacturing business has insurance. But will it actually cover the risks your operation has today? In this episode of The Manufacturers Network Podcast, Lisa Ryan talks with Michael Senderovich, President of Six Thirteen Business Insurance Services, about insurance gaps small and mid-sized manufacturers may not discover until there's a claim. They discuss equipment coverage, workers' compensation, cyber liability, AI, automation, additional insureds, employment practices liability, and the questions manufacturers should be asking their insurance brokers. Is Your Manufacturing Equipment Properly Insured? Manufacturers may have significant investments in CNC machines, tooling, inventory, and equipment that has been operating for decades. Michael explains why understanding the difference between actual cash value and replacement cost matters. A 40- or 50-year-old machine may be essential to production, but replacing its capability after a major loss could be much more complicated than its depreciated value suggests. The problem gets worse when insurance policies simply renew year after year without anyone reviewing what has changed. Michael recommends an annual insurance review even when the business appears unchanged. Manufacturers should discuss new equipment, products, employees, facilities, storage configurations, processes, and other operational changes with their broker. AI, Automation and Cyber Risk in Manufacturing As manufacturers add AI, robotics, automation, and connected equipment, their risk profile changes. Michael identifies cyber liability as a major concern for connected manufacturing operations. Small and mid-sized manufacturers shouldn't assume they're too small to become ransomware or cyberattack targets. AI can create additional insurance questions. Depending on how AI is being used and what happens when an automated system makes an error, traditional general liability coverage may not respond the way a manufacturer expects. Professional liability or errors and omissions coverage may need to be considered depending on the operation. The takeaway: tell your insurance broker how you're actually using AI and connected technology. Don't assume an existing policy automatically covers a new risk. Workers' Compensation: What Should Manufacturers Do After an Injury? When an employee is injured on the job, Michael's advice is straightforward: act quickly. Take care of the employee, notify the insurance carrier promptly, document what happened, and preserve relevant evidence. Delays and poor documentation can make a workers' compensation claim more difficult. Manufacturers should also understand whether their workers' compensation limits and policy provisions match the actual risks employees face. Additional Insured Doesn't Mean Fully Insured Michael also explains a common source of confusion involving additional insured status. Being listed as an additional insured does not necessarily provide the broad protection a customer, supplier, contractor, or business partner may assume it does. Certificates of insurance also need to be managed and monitored rather than filed away and forgotten. That false sense of security can become expensive when a claim occurs. What Insurance Should Manufacturers Ask About? Beyond general liability and workers' compensation, Michael recommends manufacturers discuss coverage such as cyber liability and employment practices liability insurance (EPLI). EPLI can address claims involving employment practices such as wrongful termination or discrimination. Manufacturers need to understand where their policies leave them exposed before a claim tests the coverage. Questions to Ask Your Manufacturing Insurance Broker • What exclusions in our policies create our biggest vulnerabilities? • Is our equipment insured for actual cash value or replacement cost? • Have changes to our products, processes, machinery, facilities, or workforce changed our risk profile? • Does our cyber insurance reflect our use of AI, automation, and connected equipment? • Are our workers' compensation limits appropriate for our operation? • Are certificates of insurance and additional insureds being properly managed? • Should we carry employment practices liability insurance? • When was the last time our policies were reviewed against how we actually operate today? Manufacturing insurance isn't something to put on autopilot. Your operation changes. Your technology changes. Your equipment changes. Your risks change with them. The policy that worked five years ago may not protect the manufacturing business you're running today. Guest: Michael Senderovich President, Six Thirteen Business Insurance Services #Manufacturing #ManufacturingInsurance #RiskManagement #CyberSecurity #AIinManufacturing #Automation #WorkersCompensation #ManufacturingLeadership #CyberInsurance #EPLI #ManufacturersNetwork

  • S5 · E27
    September 21 · 33 min

    Manufacturing Leadership: Why Being Right Isn’t Enough with Jared Scott

    What happens when a manufacturing leader’s experience becomes the very thing keeping the operation from improving? In this episode of The Manufacturers Network Podcast, Lisa Ryan talks with Jared Scott, National Training Manager at SEW-EURODRIVE and author of Edge Over Ego: Why Being Right Isn’t Enough and What Actually Makes Leaders Effective, about manufacturing leadership, workforce development, technical training, AI, and the generational shift happening across the industry. Jared has worked in manufacturing since 1995, starting with hands-on industrial maintenance before moving into workforce training and leadership development. He has watched manufacturing change dramatically, but one challenge remains: experienced leaders can become so accustomed to how things are done that they stop noticing what could be better. That’s where ego gets expensive. Jared shares a story from early in his career when he found a simple way to grease tapered bearings more efficiently using a basketball needle. Instead of considering the idea, the experienced employee training him rejected it because Jared hadn’t “paid his dues.” It’s a great example of how manufacturers can lose good ideas, efficiency improvements, and employee engagement because experience becomes a reason to stop listening. Lisa and Jared discuss a question every manufacturing leader should consider when a new employee challenges an established process: What if they’re right? As manufacturers face skilled labor shortages, retiring experienced workers, AI adoption, automation, and rapidly changing technology, leaders can’t afford to confuse experience with infallibility. Jared describes the “boiled frog” problem in manufacturing. When you’ve worked inside the same operation for years, problems can become so familiar that you stop seeing them. The pothole everyone drives over. The inefficient process everyone works around. The machine problem everyone tolerates. The procedure nobody questions because “that’s how we’ve always done it.” New employees may notice those problems immediately because they haven’t learned to ignore them yet. Manufacturing leaders don’t have to implement every suggestion. They do need to create an environment where employees can question a process, offer an idea, or point out a problem without being dismissed because of tenure or job title. Human Judgment, AI and Manufacturing Lisa and Jared also explore what happens as artificial intelligence and automation become more prevalent in manufacturing. AI can increase capability, but manufacturers still need people who understand equipment, processes, troubleshooting, and what actually happens on the shop floor. At the same time, experienced workers are retiring with decades of practical manufacturing knowledge. Younger employees may enter with less experience but different technical skills, fresh perspectives, and access to new tools. The leadership challenge is connecting those capabilities instead of allowing generations to dismiss each other. Why Manufacturing Training Fails Jared’s work in manufacturing training has taught him that theory alone doesn’t prepare someone to troubleshoot equipment, machine a component, wire a motor, or solve a real production problem. Effective manufacturing training requires practical application and instructors who understand the work. Employees also want to know why a new process is better, how it helps them do their jobs, and whether their experience and feedback matter. Jared shares how employee feedback has led his team to change training because workers discovered a better way to perform the work. Ego, Listening and Better Decisions One of Jared’s simplest leadership practices is also one of the hardest: Don’t respond immediately when you feel challenged. When a leader’s first instinct is to prove they’re right, pause before responding. Then get curious. “Help me understand what you mean.” “What made you think this would work better?” “How could we implement this idea?” The objective isn’t to give up decision authority. It’s to understand the information before deciding what to do with it. In this episode: • How ego can block continuous improvement in manufacturing • Why experienced leaders stop noticing familiar operational problems • The “boiled frog” effect and what it costs manufacturers • How frontline employees uncover waste and inefficiency leaders may no longer see • Why listening to an idea doesn’t mean you have to implement it • Manufacturing’s generational leadership shift • Retiring workers and the loss of practical manufacturing knowledge • Why vocational education, mechatronics, and skilled trades matter • AI, automation, and the continuing value of hands-on technical skills • How ego affects listening and decision-making • Mental health and workplace well-being in production environments • How to design technical training that actually sticks • Why practical experience matters when training frontline workers Manufacturing needs experienced people. It also needs experienced people willing to reconsider what they know. The competitive advantage may come from knowing when experience should guide the decision, when a new idea deserves attention, and when being right matters less than getting to a better answer. Guest: Jared Scott National Training Manager, SEW-EURODRIVE Author of Edge Over Ego: Why Being Right Isn’t Enough and What Actually Makes Leaders Effective #Manufacturing #ManufacturingLeadership #WorkforceDevelopment #SkilledTrades #ManufacturingTraining #AIinManufacturing #Automation #ContinuousImprovement #HumanJudgment #ManufacturersNetwork

  • S5 · E26
    September 14 · 35 min

    Leadership Under Pressure: Burnout, Communication & Human Judgment in Manufacturing with Kabrina Ashley

    What happens on the manufacturing floor when pressure goes up, communication shuts down, and your best employees stop speaking up? In this episode of The Manufacturers Network Podcast, Lisa Ryan talks with leadership consultant, speaker, and applied neuroscience practitioner Kabrina Ashley about how stress and burnout affect communication, decision-making, safety, employee retention, and human judgment in manufacturing. One of the earliest warning signs isn't always poor performance. It's silence. An experienced employee notices something doesn't sound right. A high performer sees a potential problem but stops mentioning it. Someone has an instinct that a machine, process, or production line needs attention, but they've learned that speaking up may get them dismissed as overly cautious. Kabrina explains how sustained pressure can narrow attention and create tunnel vision. Employees become focused on completing the immediate task, protecting themselves from criticism, and getting through the shift. That can mean missing the small warning signs that could prevent a larger safety, quality, or production problem. Lisa and Kabrina also discuss the growing importance of human judgment as manufacturers adopt AI and automation. Technology can provide data, dashboards, and alerts, but experienced workers carry what Lisa calls a "sensory library." They can hear, feel, smell, notice, remember, and recognize patterns that may never appear on a dashboard. The challenge for manufacturing leaders is creating an environment where people still use that judgment and feel safe enough to speak up. The conversation also explores burnout in manufacturing and the warning signs leaders often miss. High performers may continue producing excellent work while quietly withdrawing. They stop volunteering ideas. They stop staying the extra five minutes. They stop fixing problems nobody asked them to fix. Eventually, the manufacturer risks losing an employee whose knowledge may take two or three people to replace. Kabrina shares practical, brain-based leadership strategies plant managers and frontline supervisors can use under pressure, including slowing down before reacting, using breathing to regain composure, paying attention to physical signs of stress, and asking better questions instead of settling for "Everybody good?" In this episode: • Why silence can be an early warning sign of burnout and disengagement • How chronic pressure affects attention, communication, and decision-making • Why psychological safety matters for manufacturing safety and quality • How AI and automation increase the importance of human judgment and communication • Why experienced workers' tribal knowledge and sensory knowledge need to be protected • How generational differences can create communication breakdowns on the shop floor • Why leaders often repeat the management behaviors they experienced themselves • Early signs that a high-performing employee is mentally checking out • Why rewarding your best employees with more work can eventually drive them away • How breathing and emotional regulation can help leaders make better decisions under pressure • Why employee behavior that looks like a bad attitude may have another explanation • How leaders can ask better questions to uncover problems before they become bigger problems One practical change manufacturing leaders can make immediately: stop asking questions that make "yes" the easiest answer. Instead of "Everybody good?" or "Did everybody get it?" ask employees what they're noticing. Ask what's working with a new machine or process and what isn't. Ask what they see that leadership may be missing. When manufacturers invest in AI, automation, and smarter technology, human judgment doesn't become less important. The ability to notice, question, communicate, and intervene may become even more valuable. #Manufacturing #ManufacturingLeadership #AIinManufacturing #Leadership #EmployeeRetention #ManufacturingWorkforce #Burnout #HumanJudgment #WorkplaceSafety #Automation #ManufacturersNetwork

  • S5 · E25
    September 7 · 31 min

    Manufacturing Cybersecurity, AI Adoption, and the Future of Frontline Work with Denis O'Shea

    Manufacturers are investing millions in AI, Microsoft 365, automation, and digital transformation. Yet many organizations are still struggling with the same challenge: getting employees to actually use the technology while keeping operations secure. In this episode of The Manufacturers Network Podcast, I sit down with Denis O'Shea, Founder and CEO of Mobile Mentor, to discuss what manufacturers need to know about cybersecurity, AI adoption, Microsoft Copilot, and protecting frontline workers. Drawing on more than two decades of helping organizations bridge the gap between technology and employee adoption, Denis explains why technology alone never solves the problem. Success depends on helping people understand, trust, and use the tools they're given. We also explore one of the biggest security risks facing manufacturers today: shared passwords. Denis explains why eliminating passwords, moving to cloud-based security, and properly supporting frontline workers can dramatically reduce cyber risk while improving productivity. If you're a manufacturing executive, plant manager, HR leader, IT professional, or operations leader trying to balance innovation with security, this conversation offers practical guidance you can implement immediately. In this episode, you'll learn: Why manufacturers struggle to get full value from Microsoft 365 and AI investments The biggest cybersecurity threats facing manufacturing companies today Why shared passwords create unnecessary security risks How manufacturers can better support frontline employees using AI tools What Microsoft Copilot, AI agents, and workflow automation mean for manufacturing Why employee adoption matters as much as technology selection The advantages of cloud security over aging on-premise systems How to improve both productivity and cybersecurity without overwhelming your workforce Key Takeaways Technology is evolving faster than people can adopt it. Organizations often purchase powerful software but use only a fraction of its capabilities because employees lack training, confidence, or support. Frontline workers are frequently overlooked during digital transformation initiatives. While executives receive AI training and new tools, employees on the plant floor often receive little guidance, creating both productivity and security gaps. Manufacturers should prioritize eliminating shared passwords wherever possible. According to Denis, compromised credentials remain one of the leading causes of security breaches, particularly in environments where multiple employees share devices and accounts. Cloud-based platforms continue to provide stronger security protections than many organizations can maintain on their own, making cloud migration an important long-term cybersecurity strategy. As AI capabilities expand, organizations also need to monitor usage and costs. New AI assistants, agents, and automated workflows create tremendous opportunities, but they also introduce new budgeting and governance challenges that leaders should understand before scaling adoption. About Denis O'Shea Denis O'Shea is the Founder and CEO of Mobile Mentor, a global Microsoft partner specializing in helping organizations improve cybersecurity, modern workplace productivity, AI adoption, and employee technology experiences. After spending 15 years with Nokia during its rise to global leadership, Denis founded Mobile Mentor to help organizations close the gap between rapidly advancing technology and real-world employee adoption. Connect with Denis O'Shea Learn more about Mobile Mentor and Denis's work helping organizations strengthen cybersecurity, improve Microsoft adoption, and prepare for the future of AI in the workplace. Listen If You Want To Learn About: Manufacturing cybersecurity AI in manufacturing Microsoft Copilot for manufacturers Frontline worker technology Manufacturing digital transformation Cybersecurity best practices Passwordless authentication Microsoft 365 adoption Cloud security AI governance Employee technology adoption Manufacturing leadership Industrial cybersecurity Recommended Resources If you enjoyed this conversation, check out other episodes of The Manufacturers Network Podcast, where manufacturing leaders share practical insights on workforce development, leadership, technology, retention, automation, and building stronger organizations. Keywords: manufacturing cybersecurity, AI adoption, Microsoft Copilot, manufacturing technology, industrial cybersecurity, frontline workers, digital transformation, cloud security, Microsoft 365, passwordless authentication, manufacturing leadership, cybersecurity best practices, AI governance, manufacturing innovation, employee technology adoption.

  • S5 · E24
    August 31 · 29 min

    AI That Actually Works on the Factory Floor with Mike Fedorov

    Artificial intelligence is everywhere. Unfortunately, so is AI hype. Manufacturers are hearing promises about smarter factories, automated planning, and AI-powered decision making. But what actually works inside a real manufacturing operation where data is messy, production schedules change hourly, and experienced employees solve problems machines never see coming? In this episode of The Manufacturers Network Podcast, Lisa Ryan talks with Mike Fedorov, Co-CEO and COO of Applied AI Labs and former manufacturing leader at Mars and Accenture. Together, they cut through the AI buzzwords and focus on practical strategies manufacturers can implement today. Instead of chasing shiny technology, Mike explains why successful AI projects begin with operational pain points, involve frontline employees from day one, and focus on delivering measurable business value quickly. If you're wondering how artificial intelligence fits into manufacturing without replacing your workforce or sacrificing human judgment, this conversation is a must-listen. What You'll Learn Why more than 80% of AI projects fail before delivering meaningful results How manufacturers can identify the best first AI project Why employee buy-in matters more than software selection The difference between AI demonstrations and real factory floor solutions How AI can improve production planning and sequencing Why dirty manufacturing data shouldn't stop your AI journey How experienced employees and AI create stronger decisions together The biggest mistakes companies make when implementing AI Why resilience still matters even in highly automated operations How manufacturers can begin using AI without a massive technology budget Key Takeaways Solve Real Problems First The best AI projects don't begin with technology. They begin with the biggest frustrations employees experience every day. Instead of asking, "Where can we use AI?" ask: What's slowing us down? What's costing us money? What repetitive work frustrates our people? Those answers often reveal the highest-return automation opportunities. Human Judgment Still Wins AI is remarkably good at processing data. Experienced people are remarkably good at recognizing when something doesn't feel right. The future of manufacturing isn't AI replacing people. It's AI helping experienced employees make faster, better decisions while preserving the judgment developed over decades on the plant floor. Don't Wait for Perfect Data Many organizations delay AI because they believe their data isn't clean enough. Mike argues that's the wrong approach. Real manufacturing environments always contain incomplete, inconsistent, or messy data. The goal isn't perfection. It's building AI systems that can operate successfully in the real world. Start Small. Win Early. Manufacturers don't need million-dollar AI initiatives. Choose projects that are: Easy to implement Highly valuable Capable of delivering measurable ROI quickly Early wins build confidence throughout the organization and create momentum for larger AI initiatives. AI Should Strengthen Your Workforce The strongest manufacturing organizations combine: Experienced people Practical AI tools Operational expertise Continuous improvement Technology doesn't replace great employees. It helps them spend less time fighting systems and more time solving problems that matter. Featured Guest Mike Fedorov is the Co-CEO and COO of Applied AI Labs, helping mid-market manufacturers deploy practical AI solutions that improve operations, production planning, and business performance. Before founding Applied AI Labs, Mike spent 25 years leading manufacturing, supply chain, and consulting initiatives at Mars and Accenture. Connect with Mike Fedorov LinkedIn: Mike Fedorov Applied AI Labs Email: mike@aalc.ai About The Manufacturers Network Podcast Hosted by Lisa Ryan, CSP, founder of Grategy and author of Smart Plant: Aligning AI, Automation, and People, The Manufacturers Network Podcast features conversations with manufacturing leaders, innovators, and experts who are helping organizations build stronger cultures, improve employee retention, develop frontline leaders, and prepare for the future of manufacturing. Whether you're a manufacturer, plant manager, operations leader, HR professional, or executive, each episode delivers practical strategies you can apply immediately to improve workforce performance and business results. Keywords: AI in manufacturing, manufacturing AI, artificial intelligence for manufacturers, factory automation, manufacturing leadership, AI adoption, manufacturing operations, production planning, production scheduling, AI agents, manufacturing technology, digital transformation, frontline leadership, employee retention, manufacturing culture, operational excellence, Industry 4.0, smart manufacturing, production optimization, manufacturing workforce, manufacturing podcast, manufacturing innovation, manufacturing productivity, human judgment, manufacturing efficiency

  • S5 · E23
    August 24 · 31 min

    The Future of Manufacturing Workforce Development, AI, and Digital Transformation with Bryce Carpenter

    How can manufacturers solve workforce shortages while embracing artificial intelligence, automation, and digital transformation? In this episode of The Manufacturers Network Podcast, Lisa Ryan sits down with Bryce Carpenter, Executive Vice President and Chief Operations & Strategy Officer at Conexus Indiana, to discuss how one of America's strongest manufacturing states is preparing its workforce for the future. Bryce shares how manufacturers, educators, policymakers, and economic development organizations can work together to strengthen talent pipelines, accelerate technology adoption, and help small and mid-sized manufacturers compete in an increasingly digital economy. From apprenticeships and plant tours to AI use cases and workforce partnerships, this conversation is packed with practical ideas for manufacturing leaders looking to attract talent, improve operations, and future-proof their organizations. In This Episode You'll Learn Why workforce development remains manufacturing's biggest challenge and biggest opportunity How AI is helping reshape the image of modern manufacturing careers Why apprenticeships and work-based learning outperform traditional recruiting methods How manufacturers can partner with schools to build long-term talent pipelines Why digital transformation creates higher-paying jobs instead of replacing workers How manufacturers are successfully introducing AI without creating employee resistance Why sharing best practices across manufacturers accelerates innovation The value of plant tours, peer networking, and manufacturing associations How Conexus Indiana collected more than 100 real-world AI manufacturing use cases Why collaboration between industry, education, and government is essential for workforce success Key Topics Discussed Workforce development Manufacturing workforce shortages AI in manufacturing Digital transformation Advanced manufacturing Manufacturing leadership Apprenticeships Work-based learning Career and technical education (CTE) Community colleges Employee retention Workforce recruitment Manufacturing technology Industrial automation Cobots Manufacturing associations Economic development Manufacturing innovation Supply chain development Manufacturing careers Memorable Quotes "The day I started, the biggest challenge was workforce. Today, it's still workforce." "AI is helping manufacturers show young people what modern manufacturing really looks like." "Technology is additive to workers, not a replacement for workers." "You don't have to solve these problems on your own. Someone has already learned the lessons." Why This Conversation Matters Manufacturers everywhere are competing for skilled workers while simultaneously navigating artificial intelligence, automation, and rapid technological change. Bryce explains that success isn't just about adopting new technology. It's about building partnerships that connect manufacturers with schools, community colleges, policymakers, and each other. The companies that thrive won't necessarily be the ones with the biggest budgets. They'll be the organizations that embrace collaboration, invest in people, and create cultures where technology helps employees do more meaningful work. For manufacturers wondering how to recruit younger workers, introduce AI successfully, or build stronger workforce pipelines, this episode offers a practical roadmap. About Bryce Carpenter Bryce Carpenter is the Executive Vice President and Chief Operations & Strategy Officer at Conexus Indiana, where he helps strengthen Indiana's advanced manufacturing and logistics ecosystem through workforce development, digital transformation, economic strategy, and collaboration between industry, education, and government. Conexus Indiana works with more than 130 manufacturing and logistics partners to advance innovation, workforce readiness, and competitiveness across one of the nation's largest manufacturing economies. Connect Learn more about Conexus Indiana: https://www.conexusindiana.com Connect with Bryce Carpenter on LinkedIn. Connect with Lisa Ryan: https://www.LisaRyanSpeaks.com Learn more about Smart Plant: Aligning AI, Automation, and People https://www.SmartPlantBook.com Listen to more episodes of The Manufacturers Network Podcast: https://www.TheManufacturersNetworkPodcast.com Recommended For Manufacturing CEOs Plant Managers Operations Leaders HR Leaders Workforce Development Professionals Manufacturing Executives Community College Leaders Economic Development Organizations Manufacturing Associations Career and Technical Education (CTE) Leaders Industrial Engineers State Manufacturing Partnerships Government Workforce Agencies

  • S5 · E22
    August 17 · 29 min

    AI, Supply Chains, and Global Logistics: How Manufacturers Can Build More Resilient Operations with Phil Rees

    What happens after your product leaves the factory may determine your profitability just as much as what happens inside it. In this episode of The Manufacturers Network Podcast, Lisa Ryan talks with Phil Rees, founder of ShipMax and a supply chain strategist with more than 20 years of experience helping manufacturers, retailers, and global brands improve fulfillment, warehousing, customs compliance, and international logistics. Phil explains why many manufacturers focus heavily on production efficiency while overlooking logistics decisions that quietly increase costs, delay shipments, and create unnecessary risk. He also shares how artificial intelligence is transforming warehousing and fulfillment, why companies should rethink inventory strategies, and what changing global trade regulations mean for manufacturers expanding into international markets. If you're responsible for manufacturing operations, supply chain management, distribution, procurement, or business growth, this episode offers practical strategies for building a more resilient, efficient supply chain. In This Episode You'll Learn The biggest logistics mistakes manufacturers make after products leave the factory Why HS (Harmonized System) codes have a major impact on customs clearance and import costs How manufacturers can reduce supply chain costs by minimizing border crossings When reshoring, nearshoring, or regional inventory makes financial sense How AI is improving warehouse management, fulfillment, inventory forecasting, and logistics planning What manufacturers should know about tariffs, customs regulations, and global trade changes Why supply chain strategy should be reviewed continuously instead of treated as a one-time project Practical ways manufacturers can begin using AI immediately to improve operations Key Topics Discussed Manufacturing supply chains Global logistics Warehousing Fulfillment Distribution strategy Customs compliance HS Codes International shipping Tariffs Reshoring Nearshoring Fourth-party logistics (4PL) Warehouse automation Robotics Artificial intelligence in manufacturing AI for supply chain management Inventory optimization Manufacturing operations Global trade Memorable Quotes "Supply chain compliance is a journey, not a destination." "Every time you cross a customs border, you add cost." "If you put garbage into AI, you'll get garbage out." "Manufacturers that aren't experimenting with AI risk falling behind." Why This Conversation Matters Manufacturers spend enormous resources improving production efficiency, yet many overlook opportunities to optimize what happens after products leave the factory. As tariffs evolve, customer expectations change, and artificial intelligence reshapes logistics, manufacturers need supply chains that are flexible, data-driven, and globally competitive. Phil explains why resilient supply chains depend on more than transportation. They require smarter inventory placement, better customs planning, AI-powered decision-making, and continuous adaptation to changing global markets. Whether you're shipping across the country or around the world, these strategies can help reduce costs, improve customer experience, and strengthen your competitive advantage. About Phil Rees Phil Rees is the founder of ShipMax, where he helps manufacturers, retailers, and growing brands optimize fulfillment, warehousing, logistics, and international distribution. With more than two decades of experience in global supply chain management, Phil specializes in helping organizations simplify complex logistics while preparing for future growth through automation and artificial intelligence. Connect Learn more about ShipMax: https://www.shipmax.co.uk Connect with Phil Rees on LinkedIn. 🎯Phil Rees | LinkedIn Connect with Lisa Ryan: https://www.LisaRyanSpeaks.com Learn more about Smart Plant: Aligning AI, Automation, and People Amazon.com: Smart Plant: 9798995174707: Ryan, Lisa: Books Listen to more episodes of The Manufacturers Network Podcast: https://www.manufacturers-network.com/ Recommended For Manufacturing CEOs Operations Leaders Supply Chain Directors Plant Managers Logistics Managers Procurement Professionals Distribution Leaders Warehouse Managers Manufacturing Executives Business Owners Industrial Engineers International Trade Professionals

  • S5 · E21
    August 10 · 23 min

    How Manufacturers Can Attract Gen Z Talent Through Apprenticeships with 2026 Apprentice of the Year Sarah Morgan

    Why do so many manufacturers struggle to attract younger workers while companies with strong apprenticeship programs have candidates lining up? In this episode of The Manufacturers Network Podcast, Lisa Ryan sits down with Sarah Morgan, Toolmaking Apprentice at R&D Leverage (an Adler Company) and the 2026 Apprentice of the Year recognized by the Mold Technologies Division. Sarah shares how a high school manufacturing tour changed the direction of her career, why apprenticeships are one of manufacturing's strongest recruiting tools, and what employers can do differently to attract, train, and retain the next generation of skilled trades professionals. Whether you're a manufacturing executive, HR leader, plant manager, educator, or parent exploring career options, this conversation offers practical insights into workforce development, mentorship, and succession planning. In This Episode You'll Learn Why high school manufacturing tours influence career decisions How apprenticeship programs help solve the skilled labor shortage What Gen Z employees look for in manufacturing employers Why visibility and outreach matter more than ever for recruiting The importance of mentorship and knowledge transfer before experienced employees retire How reverse mentoring strengthens relationships between experienced workers and younger employees Why manufacturing careers offer multiple career paths without requiring a traditional four-year degree How tuition reimbursement and continuous learning improve employee retention Ways manufacturers can partner with local schools to build future talent pipelines Key Topics Discussed Manufacturing apprenticeships Workforce development Skilled trades careers Toolmaking Plastic injection mold manufacturing Manufacturing career pathways Employee development Succession planning Knowledge transfer Reverse mentoring High school career exploration Manufacturing education Recruiting younger workers Gen Z workforce Manufacturing leadership Employee retention Manufacturing workforce shortages Memorable Quotes "We'll teach you if you don't know." "Recognition doesn't have to be a big thing. People notice when you care." "There are so many different jobs in manufacturing. You can find your niche." "I'm learning something new every day." Why This Conversation Matters Manufacturing companies across North America are facing an aging workforce, increasing retirements, and a growing shortage of skilled workers. Sarah's story demonstrates that attracting younger talent isn't simply about higher wages or better technology. It's about visibility, mentorship, career pathways, and creating opportunities for people who may never have considered manufacturing. Her experience also highlights the importance of structured apprenticeship programs, partnerships with schools, and transferring critical institutional knowledge before experienced employees retire. About Sarah Morgan Sarah Morgan is a Toolmaking Apprentice at R&D Leverage, an Adler Company, and the recipient of the 2026 Apprentice of the Year Award from the Mold Technologies Division. She is currently completing her Toolmaking degree while working full-time and serves on her local ITEC advisory board, helping strengthen partnerships between manufacturers and schools. Connect Learn more about R&D Leverage: https://www.rdleverage.com Connect with Lisa Ryan: https://www.LisaRyanSpeaks.com Learn more about Smart Plant: Aligning AI, Automation, and People https://www.amazon.com/dp/B0H2FVPZZ5 Listen to more episodes of The Manufacturers Network Podcast: https://www.manufacturers-network.com/ Recommended For Manufacturing CEOs Plant Managers HR Professionals Operations Leaders Manufacturing Executives Workforce Development Professionals Technical Education Leaders Career and Technical Education (CTE) Instructors Apprenticeship Coordinators Manufacturing Association Leaders Students exploring manufacturing careers Parents and educators

  • S5 · E20
    August 3 · 27 min

    Why AI Pilots Fail in Manufacturing (and How to Fix It) with Russell Halper

    AI pilots look great in a controlled environment. Then they hit the real shop floor and quietly fall apart. In this episode, Lisa Ryan talks with Russell Halper, founder and managing director of Insight Kitchen, about why so many manufacturing AI initiatives stall after deployment and what leaders can do differently before they ever write the first prompt. Russell's path here is unusual. He started a PhD in mathematics under a founder of chaos theory, moved into operations research (one of the earliest forms of data science), worked at UPS, then went in-house as an internal consultant for a major consumer goods manufacturer. From there, he spent eight years at a boutique Palo Alto consulting firm, helped grow it from 16 to 100 people, saw it acquired by a large global consultancy, and ran its West Coast Generative AI practice. Two years ago, he left to found Insight Kitchen, a boutique data science and AI consultancy focused on operational AI in manufacturing and supply chain. Key Takeaways for Manufacturing Leaders A pilot is not a proof point; it is a rehearsal for scale. Most organizations design pilots to prove AI works in a controlled setting. Russell argues the real work is designing the pilot to surface the change management, data, and complexity issues that will show up at full scale, before you ever roll it out plant-wide. A 95 percent solution can be a catastrophic failure. In operational environments, the last few percentage points of accuracy often carry the most real-world risk. Before adopting an AI tool, define what "good enough" actually means for that specific decision, because the threshold changes by use case. Watch for compounding error, not just error rate. If an AI model is 99 percent as good as your best people but making decisions much faster, small errors can compound quickly. Ask whether faster, slightly less accurate decisions are actually creating value or just creating a bigger mess sooner. Usage is your earliest warning sign. If the people on the floor are not acting on the AI's recommendations, you already have your answer. A model nobody trusts is not a decision-making tool, no matter how sophisticated it is. Your senior operators know things your data never captured. A 40-year machine operator who says "something's off with this machine" is picking up on signals that never made it into a sensor feed. When leadership overrides that instinct because "the dashboard is green," they lose the tribal knowledge as retiring workers walk out the door. "Clean data first" can be a stall tactic. Russell has seen organizations spend endless cycles perfecting data before doing anything with it. His advice: work the actual business problem and pull the data along with you. You will often learn more about your data by using it than by polishing it in isolation. Start with the business problem, not the technology. The mechanics of building a financial case for an AI project look almost identical to the case for any other software investment. Start with the outcome you want (efficiency, reduced reject rate, faster throughput) and work backward to whether AI is the right tool, not the other way around. Mid-market manufacturers may have a real speed advantage right now. Fewer legacy systems, more focused operations, and lower internal liability friction mean mid-sized manufacturers can often move faster on AI adoption than large enterprises, which are weighed down by legacy tech and internal politics. As AI gets better, ask whether your business is getting better with it. Russell's framework: track whether your organization's capability is compounding alongside the technology, or whether you are just layering new tools onto the same old process. Discussion Questions for Your Leadership Team Where are we chasing a "bright, shiny" AI tool instead of a defined business outcome? What does our frontline team know that never makes it into our systems, and how are we capturing it before they retire? If usage of a tool dropped to zero tomorrow, would we notice, and would it matter? About Russell Halper Russell Halper is the founder and managing director of Insight Kitchen, a boutique data science and AI consultancy that embeds AI directly into the processes that run supply chain, manufacturing, and revenue management operations. He holds a PhD in Applied Mathematics and brings over 20 years of experience at the intersection of applied mathematics, operations research, and AI, having advised startups, private equity-backed SaaS companies, and Fortune 500 organizations across retail, consumer goods, manufacturing, high-tech, and logistics. Before founding Insight Kitchen, Russell was a partner at End-to-End Analytics (acquired by Accenture) and later led Accenture's West Coast Generative AI practice as Managing Director. Connect with Russell: Insight Kitchen: insightkitchen.ai LinkedIn: linkedin.com/in/russellhalper About the Host Lisa Ryan, CSP, MBA, is the founder of Grategy® and Chief Appreciation Strategist. She hosts the Manufacturers Network Podcast and speaks to manufacturing, industrial, skilled trades, and healthcare audiences on employee retention, workplace culture, and the human side of AI and automation. Her newest book, Smart Plant: Aligning AI, Automation, and People, explores how manufacturers can adopt AI without losing the judgment and tribal knowledge their people bring to the floor. Book Lisa Ryan for your next event, conference, or leadership training on AI, culture, and workforce retention: Website: LisaRyanSpeaks.com Email: lisa@grategy.com Connect and Subscribe Listen to more episodes of the Manufacturers Network Podcast Learn more about Grategy at LisaRyanSpeaks.com Get Smart Plant: Aligning AI, Automation, and People: amazon.com/dp/B0GZMFBVZ2

  • S5 · E19
    July 27 · 27 min

    The Recognition Mistake Costing You Your Best People with Michelle Kozin

    Lisa Ryan sits down with Michelle Kozin, an organizational strategist who uses behavioral science to help manufacturers connect people strategy with business strategy. Michelle's background in change management started with large-scale ERP implementations, where she learned that the technology was never the hard part. The people were. In this conversation, Michelle and Lisa unpack why the same recognition can motivate one employee and completely miss the mark with another, why pay is rarely the real reason a skilled tradesperson walks out the door, and why role clarity might matter more than personality type when it comes to unlocking performance. They also look ahead to a shift already underway on plant floors: leaders who will soon manage AI agents alongside human teams, and what that means for trust, communication, and job design. What You'll Learn Why change triggers fear of loss, not fear of change itself, and what that means for how leaders communicate The difference between extrinsic and intrinsic motivators, and why money is rarely the true reason someone starts job hunting How to recognize employees according to how they're wired, not how you'd want to be recognized yourself Why treating everyone "the same" often reads as unfair, and what real fairness looks like instead The difference between behavioral assessments and job assessments, and why role clarity solves more retention problems than personality typing does How AI and automation are reshaping job expectations the same way ERP implementations did two decades ago One question every plant manager can ask before their next one-on-one to build more trust this week Key Quotes Michelle Kozin on why people resist change: people aren't afraid of change itself, they're afraid of what they might lose, whether that's control, influence, or relationships. Michelle on recognition: a gift lands based on the person opening it, not the person giving it, and that means leaders need to know how each team member is wired before deciding how to show appreciation. Michelle on fairness: real fairness means matching your approach to the person in front of you, using the same standard of communication but a different path to get there. Lisa Ryan on AI and human judgment: machines will be right the vast majority of the time, but the small percentage where human judgment matters is exactly where tribal knowledge and critical thinking need to be protected and passed down. Actionable Takeaways for Plant and Operations Leaders Before your next one-on-one, ask yourself one question. How does this person want to be led, similarly to you or differently? Let the answer shape how you open the conversation. Audit your recognition approach by employee, not by policy. Some people want public praise. Others want a quiet handshake and a private word. Find out before you plan the next round of engineering week gifts or service awards. Separate role clarity from personality typing. Before investing in another behavioral assessment, make sure every person on your team can answer this: what does success in my role actually look like right now? Over-communicate during any transformation, especially the uncomfortable parts. Sharing the good, the bad, and the ugly builds more trust than protecting people from bad news ever will. Get ahead of AI-driven job redesign the way you'd handle any major system change. As AI takes on more tasks, job descriptions and expectations will shift. Name that shift out loud instead of letting people guess at what their role now requires. Watch for the quiet quitters. Most people disengage long before they resign. Treat consistent, values-aligned recognition as a retention tool, not an afterthought. About Michelle Kozin Michelle Kozin is an organizational strategist who helps companies and leaders connect people strategy with business strategy using behavioral science. She has spent 20 years using the Predictive Index methodology to help organizations improve hiring, define roles, and unlock performance through better leadership. Her work centers on how trust and connection form under pressure, particularly during periods of organizational change like digital transformation, technology implementation, and now the rise of AI in the workplace. Connect with Michelle on LinkedIn or visit predictiveadvisors.com. About the Host Lisa Ryan, CSP, MBA, is the founder of Grategy® and host of the Manufacturers Network Podcast. She works with manufacturing, industrial, and skilled trades organizations on employee retention, workplace culture, and the human side of AI and automation. Her newest book, Smart Plant: Aligning AI, Automation, and People, is available now on Amazon. Connect Explore more episodes of the Manufacturers Network Podcast Learn more about Grategy at LisaRyanSpeaks.com Get Smart Plant: Aligning AI, Automation, and People: https://www.amazon.com/dp/B0GZMFBVZ2

  • S5 · E18
    July 20 · 33 min

    When the Expert Retires, Does the Answer Leave with Them? with Brian Kaufman

    Brian Kaufman is co-founder and chief product officer at Strudel, an AI startup that gives technical support teams real-time context when issues hit and detects error patterns before they become customer-facing problems. His background is in software product development and healthcare technology, but the problems he solves map directly onto what manufacturing companies face every day: institutional knowledge that lives in people's heads instead of in systems, and support teams solving the same problems over and over from scratch. Brian and Lisa dig into what it actually costs when undocumented knowledge walks out the door, how AI can serve as a partner to experienced technicians without replacing their judgment, and what a realistic starting point looks like for manufacturers considering AI-assisted support. Key Takeaways for Manufacturing Leaders The information exists. It just isn't findable. Most organizations aren't starting from zero. The knowledge is in old tickets, emails, PDFs, and people's heads. The first step is figuring out where it lives, not waiting until it's gone to wish you'd captured it. Start before someone gives notice. The best time to document institutional knowledge is before retirement is on the horizon. If the person with 30 years of experience is leaving in two months, you're already behind. Build the habit now. Ask the question nobody's asked. One of the most powerful knowledge-capture prompts: "What do you know that nobody's ever asked you about?" Experienced technicians have built sensory libraries over decades, knowing what a machine sounds like, feels like, and smells like when something's about to go wrong. That knowledge doesn't survive a standard exit interview. AI should be an investigator, not an oracle. Strudel presents troubleshooting suggestions as hypotheses grounded in real historic tickets, not confident declarations. When a technician is standing at a machine, that distinction matters. Build trust by showing your work, not by pretending to be certain. Machine context cuts investigation time dramatically. Knowing the model, firmware version, and configuration immediately narrows the problem space. A known defect affecting machines shipped between two specific dates becomes a one-step fix rather than a multi-hour troubleshooting process. Don't use LLMs for everything. Strudel uses traditional statistical analysis and machine learning for the heavy lifting, reserving large language models for last-mile summarization. The result is fewer hallucinations and answers that are easier to monitor and evaluate for quality. Your most skeptical expert is your most important early win. Find the team member with deep expertise who doubts new tools and figure out what task they hate doing most. Solve that one problem well, and you've turned your biggest skeptic into your biggest advocate. Start small, find wins, then expand. Don't try to solve everything at once. Pick one product line, one process, one team. Get good at that before scaling. Build in an early checkpoint to evaluate and adjust. Involve your people before you buy anything. Coming back from a trade show with a shiny new system your team had no input on is a reliable way to end up with a system nobody uses. Ask what's causing the most pain. Start there. Working top of license matters on the shop floor too. When your most experienced technician is answering the same question for the fifth time, that's a waste. Free those people up for novel problems, mentoring, and process improvement. About Strudel Strudel embeds directly into existing support ticketing systems and generates troubleshooting steps within 15 to 20 seconds of a ticket coming in, drawing on historical tickets and documentation specific to the machine, software version, and configuration in question. As more tickets are resolved, that knowledge becomes part of the system, making new staff onboarding faster and institutional knowledge more durable. Connect with Brian Kaufman Email: brian@strudel.io Website: www.strudel.io The Manufacturers Network Podcast features long-form conversations with leaders, practitioners, and experts across manufacturing, the skilled trades, and industrial sectors. Host Lisa Ryan, CSP, MBA, is a keynote speaker, author of 13 books, and founder of Grategy.

  • S5 · E17
    July 13 · 32 min

    Why Women Leave the Trades (And What Stops Them) with Samantha Kaye Harris

    Samantha Kaye Harris spent 27+ years in structural maintenance leadership at JFK Airport, managing teams of 100+ people in one of the most male-dominated environments in the trades. She started as a general maintainer, learned paving, roofing, sheet rock, and concrete work from the ground up, and earned her way into leadership one job at a time. Today she helps women in manufacturing, the trades, and industrial environments own their voice, stay in the room, and get paid for the value they bring. Lisa and Samantha dig into what it actually costs when women go silent on the shop floor, why psychological safety and physical safety are directly connected, and what plant managers and operations leaders can do right now to change the dynamic on their teams. Key Takeaways for Manufacturing Leaders Retention starts with safety, not perks. Women don't leave because the pay is bad. They leave because they don't feel safe speaking up, asking for what they need, or being heard without having their competence questioned. Fix the environment before you worry about the benefits package. The fear cycle is a real retention risk. Samantha describes a predictable pattern: a woman arrives, over-performs to prove herself, gets worn down by constant testing and second-guessing, goes silent, starts hiding, and eventually leaves. Recognizing where someone is in that cycle is the first step to stopping it. "Are you sure?" is a red flag phrase. Asking a leader whether she's sure, or checking her answer with another supervisor, sends a clear message about whose judgment is trusted. Leaders need to monitor this in their own behavior and in their teams. PPE that doesn't fit is a safety and morale issue. One-size-fits-all gear made for male bodies signals that women weren't considered when the workplace was designed. Getting the right fit is a practical step that communicates respect. Psychological safety connects directly to physical safety. When a woman is spending mental energy calculating how to avoid being dismissed, she's not focused on the work. In an environment with heavy equipment and real hazards, that's not just a morale problem. Don't send the complaint back to the floor. When a woman raises a concern and leadership takes it straight back to the crew, her colleagues often figure out exactly who said what. That's when isolation and retaliation start. Handle issues with confidentiality and intention. One woman in a safety or HR-adjacent role changes things. Having someone on staff who has actually done the work, who gets the environment, gives women a place to raise issues without fear of being laughed off or ignored. Community is a retention strategy. Women's groups, networking events, and peer connections within associations are growing fast because they work. If your industry association doesn't have a women's group, it's worth asking why not. Training boxes don't change behavior. Computer-based compliance training may satisfy HR requirements, but it doesn't change what happens on the shop floor. Real culture change takes conversation, modeling, and accountability. When women stop hiding, companies win. Samantha is direct about this: when a woman feels safe enough to fully show up, use her voice, and go after advancement, productivity goes up, teams communicate better, and the company starts attracting more skilled talent. The ROI is real. Samantha's Truth Methodology Samantha works with women one-on-one and through 30-day intensives to help them understand the internal patterns holding them back, learn where those patterns came from, and build the self-trust to use their voice, ask for what they want, and step fully into their power. Connect with Samantha Kaye Harris Email: info@samanthakayeharris.com (Note: Kaye is spelled K-A-Y-E) The Manufacturers Network Podcast features long-form conversations with leaders, practitioners, and experts across manufacturing, the skilled trades, and industrial sectors. Host Lisa Ryan, CSP, MBA is a keynote speaker, author of 13 books, and founder of Grategy.

  • S5 · E16
    July 6 · 24 min

    Stop Competing on Price: How to Find and Tell Your Company's Story with Lauren Kwedar Cockerell

    If your sales team keeps losing deals on price, the problem might not be your pricing. It might be your story. Lauren Kwedar Cockerell, founder and president of Kwedar & Co., a strategic communications firm based in Fort Worth, joins Lisa to talk about why so many manufacturers struggle to articulate what makes them genuinely different, and what to do about it. Lauren has spent 23 years in public relations working with B2B companies, with deep roots in manufacturing and industrial sectors. Her firm helps companies excavate what's already there, that unique thread hiding in plain sight, and turn it into messaging that resonates with customers, prospects, and the talent they're trying to attract. What You'll Learn in This Episode Why "our people" and "our quality" aren't differentiators. Every competitor is saying the same thing. Lauren explains why surface-level answers won't cut it and how to dig multiple levels deeper to find what's actually distinctive about your operation. The "yeah, duh" trap. The things your team dismisses as obvious are often the most compelling to your buyers. The challenge is that it's hard to read the label from inside the bottle. The Thread: Lauren's four-stage methodology Excavate. Deep discovery through conversations, competitive review, and a close look at everything you've built Surface. Finding that through line, the offhand comment you almost threw away that turns out to be the whole thing Articulate. Translating the story into language that resonates across every channel and audience Activate. Putting it out into the world on your website, in media, in sales conversations, and in internal communications Where AI fits and where it falls short. AI can help you iterate content once you have a strong narrative, but it cannot create one for you. Without a distinctive source document, you are just replicating what already exists and creating volume no one is listening to. The new visibility equation. Trade journals, podcasts, and consistent digital content are not just good marketing. They are signals that AI-powered search uses to determine relevancy and authority. If your messaging is inconsistent or generic, the LLMs cannot distinguish you from a competitor either. Signs your messaging problem is costing you real money. You are losing deals on price alone, your salespeople are delivering inconsistent pitches, you are attracting candidates who do not fit, and the marketing firms you have hired just cannot seem to nail it. The first thing to do this week. Pull up your website headline, take away your logo, and ask: could this apply to any other industry? If the answer is yes, you have work to do. Connect with Lauren Website: KwedarCo.com LinkedIn: Lauren Kwedar Cockerell The Manufacturers Network Podcast is hosted by Lisa Ryan, CSP, founder of Grategy and Chief Appreciation Strategist. Lisa helps manufacturing and industrial organizations build cultures where people want to stay.

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