Practitioners Unplugged

Episode #18 | How $4K Beat $100K: A CEO’s Interoperability Story

Executive Key Points * How one manufacturer solved interoperability for $4K instead of $100K * Why traditional plant integration approaches create unnecessary cost * What manufacturing leaders should evaluate before investing in connectivity * A simpler path to IT/OT alignment and scalability GET FUTURE PRACTITIONERS UNPLUGGED EPISODES Join manufacturing executives getting new conversations and key insights in their inbox. Subscribe Now “Standards and rigor be damned—that’s the cost of doing business.” For three decades, this mentality defined manufacturing operations. Plant floor heroes solved problems with whatever tools they could cobble together. Innovation happened one use case at a time. Each solution worked brilliantly. Together, they created a technical debt crisis where a small manufacturer would need to spend $100,000 for capabilities they could now access for $4,000. Episode 18 of Practitioners Unplugged, recorded live at Schneider Electric’s Innovation Summit, explored how that dramatic cost reduction became possible. John Dyck, CEO of CESMII (Clean Energy Smart Manufacturing Innovation Institute), explained why interoperability represents an inflection point for American manufacturing—particularly for the 98.4% of manufacturers that are small and medium-sized operations. Manufacturing productivity in the United States declined for the first time in recorded history over the last five years. Meanwhile, AI at scale remains out of reach for most organizations, blocked by technical debt accumulated through decades of problem-solving. WHAT INTEROPERABILITY ACTUALLY MEANS “Interoperability is one of those loaded terms, but it remains a super important idea and capability with very real outcomes,” John acknowledged. At its core, interoperability is the capability of disparate software systems to communicate seamlessly using standard interfaces and APIs. However, the definition matters less than the problem it solves. Thirty years of manufacturing data solutions created significant technical debt. Great companies built highly innovative solutions for productivity, quality, and maintenance. Nevertheless, each one became its own data silo with its own stovepipe architecture. “When great new capabilities show up, as we’ve seen with the fourth industrial revolution and certainly now with AI, we’re prohibited from innovating at scale because of that lack of rigor and lack of focus on data standardization,” John explained. John posed a striking challenge: “I can count on one hand how many Fortune 100 companies have effectively scaled large-scale manufacturing operations platforms across their entire fleet of sites.” The most resourced organizations still struggle to scale digital solutions. Not because the solutions don’t work—they work brilliantly. Rather, the lack of interoperability makes replication prohibitively complex and expensive. This scaling failure devastates the 98.4% of US manufacturers that are small and medium-sized operations. These companies need access to smart manufacturing capabilities but can’t afford the $100,000+ price tags that come with traditional approaches. THE THREE SMART MANUFACTURING IMPERATIVES CESMII’s approach centers on three foundational imperatives. First: Standardized Information Models. Today, you’re building data context from scratch every single time, and there’s no way to share these models because the structure varies from vendor to vendor. CESMII’s solution? Crowdsource standardized information models and make them freely available. “We can collaborate, come together as a community and build these standardized information models, put them in a marketplace, and make them accessible for every platform, for every manufacturer, for free,” John explained. These models cover every manufacturing asset—pumps, conveyors, compressors, CNCs, robots. Instead of reinventing the wheel, manufacturers access pre-built, standardized models that work across platforms. Second: Type-Safe Information Models. CESMII treats these models as “type safe”—preventing anyone from modifying the standard. This ensures consistency across deployments. Third: Standard APIs for Universal Access. The third imperative creates an open standard API that allows any platform to expose those information models and allows any application to discover those objects and their relationships. THE $4,000 SOLUTION THAT CHANGED EVERYTHING A small manufacturing company in Medina, Ohio with fewer than 20 employees faced major quality and reliability challenges. They couldn’t afford sophisticated software solutions or systems integration consulting. Through a small systems integrator familiar with CESMII’s approach, they deployed a standards-based solution for less than $4,000. “They were able to take a standards-based information model for a waste scale, bring that information into the cloud with no on-premise infrastructure and using Excel, solve their quality and reliability challenges,” John explained. In a traditional environment? That same capability would have cost approximately $100,000. This small manufacturer gained capabilities they could actually sustain. They didn’t have IT staff to maintain infrastructure or in-house expertise to connect complex systems. Nevertheless, with crowdsourced, open approaches, they now have a data platform that works with Excel, Power BI, or any other solution against the same API. BREAKING THE HIERARCHICAL PARADIGM Sree raised a critical technical point: the limitation of hierarchical data models. “I’ve never seen a manufacturing system that isn’t hierarchical,” John acknowledged. The ISA-95 model taught the industry to think in hierarchies: enterprise, site, area, line, asset. “But when you bring material or people or energy into that process, the hierarchical model falls down,” John explained. This limitation becomes critical when deploying AI at scale. “AI at its core wants to infer relationships—how equipment and operators and material interact,” John explained. “But in a hierarchical system that’s just not coded unless it’s custom coded every single time.” CESMII’s answer? Graph relational databases—the same technology social media companies use to determine relationships. “That’s really powerful in manufacturing because now you can expose data and figure out causation and correlation you wouldn’t have dreamed of before,” Dante noted. Graph databases treat every object as nodes with relationships to other nodes. Moreover, these relationships change over time. “AI can now infer real value from these relationships in ways that can be scaled very rapidly from site to site,” John explained. THE TRANSLATION PROBLEM EXECUTIVES UNDERSTAND Sree offered a powerful analogy for communicating interoperability’s value to leadership: “If every country comes to the UN with different languages, you need translators. But that’s exactly what we have—layers and layers of translators at different levels of the stack. When we say technical debt, that’s exactly what it is.” These translation layers compound complexity and cost. Worse, they erode data trust. “When you go through layers of translation and all these Frankenstein integrations, you lose trust in the data,” Sree noted. This insight particularly resonated from his life sciences experience, where regulatory compliance demands absolute data integrity. For CEOs, this creates the “aha moment.” Technical debt isn’t an IT problem—it’s layers of expensive translation that slow innovation, increase costs, and undermine confidence in the very data needed to make better decisions. THE MINDSET CHALLENGE AND PATH FORWARD Sree observed that “the mindset challenge is bigger than the actual technical viability.” John agreed emphatically. A significant part of the challenge involves helping manufacturers understand the disconnect between their business strategy and their digital or smart manufacturing strategy. “It turns out most manufacturers don’t have a cohesive digital or smart manufacturing strategy,” John revealed. When that epiphany happens, the rest falls into place. John highlighted a fundamental challenge: “As Americans, we’re as individualistic as corporations as we are as people—we don’t like collaborating.” CESMII exists precisely to overcome this tendency. As a vendor-agnostic consortia, they bring competitors to the table to solve problems collaboratively. “One of the most important things we can instill is a mindset biased towards collaboration and partnering,” John emphasized. This isn’t just philosophical. Interoperability cannot be solved by any one vendor or any one manufacturer alone. Therefore, it demands the kind of collaborative effort that CESMII facilitates. John described what he called the “bailing twine and duct tape mentality” that created current technical debt. “Fred or Sue on the shop floor—she’s gotta solve that problem right now so we can get product out the door. Standards and rigor be damned, that’s the cost of doing business.” This problem-solving approach made heroes of individuals who kept operations running. However, scaled across 30 years and thousands of sites, it created the interoperability crisis manufacturers face today. The transformation requires moving from heroic individual problem-solving to systematic, scalable solutions. THE INFLECTION POINT “We’re at an inflection point,” John emphasized. “I’m very aggressive in telling every manufacturer I have the opportunity to speak with: You can continue propagating this technical debt, this cost and complexity, or you can choose a different way—a way that will lead you towards productivity, competitiveness, fundamentally enabled by interoperability.” Manufacturing productivity in the United States has declined for the first time in recorded history. The next 30 years cannot be marked by the same stovepipe architecture approach that defined the last 30. Consequently, manufacturers face a choice: lead the transformation or scramble to catch up later. CESMII’s strategy centers on three pillars: knowledge (training and certification programs), technology (the three Smart Manufacturing Imperatives), and ecosystem collaboration. “All three have to be a vital part of any transformation,” John emphasized. For American manufacturing to reverse its productivity decline, capture AI’s potential at scale, and remain globally competitive, more organizations need to choose a different way. The inflection point is here. The question is whether manufacturers will recognize it and act while they still lead rather than follow. Ready to explore interoperability? Visit CESMII.org [https://www.cesmii.org/] to learn about knowledge programs, technology initiatives, and how to join the collaborative ecosystem transforming smart manufacturing. Keep practicing. Keep learning. Keep transforming. To submit a request for a new episode topic from Practitioners Unplugged, visit our contact page [https://www.industrialsage.com/contact/] Thanks for reading. Don’t forget to subscribe to our weekly newsletter [https://www.industrialsage.com/subscribe/] to get every new episode, blog article, and content offer sent directly to your inbox. Explore more about Schneider Electric [https://www.se.com/us/en/] & AVEVA [http://www.aveva.com/en/] [https://www.industrialsage.com/wp-content/uploads/2024/07/Presented-By-Aveva-SE-lockup_Color_Alt_Singleline-300x33.png]

Episode #17 | Open Automation Is Finally Happening: Real-World Proof from Universal Automation

For years, the automation industry talked about decoupling hardware and software. IT/OT convergence became a buzzword that everyone nodded at but few truly believed would arrive. Episode 17 of Practitioners Unplugged, recorded live at Schneider Electric’s Innovation Summit in Las Vegas, proves the skeptics wrong. Greg Boucaud, Chief Marketing Officer of UniversalAutomation.org, and Renato Silva, CEO of Aimirim, shared real implementations, actual deployments, and measurable results. This wasn’t a vision presentation. Instead, it was a field report from practitioners who’ve already made the future work. THE UNIVERSAL AUTOMATION MOVEMENT: FOUR YEARS OF REAL PROGRESS UniversalAutomation.org launched in November 2021 with nine founding members. Four years later, the nonprofit association has grown to 115 members spanning end users, system integrators, technology vendors, and academia. “Our motto in life is to unlock the automation software—decouple hardware and software in the automation space,” Greg explained. While the goal sounds simple, it represents a fundamental shift in how industrial automation functions. Think about your personal computer. You download software, install it, and never wonder about your laptop brand. Industrial automation historically hasn’t worked this way. Instead, you needed the right brand, the correct hardware, and the proper topology. Through open standards—specifically IEC 61499—UniversalAutomation.org brings the IT world’s flexibility to OT environments, enabling true hardware/software decoupling. WHY DECOUPLING MATTERS FOR LONG-TERM INVESTMENT Greg highlighted a critical challenge: “If you invest in your OT systems, your investment is tightly tied to the lifecycle of your hardware. If your hardware tends to be end of life, then you need to reinvest for the next generation.” That’s an expensive, disruptive cycle. When hardware reaches obsolescence, companies face massive capital expenditures to replace entire systems. However, decoupling changes this equation dramatically. Software becomes independent from hardware lifecycles. Manufacturers can upgrade hardware without throwing away automation logic. Furthermore, they can add new capabilities without rip-and-replace projects. For facilities running 20, 30, even 50 years, this matters enormously. Consequently, the ability to evolve automation without complete overhauls transforms how organizations approach digital transformation. THE THREE-PILLAR COMMUNITY What makes UniversalAutomation.org different? A deliberate community structure bringing together three critical groups. Users of automation represent the entire value chain—end users, system integrators, technology integrators like Aimirim, and distributors. Technology vendors include both traditional automation companies and increasingly IT companies attracted by easier data access. Academia completes the picture by training the next generation with full curriculum provided by UniversalAutomation.org. Greg cited a sobering statistic: “By 2030, 2 million jobs will go unfilled in the automation space because of lack of engineering skills.” Therefore, academia’s role in closing this gap becomes strategic, not optional. THE AIMIRIM STORY: NINE YEARS TO WHAT USUALLY TAKES THIRTY Renato Silva’s journey provides the perfect case study for why open standards matter. Aimirim specializes in advanced process control based on artificial intelligence and real-time optimization. Here’s what makes the story remarkable: Aimirim accomplished in nine years what typically takes established companies 30-40 years. Moreover, they achieved this by building on the IEC 61499 framework. “Would it be possible to do in 90 years the same thing we do without a framework for scaling? No,” Renato emphasized. “The scalability of complex technology is only feasible right now because of the standard.” THE BRITISH AMERICAN TOBACCO DEPLOYMENT Aimirim’s flagship implementation with British American Tobacco (BAT) demonstrates open automation’s practical viability. Starting in Uberlândia, Brazil, Aimirim digitalized BAT’s entire industrial operation using IEC 61499 and Universal Automation Organization (UAO) runtime. What started locally scaled globally. Consequently, the same technologies now operate across at least eight countries for BAT, proving the approach works across different regulatory environments. “We could deploy an advanced process control in one week,” Renato explained. “And then they say, can you scale to 15 more facilities?” For startups competing against 30-40 year old companies, the open standard framework became the competitive differentiator. HOW IT WORKS: THE EDGE LAYER TRANSFORMATION Dante asked the technical question practitioners need answered: what compelled choosing IEC 61499 over traditional PLCs and SCADA infrastructure? Renato’s explanation reveals the architectural shift: “The point about the PLC and DCS systems for us is that it became purely infrastructure. We take some edge device—it doesn’t matter the brand—and we fully integrate this edge device to any PLC.” Traditional PLCs lack edge compute power for complex AI models. In contrast, Aimirim’s approach integrates edge compute at the same layer, treating existing PLCs as infrastructure. MAINTAINING SAFETY WHILE ADDING CAPABILITY “If we can read, I can take this information and stream it to a cloud,” Renato explained. “If I can write, I can take some decisions on the edge and instantly write on the PLC.” Critically, this approach maintains safety: “When the PLC becomes infrastructure, we keep the automation as they are. If you turn off my technology, you instantly go back to your old technology.” As a result, this architecture enables brownfield deployments without ripping out existing systems. Organizations add capabilities on top of current infrastructure, upgrading incrementally. WHAT END USERS ACTUALLY CARE ABOUT Renato shared an insight from driving 120,000 kilometers per year for three years, visiting facilities and listening to operators, supervisors, managers, and executives: “The client doesn’t want one standard or another. They just don’t care. They want to know if you as a company are compliant. They want efficiency increase.” This perspective matters. Technology providers often sell features and standards. However, end users buy outcomes and compliance. Sree highlighted the strategic thinking behind standards: “You were able to think two, three steps ahead. The client wants scalability. The value of standards in enabling that.” End users struggle to envision the end state of their digital transformation journey. Therefore, practitioners and vendors thinking strategically understand that standards enable the scalability clients need even when they can’t articulate it. PROVING CAPABILITY THROUGH DEMONSTRATION “It’s a game of proving everything you say,” Renato noted. “You go to a big client and you say, I can deploy an advanced process control in one week. And they say, okay, do it.” The proof comes through demonstration, not presentation. Startups especially must prove capability before negotiating terms. Moreover, standards enable that rapid proof-of-concept by providing frameworks that work reliably. BROWNFIELD, GREENFIELD, AND EVERYTHING BETWEEN Greg emphasized that open automation applies across implementation scenarios, not just new facilities. ExxonMobil’s Baton Rouge project represented greenfield application—full rip and replace using Open Process Automation (OPA) with Universal Automation Organization as a technology enabler. Kongsberg Maritime’s oil and gas platforms demonstrated brownfield application. They couldn’t replace everything on existing platforms. Instead, they added an orchestration layer using UAO technology on top of existing systems. Aimirim’s BAT deployment represented another brownfield approach—facilities with existing infrastructure where new capabilities deployed incrementally. THE ORCHESTRATION LAYER STRATEGY “Some people may tend to think that this technology is only for greenfield application,” Greg noted. “But actually, no. One of the easiest ways is going through the orchestration layer, adding a layer on top of what is existing.” Kongsberg Maritime standardized well barrier testing—previously done manually by different operators in different ways. They automated it using universal automation technology, orchestrating the process without replacing underlying systems. This flexibility matters because few organizations can afford complete system replacements. Furthermore, the ability to add open automation capabilities incrementally, proving value before expanding, enables adoption that wouldn’t happen otherwise. THE OBSOLESCENCE MITIGATION STRATEGY Dante highlighted a powerful advantage: “Creating that abstraction or control layer and being able to manage obsolescence simultaneously, developing your software simultaneously without having to worry about tremendous downtimes.” Traditional automation faces a harsh reality. When hardware reaches end-of-life, organizations face downtime, capital expenditure, and risk. With hardware/software decoupling, organizations abstract the control layer first, then gradually replace underlying hardware. “Building it into that layer over time as opposed to ripping everything out and starting over,” Dante summarized. Greg emphasized the investment perspective: “You need to ensure that this money which is invested, you will have your return on investment quite soon. But as well, that your investment lasts a certain amount of time.” GET FUTURE PRACTITIONERS UNPLUGGED EPISODES Join manufacturing executives getting new conversations and key insights in their inbox. Subscribe Now THE “THIS IS HAPPENING NOW” MOMENT Sree posed the critical question: “Could we say that the big takeaway here is we’ve been talking about this for a while, but this is happening now?” “This is happening now,” Greg confirmed emphatically. “Adoption is happening and adoption is accelerating.” FIFTEEN YEARS FROM VISION TO REALITY The timeline provides context. Germany launched Industry 4.0 in 2010—15 years ago. France called it Industry of the Future. Similarly, the U.S. talked about digitalized industry. “It takes time for sure, because we speak about OT processes, physical processes,” Greg acknowledged. “But luckily now we have the tools. We have the technology. We have the right companies to do it.” Aimirim’s nine-year journey mirrors the Industry 4.0 timeline. The companies, technologies, and standards needed for open automation matured together. What seemed theoretical five years ago now operates in production environments across multiple countries. Renato’s approach to clients captures the moment: “I say to them, you’re gonna make it now or tomorrow. And I am here right now, so why waiting?” THE COMPETITIVE PRESSURE OF OPEN STANDARDS Dante observed an interesting dynamic: democratization of hardware creates competitive pressure on vendors to deliver best-in-class products. “Most systems today are vendor locked. It puts pressure on you as a manufacturer to come out with best in class hardware to compete in this now open space.” Greg acknowledged Schneider Electric’s commitment: “I’m quite proud that Schneider is saying openly we go towards open automation. That’s the way we see it for industry, for energy. This world needs to be open.” This represents a fundamental shift from “lock in the customer and lock out the competition” to competing on hardware quality, service, and ecosystem value. THE OPEN-MINDED REQUIREMENT Renato emphasized mindset as critical to this transformation: “This moment requires a lot of open-minded people. To be with Universal Automation means that you have the right mindset for an open world.” His call to other startups: “It’s not really about the competition. It’s about changing the market. A new market is being created and to be part of it, you have to be open-minded enough to join.” Dante agreed: “Open-minded is what’s definitely missing right now. It’s just rigid thoughts of 50 years of how we’ve done automation systems.” Sree referenced the old approach: “Lock in the customer and lock out the competition.” The future approach recognizes that ecosystems require frictionless exchange of information. Furthermore, open standards provide the foundation that makes ecosystems viable. KEY LESSONS FOR PRACTITIONERS Several critical insights emerged for practitioners evaluating open automation: Standards enable startup speed at enterprise scale. Aimirim’s nine-year achievement demonstrates how frameworks accelerate complex technology deployment. Therefore, standards aren’t bureaucratic overhead—they’re competitive advantages. Brownfield deployment removes the biggest adoption barrier. The ability to add open automation layers on top of existing infrastructure means organizations don’t need greenfield opportunities to start. Moreover, incremental adoption with rapid proof points drives expansion. End users buy outcomes, not standards. While standards enable scalability strategically, sales conversations focus on efficiency and proven results. Consequently, standards matter most in delivery and scaling. Investment protection matters more as facilities age. For 20, 30, 50-year operations, the coupling of software to hardware lifecycles creates expensive replacement cycles. However, decoupling transforms capital planning and operational risk. The ecosystem finally exists. Technology, companies, standards, and talent converged to make open automation viable. What seemed theoretical five years ago now runs in production across industries. Competitive dynamics shift from lock-in to excellence. Vendors must compete on product quality and ecosystem value rather than proprietary control. Consequently, this accelerates innovation and benefits end users. CONCLUSION: FROM TALKING TO DOING Episode 17 marked a transition point in the open automation conversation. For years, industry events featured vision presentations about possibilities. This conversation presented field reports about what’s already working. Greg Boucaud and Renato Silva didn’t pitch concepts. Instead, they shared implementations—British American Tobacco across eight countries, ExxonMobil’s Baton Rouge facility, Kongsberg Maritime’s oil platforms. UniversalAutomation.org’s growth from 9 to 115 members in four years, with 15 commercial offers available, indicates momentum. Moreover, Aimirim’s rapid scaling demonstrates that open standards enable capabilities previously reserved for established players. The convergence of IT and OT that Industry 4.0 promised in 2010 finally materialized in practical, deployable form. Standards matured. Companies built products. Practitioners proved concepts. Furthermore, academia started training the next generation. As Renato told potential clients: “You’re gonna make it now or tomorrow. And I am here right now, so why waiting?” The question for manufacturers isn’t whether open automation will happen—it’s already happening. Rather, the question is whether they’ll lead the transition or scramble to catch up later. For practitioners tired of vendor lock-in and frustrated by hardware obsolescence cycles, the tools exist today. The standards work. The implementations prove viability. Additionally, the ecosystem supports adoption. Open automation isn’t the future anymore. It’s the present for organizations open-minded enough to embrace it. Ready to explore open automation? Visit UniversalAutomation.org [https://universalautomation.org] to learn more about the technology, join the community, and access training resources. Keep practicing. Keep learning. Keep transforming. To submit a request for a new episode topic from Practitioners Unplugged, visit our contact page [https://www.industrialsage.com/contact/] Thanks for reading. Don’t forget to subscribe to our weekly newsletter [https://www.industrialsage.com/subscribe/] to get every new episode, blog article, and content offer sent directly to your inbox. Explore more about Schneider Electric [https://www.se.com/us/en/] & AVEVA [http://www.aveva.com/en/] [https://www.industrialsage.com/wp-content/uploads/2024/07/Presented-By-Aveva-SE-lockup_Color_Alt_Singleline-300x33.png]

Episode #16 | 2025 Year in Review: The Themes That Defined Digital Transformation

As 2025 drew to a close, Episode 16 of Practitioners Unplugged took a reflective look back at the conversations that shaped our understanding of digital transformation throughout the year. Cohosts Dante Vaccaro and Sree Hameed unpacked the common threads, surprising insights, and memorable moments from a year of conversations with practitioners driving real change. What started as a podcast focused broadly on digital transformation evolved into something more nuanced—a collection of stories revealing the human challenges, infrastructure realities, and cultural shifts that determine whether technology initiatives succeed or fail. From live recordings at Automate in Detroit (complete with an infamous train that became a running joke) to conversations about change management and AI’s reality, 2025 brought clarity to what actually matters in Industry 4.0 and beyond. “It really seemed like it kind of morphed into little breadcrumbs from everyone we talked to kind of evolving into different drawdown topics that didn’t even think to consider,” Dante reflected on the year’s journey. A YEAR OF VOICES: THE 2025 GUEST LINEUP The practitioners who made 2025’s conversations possible: * Jonathan Wise, Chief Technology Architect at CESMII * Brett Redmond, EcoStruxure Automation Expert at Schneider Electric * Jim Davis, UCLA Vice Provost IT Emeritus CESMII Program Oversight & Principal Investigator * Daniel Harr, CEO at Delta Systems & Automation * Jim Mayer, Founder of The MFG Connector and Host of Manufacturing Culture Podcast * Jason Head, Controls Development Engineer at Fallas Automation * Jonathan Alexander, Manufacturing AI & Advanced Analytics Manager at Albemarle Intelligence * Ed Koch, Chief Solutions Officer at CCi * Craig Henry, Global Account Director for Amazon at Murrelektronik * Nick Valdez, Automation & Controls Business Development Manager at Vessco Water Each brought unique perspectives from different corners of the industrial ecosystem, painting a comprehensive picture of where digital transformation stood in 2025. THE FIVE MAJOR THEMES THAT EMERGED IN 2025 1. PEOPLE DON’T HATE CHANGE—THEY HATE BEING BLINDSIDED BY IT Jim Mayer delivered one of the year’s most memorable insights when he challenged a fundamental assumption about transformation initiatives. “Humans hate change, and that’s just not true,” Jim explained, “What did you have for lunch today, Sree?” Sree replied, “I had a slice of pizza.” Jim then turned to Dante, “What did you have for lunch today?” Dante replied, “Kebabs.” Jim concluded his point, “I had a wrap. We love change.” The real issue isn’t change itself—it’s how change is managed and communicated. When people feel blindsided, resistance follows naturally. However, when teams are brought along and feel like participants rather than victims, adoption becomes significantly easier. “Change has to be done simultaneously with the strategy, bringing people around from day one,” Dante observed. “It can’t just be the afterthought at the end where we say, hey, nobody’s doing what we set out to do.” THE CENTER OF EXCELLENCE CHALLENGE Sree connected this to multi-site MES rollouts, noting the critical importance of centers of excellence that genuinely included stakeholders rather than dictated to them. When people participated in the design process, projects tended to progress much more smoothly. The lesson applied broadly: organizations needed to question whether they were truly bringing people along or simply informing them of decisions already made. 2. CULTURE WASN’T A SOFT TOPIC—IT WAS THE FOUNDATION FOR TECHNOLOGY ADOPTION Nick Valdez articulated a challenge many guests touched on when discussing water infrastructure modernization: “We struggle with people really understanding what information they need and what’s the best way to achieve that information because not everyone in the water wastewater industry is on the modernization train. They don’t necessarily want to spend the capital or invest the time or energy or effort.” Across industries, culture determined whether organizations could even recognize opportunities for improvement. When “that’s the way we’ve always done it” became the default response, technology investments delivered minimal returns. Jim Mayer’s work on manufacturing culture reinforced this point. His focus on creating environments where people wanted to work rather than simply needed to work addressed the human foundation that made everything else possible. Technology amplified existing culture. If the culture valued learning and improvement, technology accelerated both. If the culture resisted change, technology became another source of friction. 3. TRAINING AND UPSKILLING WEREN’T OPTIONAL ANYMORE—THEY WERE STRATEGIC IMPERATIVES The conversation kept returning to workforce challenges throughout 2025. Experienced workers were retiring with institutional knowledge, younger workers had different expectations about development, and technology evolution meant even veterans needed ongoing skill development. Organizations addressing this successfully shared common approaches: structured knowledge transfer programs, apprenticeship and mentorship models, continuous learning culture, and technology as a capability multiplier rather than replacement. “It does pay off even if it means projects get delayed in terms of being able to find the right resources,” Sree noted. “You do end up making change that is sustainable.” Rushing implementation with inadequate capability development created technical debt. Taking time to build capabilities properly produced more sustainable results. 4. DATA QUALITY AND STANDARDIZATION REMAINED FUNDAMENTAL CHALLENGES While AI grabbed headlines throughout 2025, practitioners consistently emphasized that more fundamental data challenges continued to limit what organizations could actually accomplish with advanced technologies. Jonathan Wise’s discussions around Unified Namespace and Craig Henry’s “industrial nervous system” metaphor reinforced the same point: organizations investing heavily in AI (the “brain”) while neglecting connectivity and data infrastructure (the “nervous system”) created powerful capabilities that couldn’t sense what was happening on the factory floor. Organizations making progress addressed these systematically rather than expecting AI to magically overcome poor data foundations. They invested in connectivity, established data governance, and created infrastructure that enabled data to flow where it was needed when it was needed. 5. AI’S PROMISE VERSUS REALITY—CLOSING THE GAP REQUIRED HONESTY If there was one topic that generated both excitement and skepticism in 2025, it was artificial intelligence. The year brought clarity about the gap between vision and reality. Sree captured the challenge: “I look at AI and my reaction is that is not in my comfort zone. I want explainability and transparency and see the promise of AI and I’m still okay, there’s a lot of learning to do here.” When AI systems functioned as “black boxes” without explaining reasoning, practitioners struggled to trust them for critical decisions. In manufacturing operations where safety, quality, and efficiency had direct consequences, this transparency gap mattered enormously. PRACTICAL AI VERSUS GENERATIVE HYPE Dante made an important distinction: “When we talk about practical AI, this goes back into what’s proven. This is more machine learning. This is neural network building. All of this stuff existed before without the generative component to it on top.” Established forms of AI—machine learning for predictive maintenance, computer vision for quality control, optimization algorithms—had proven track records. These applications delivered measurable value in specific use cases. In contrast, generative AI represented something newer, less proven in industrial contexts. While the promise was significant, so were the unknowns around reliability and appropriate applications in high-stakes environments. The conversation pointed toward where 2026 needed to evolve: from hype toward practical implementation stories. What was working? What wasn’t? How could organizations maintain human expertise even as they deployed AI tools? GET FUTURE PRACTITIONERS UNPLUGGED EPISODES Join manufacturing executives getting new conversations and key insights in their inbox. Subscribe Now THE INDUSTRY 4.0 TO INDUSTRY 5.0 PROGRESSION: NO SKIPPING STEPS One of the year’s clearest messages: organizations couldn’t skip foundational work. As a customer Sree referenced noted: “There is no Industry 4.0 without Industry 3.0. It builds on that, right?” Organizations rushing to embrace Industry 5.0 concepts without properly implementing Industry 4.0 foundations faced significant challenges. “If you didn’t start your Industry 4.0, you’re going to be left in the dust,” Dante emphasized. Successful modernization required honest assessment of current capabilities and systematic progression rather than attempting to leapfrog without building necessary foundations. LESSONS FROM LIVE RECORDING: THE INFAMOUS AUTOMATE TRAIN The live recording experiences from Automate in Detroit added memorable dimension to 2025’s podcast journey. Recording on the show floor captured real energy and context—along with an unexpected guest star: a train that repeatedly rolled through recordings, eventually becoming a running joke turned into a montage of train puns. “I didn’t realize actually how many times that train really just disrupted the flow of the conversation,” Dante laughed while reflecting on the experience. The incident illustrated something important: authenticity and real-world context mattered more than perfectly controlled conditions. Real implementation happened in messy, imperfect environments. Success came from adapting and learning rather than waiting for ideal circumstances that never arrived. LOOKING AHEAD: THE 2026 RESEARCH AGENDA As 2025 concluded, Dante and Sree outlined what they hoped to explore in 2026: more stories, more specifics, more honest accounts of what was working and what wasn’t. “Stories, successes, trials, tribulations, what’s working, what’s not,” Dante outlined. “Learning the biggest impacts, the biggest failures.” The emphasis on practical AI over hype would continue. The focus on people and culture alongside technology would remain central. And the commitment to learning from practitioners actually implementing initiatives rather than consultants selling visions would define the podcast’s approach. THE BROADER LESSON: TRANSFORMATION REQUIRED INTEGRATED THINKING If 2025’s conversations proved anything, it was that successful digital transformation required integration across multiple dimensions simultaneously. The best technology failed without capable, engaged people. Brilliant strategies couldn’t overcome cultures that resisted change. Big visions meant nothing without foundational infrastructure to support them. Organizations that fragmented these elements—treating culture as HR’s job, technology as IT’s responsibility, strategy as leadership’s domain—struggled to achieve transformation that stuck. Those that recognized these elements must evolve together created conditions where change could take root and grow. GRATITUDE AND LOOKING FORWARD Dante and Sree expressed appreciation for their sponsors—Schneider Electric and AVEVA—whose support made the podcast possible while allowing editorial freedom. Most importantly, they thanked listeners who showed up, shared episodes, and provided feedback throughout the year. The invitation remained open: if there were guests who should be featured, topics that needed exploration, or perspectives missing, the Practitioners Unplugged team wanted to hear about it. The community shaped the content, and that collaborative approach aligned with the podcast’s philosophy that the best insights came from practitioners sharing real experiences. CONCLUSION: THE YEAR THAT GROUNDED DIGITAL TRANSFORMATION Looking back at 2025, Practitioners Unplugged provided something increasingly rare in discussions about digital transformation: grounding in reality. The practitioners featured throughout the year offered nuanced perspectives. Yes, technology enabled new possibilities. But also: people and culture mattered more than most discussions acknowledged. Infrastructure determined whether advanced capabilities could actually function. Sustainable change required bringing teams along. And honest assessment of what was working versus hype helped organizations invest wisely. THE PATH FORWARD As manufacturing and industrial operations moved deeper into Industry 4.0 and began exploring Industry 5.0 concepts, these grounded perspectives became increasingly valuable. Organizations that would thrive wouldn’t necessarily be those with the biggest technology budgets. Rather, they would be the ones that systematically built capabilities, developed their people, strengthened their culture, and deployed technology thoughtfully. Practitioners featured in 2025 understood this. Their stories, struggles, and successes provided the practical wisdom that helped other organizations navigate similar journeys. That was the value Practitioners Unplugged delivered—not abstract theories or consultant frameworks, but lived experience from people doing the work. Here’s to another year of conversations that cut through hype, celebrate honest problem-solving, and build community among practitioners driving real change. Keep practicing. Keep learning. Keep transforming. To submit a request for a new episode topic from Practitioners Unplugged, visit our contact page [https://www.industrialsage.com/contact/] Thanks for reading. Don’t forget to subscribe to our weekly newsletter [https://www.industrialsage.com/subscribe/] to get every new episode, blog article, and content offer sent directly to your inbox. Explore more about Schneider Electric [https://www.se.com/us/en/] & AVEVA [http://www.aveva.com/en/] [https://www.industrialsage.com/wp-content/uploads/2024/07/Presented-By-Aveva-SE-lockup_Color_Alt_Singleline-300x33.png]

Episode #15 | From Run-to-Failure to Predictive Operations: Transforming Water Infrastructure

---------------------------------------- FROM RUN-TO-FAILURE TO PREDICTIVE OPERATIONS: TRANSFORMING WATER INFRASTRUCTURE WITH NICK VALDEZ Most people take for granted that clean water flows when they turn on the faucet. Wastewater disappears when they flush. Episode 15 of Practitioners Unplugged pulls back the curtain on this critical infrastructure with Nick Valdez, Automation & Controls Business Development Manager at Vessco Water. He reveals how digital transformation is revolutionizing an industry that quietly serves every community. Operating across 41 states through a portfolio of acquired companies, Vessco Water represents the evolution from component supplier to comprehensive solutions provider. Nick’s journey—from culinary school dropout to manufacturing to leading automation initiatives for water/wastewater systems—provides unique perspective on bringing change to an industry historically resistant to modernization. This conversation explores a different dimension of Industry 4.0: not sexy manufacturing facilities, but the essential infrastructure that determines whether communities can grow, whether rivers stay clean, and whether taxpayers get value from their utility investments. As Nick puts it: “A lot of our customers don’t know what they don’t know. They don’t know that there are great products that can help them be smarter and better. They really lean on us as a platform to help them solve their problems.” KEY INSIGHTS FROM OUR CONVERSATION Here are the five key insights from our conversation with Nick: 1. THE VIRTUOUS CYCLE—STARTING SMALL CREATES UNSTOPPABLE MOMENTUM Water and wastewater utilities face a classic chicken-and-egg problem. They won’t invest in sensors and data infrastructure until they see value. But they can’t see value without data. Nick’s team has mastered breaking this impasse by creating what he calls the “virtuous cycle.” (Originally “drinking the Kool-Aid” before our marketing expert Sree upgraded the terminology.) “Once they start, it continues, it perpetuates. It’s almost incredible to watch how customers really do drink the Kool-Aid and say, oh wow, this is incredible. We’re able to have this information, now we can use it, and then it makes their lives a lot easier.” HOW THE PATTERN REPEATS Across municipalities, the pattern repeats consistently. Initial reluctance gives way to pilot projects. Pilot results then drive broader deployment. Suddenly, utilities that ran equipment from the 1970s until failure are calling to retrofit entire station networks. What’s the key? Demonstrating tangible benefits in the first installation. This includes energy reduction, better operational visibility, or predictive maintenance that prevents costly failures. Moreover, this insight challenges the “big bang” digital transformation approach. In water infrastructure, patience and proof points matter more than comprehensive strategies. One successful pump station with VFD controls and smart analytics generates more momentum than any presentation about Industry 4.0 possibilities. The challenge Nick identifies is clear: “We struggle with people really understanding what information they need and what’s the best way to achieve that information because not everyone in the water wastewater industry is on the modernization train.” 2. REGIONAL DIVERSITY DEMANDS FLEXIBLE SOLUTIONS—41 STATES, 41 DIFFERENT MINDSETS Vessco Water’s geographic spread—41 states and growing—provides insight into how dramatically water infrastructure approaches vary across America. New York City faces completely different challenges and regulations than Iowa communities. This requires solutions that adapt while maintaining quality standards. “In New York City, our platform partners there have a different challenge and different mindset of their customer than say what one in Iowa does. The real trick to it all is for us as a platform to have the resources and the availability of equipment and engineering and manufacturing to make a holistic approach to solving each of the different mindsets of our customers.” THE PILLAR STRATEGY Consequently, this diversity drives Vessco Water’s pillar strategy: service, aftermarket, automation and controls, pumps, and distributed products. Rather than forcing one-size-fits-all solutions, they combine specialized capabilities from different regional partners to address local requirements. For example, an Iowa partner specializing in pump distribution might team with a regional automation expert to serve an engineering firm’s specific needs. The lesson extends beyond water infrastructure to any organization serving diverse markets. Standardization matters for capabilities and quality. But application requires flexibility. Build pillars of expertise that can be combined differently depending on customer context rather than rigid solutions that ignore regional differences. Nick’s point about becoming “subject matter experts” resonates here. Customers lean on Vessco Water precisely because they understand the nuances of different regulatory environments, population densities, and community expectations across geographies. 3. RELATIONSHIPS TRUMP TRANSACTIONS—EQUIPMENT THAT LASTS DECADES REQUIRES TRUST Unlike consumer goods or even most industrial equipment, water infrastructure investments span decades. This time horizon fundamentally changes how buying decisions happen and what matters to customers evaluating partners. “People buy from people in our industry. It’s very rare someone looks on the internet and just says, oh, I wanna buy a flight pump. They know the local community uses them. They call their local rep or distributor. They call one of our platform partners, come out and talk to me. Let’s build a relationship because the equipment that you’re gonna put in and the solution you’re gonna provide has to last for decades. That’s the expectation.” BUILDING TRUST THROUGH EDUCATION This relationship focus shapes Vessco Water’s entire approach. They offer free training classes on drives and pump optimization. They provide arc flash studies and safety training. They bring mobile equipment demonstrations to municipalities and colleges. These investments build trust and educate customers who “don’t know what they don’t know” about available solutions. The strategy addresses a critical industry challenge: water infrastructure expertise is retiring without adequate knowledge transfer. Vessco Water’s “new leaders group” creates mentorship paths where experienced professionals transfer “ancestral knowledge” about handling specific situations and selecting appropriate equipment. THE BROADER LESSON In industries with long equipment lifecycles and high switching costs, customer education and relationship building deliver better returns than transactional selling. Your ability to help customers make informed decisions matters more than any individual product sale. GET FUTURE PRACTITIONERS UNPLUGGED EPISODES Join manufacturing executives getting new conversations and key insights in their inbox. Subscribe Now 4. RUN-TO-FAILURE IS EXPENSIVE—PREDICTIVE OPERATIONS DELIVER MULTI-DIMENSIONAL VALUE Nick’s Minnesota success story illustrates how modernization transforms economics and community impact simultaneously. A municipality running pumps with “archaic” starting methods moved to variable frequency drives with smart analytics. This generated benefits across multiple dimensions. “They were able to reduce the amount of energy they were gonna have to use for their treatment of wastewater. They were able to support more people moving to that city. We could interpolate and predict high flow scenarios. So when it was gonna rain or when people were getting off work, we were gonna have more of an intake to the facility.” MULTI-DIMENSIONAL BENEFITS Energy optimization reduced costs for taxpayers. Predictive capabilities prevented overflow events that would contaminate rivers and trigger regulatory fines. Better operational control enabled the municipality to support population growth. The technology investment paid dividends far beyond the initial business case. Nick emphasizes downstream effects people don’t consider: “If they don’t have equipment in place that can understand that and predict that, or recognize that scenario in real time and then augment and change to mitigate it, then they do have these events where maybe they flood a whole bunch of houses or there’s regulatory fines and penalties for them having to divert effluent into a creek or a river.” The parallel to manufacturing is clear: digital transformation delivers value across multiple dimensions simultaneously. Don’t evaluate investments purely on energy savings or maintenance reduction. Consider community impact, regulatory compliance, growth enablement, and risk mitigation together. 5. CULTURE AND QUALITY CONTROL DRIVE INSOURCING DECISIONS—BRAND PROMISE MATTERS MORE THAN COST While many manufacturers outsource to reduce costs, Vessco Water makes the opposite choice. Nick explains their decision to keep manufacturing, engineering, and quality control in-house despite seeing competitors find success with outsourcing. “If we outsource some of that work, the quality control measure gets limited. We want to control the quality that our customers get and the experience that they have so we can put our stamp and brand on it and we know for a fact what the outcome’s gonna be.” BRAND PROMISE OVER COST OPTIMIZATION This reflects a broader philosophy about customer experience versus short-term cost optimization. Vessco Water offers service agreements guaranteeing pump replacement every five years and 100% operational uptime. Delivering on these promises requires controlling the entire value chain. Furthermore, Nick’s passion for company culture is evident: “Everybody is important. Everybody has their role and responsibilities that contribute to it, and we all breathe and believe in the same thing as we have one common goal. The most beautiful thing about our company is our culture.” ADDRESSING TALENT CHALLENGES In addition, the insourcing decision also addresses talent challenges. Rather than struggling to find experienced engineers in a tight market, Vessco Water invests in developing people through mentorship, cross-platform learning boot camps, and technology that amplifies individual capabilities. The strategic lesson: outsourcing and cost reduction aren’t always optimal strategies. When brand reputation and customer experience drive competitive advantage, controlling quality through vertical integration may deliver better long-term value despite higher upfront costs. CONCLUSION: ESSENTIAL INFRASTRUCTURE DESERVES MODERN OPERATIONS Nick Valdez’s perspective reveals that digital transformation reaches far beyond traditional manufacturing into infrastructure that touches every home and business daily. Water and wastewater systems represent critical infrastructure where modernization delivers community benefits that extend well beyond operational efficiency. KEY TAKEAWAYS FOR PRACTITIONERS First, start small to create momentum through demonstrated value. Build flexible solutions that adapt to regional requirements while maintaining quality standards. Invest in relationships and education because equipment lifecycles demand trust. Evaluate modernization through multiple value dimensions including community impact. Consider whether vertical integration better serves brand promises than cost optimization. As Nick advises those hesitant about modernization: “Pick up the phone and call somebody. Reach out, go to your local distributor, go to your local channel partner. Learn what’s out there. Really give yourself the opportunity to understand that there are incredible products and technology that can reduce the amount of headache and heartburn. Be proactive, not reactive. The more proactive you are, the less reactive you have to be.” THE BIGGER PICTURE The water infrastructure story provides valuable perspective for all digital transformation initiatives. Technology alone doesn’t create value. Technology combined with trusted partnerships, customer education, and commitment to quality experiences drives lasting change. While manufacturing often dominates Industry 4.0 conversations, infrastructure modernization demonstrates how these same principles apply to essential services that most people never think about until something goes wrong. The municipalities transforming from run-to-failure to predictive operations create value that reaches every constituent, even if that value remains invisible when everything works properly. The ultimate measure of success isn’t impressive technology demonstrations but communities where clean water flows reliably, wastewater disappears safely, and infrastructure adapts to support growth while protecting the environment. That requires exactly the combination Nick describes: smart technology, trusted relationships, and commitment to customer experience over transactions. FINAL THOUGHTS While people may take clean water for granted, the professionals modernizing infrastructure understand that reliability requires constant innovation and partnership. The transformation from archaic pump stations to predictive operations happens one relationship, one pilot project, and one virtuous cycle at a time. To submit a request for a new episode topic from Practitioners Unplugged, visit our contact page [https://www.industrialsage.com/contact/] Thanks for reading. Don’t forget to subscribe to our weekly newsletter [https://www.industrialsage.com/subscribe/] to get every new episode, blog article, and content offer sent directly to your inbox. Explore more about Schneider Electric [https://www.se.com/us/en/] & AVEVA [http://www.aveva.com/en/] [https://www.industrialsage.com/wp-content/uploads/2024/07/Presented-By-Aveva-SE-lockup_Color_Alt_Singleline-300x33.png]

Episode #14 | The Industrial Nervous System: Why Your Factory’s AI Brain Needs a Body with Craig Henry

If you’ve invested in AI, machine learning, and digital twins only to see disappointing returns, Episode 14 of Practitioners Unplugged diagnoses the problem. Craig Henry, Global Account Director for Amazon at Murrelektronik and author of Super Connected: The Future of Industrial Nervous System, cuts through the AI hype with a sobering truth: your factory’s expanding “brain” is useless without a properly designed nervous system to connect it to reality. With over 30 years in advanced manufacturing and inter-logistic systems—including major roles at Amazon, Siemens, and Danaher—Craig brings a practical, infrastructure-focused perspective to Industry 4.0 and 5.0. His book and this conversation challenge the current obsession with AI capabilities by asking a more fundamental question: can your AI actually feel what’s happening on your factory floor? As Craig puts it: “We’re operating a brain that is suspended in space and isn’t connected to a body. Without the nervous system, we are crippled.” Here are the five key insights from our conversation with Craig: 1. THE FORGOTTEN MIDDLE—INFRASTRUCTURE IS YOUR REAL COMPETITIVE ADVANTAGE While manufacturers pour resources into AI analytics platforms (the “brain”) and field devices (the “extremities”), Craig identifies a critical gap: the connectivity layer that bridges them. This “forgotten middle” represents the difference between AI that transforms operations and AI that generates impressive demos with no business impact. “As I’ve talked with Amazon and others in the field, I’m seeing that when you get the connectivity right, it opens up all of the promises of Industry 4.0 and Industry 5.0 and the digital twin. But without it we are crippled.” The problem is pervasive: manufacturers operate with 30-year-old control systems that create “black box effects.” A CEO cannot drill down through cybersecurity, edge infrastructure, and proprietary PLCs to see a single sensor reading that might explain why a critical customer order is delayed. The data exists but remains invisible. Craig’s prescription: invest in the forgotten middle before investing in AI. Move from analog signals to digital communication networks. Implement open architectures like OPC UA that expose data across the organization. This infrastructure investment delivers the fastest ROI because it enables you to see and feel what’s happening across your operations for the first time. The parallel to Amazon’s approach is instructive: Jeff Bezos mandated 20 years ago that every system would have an open API with exposed data. This infrastructure-first philosophy enabled Amazon’s rapid innovation and operational excellence—not because they had better AI, but because their AI could actually see the operation. 2. DIGITAL NETWORKS BEAT ANALOG SIGNALS—EVEN WHEN INSTALLATION COSTS $20,000 Craig addresses the objection every plant engineer faces: why spend $20,000 installing a $200 sensor when budget pressures demand “value engineering”? His answer reframes the investment from cost to insurance against catastrophic failure. “I would venture to say having that data could mean you’ve saved a million dollar problem down the line from happening. And the $20,000 would be small compared to what could be just operating blindly and hoping for the best.” The critical distinction: don’t install analog signals—install communication networks. Run digital, self-checking, deterministic, error-checking protocols through that expensive conduit run. This enables condition monitoring that moves unplanned downtime to planned maintenance, a transformation that pays for sensor investments many times over. Craig cites the harsh reality of “value engineering” in capital projects: data infrastructure gets cut first, then costs 30-50% more to retrofit later when problems emerge. Leading organizations take the opposite approach—they get data first, even before knowing exactly how it will be used, because they understand the infrastructure enables future capabilities. The lesson extends to OEMs and system integrators: companies that deliver equipment with comprehensive digital twins and exposed data differentiate themselves from competitors still selling hardware. The conversation shifts from price to ROI when you can demonstrate how your system will improve throughput by specific percentages. 3. HUMAN IN COMMAND, NOT JUST IN THE LOOP—AUTOMATION’S CRITICAL DESIGN PRINCIPLE Craig challenges both the “lights out factory” dream and the passive “human in the loop” compromise with a more sophisticated paradigm: human in command. This distinction becomes critical as automation advances and skills fade threatens operational resilience. “It’s not human in the loop, but human in command. The system should be able to push up to him: I’m seeing this. Here are three options. Please choose one and approve it.” The analogy to chess masters illustrates the point: the highest performance comes from humans with computer assistance, not computers alone. The master can recognize patterns, apply judgment, and execute strategies that algorithms miss. Similarly, factory operators should manage 20 stations with AI flagging exceptions and recommending actions rather than pushing buttons on individual machines. This approach addresses multiple converging crises: the global labor shortage (500,000 positions unfilled in U.S. fulfillment alone), the competency crisis (87% of companies cite skill gaps as their biggest constraint), and the skills fade problem (automation that works well until catastrophic failure when humans have stopped understanding the underlying process). Craig’s warning about autonomous driving accidents applies equally to manufacturing: when humans assume automation has everything under control, disasters happen. The solution isn’t eliminating automation but designing systems where humans maintain operational understanding and decision authority even as AI handles routine optimization. GET FUTURE PRACTITIONERS UNPLUGGED EPISODES Join manufacturing executives getting new conversations and key insights in their inbox. Subscribe Now 4. OPEN STANDARDS ARE NON-NEGOTIABLE—PROPRIETARY SYSTEMS ARE RANSOM, NOT STRATEGY Craig takes a strong stance on the standards debate, arguing that proprietary protocols and closed systems amount to holding customers hostage. For manufacturers evaluating equipment purchases or system upgrades, this represents a critical strategic decision. “If I decide, hey, I’m going to force my customers who buy my equipment to use my protocols and my networks to the exclusion of everybody else, what they’re really doing is holding their customer for ransom. And that’s not cool. It’s not okay.” His recommendation is clear: use OPC UA, which bridges devices to cloud, includes built-in encryption, and democratizes access across vendors. Avoid fieldbus systems controlled by single vendors. Demand that OEMs expose data through standard interfaces even if internal IP remains protected. The business case for open standards extends beyond technical elegance. Standards enable faster deployment, broader talent pools for implementation and support, and protection against vendor dependency. When Amazon and other large end-users mandate specific protocols, they’re protecting their ability to innovate independent of equipment vendor roadmaps. For OEMs, Craig’s advice flips the conventional wisdom: don’t view open standards as giving away competitive advantage. Instead, differentiate through consulting on process improvement and ROI rather than locking in through proprietary interfaces. Companies that help customers achieve measurable performance gains win business regardless of protocol choices. 5. CYBERSECURITY IS EVERYONE’S PROBLEM—AND SKILLS FADE IS YOUR HIDDEN VULNERABILITY Craig delivers sobering statistics: cybersecurity attacks now generate more revenue than illegal drug trafficking, with loss of use (ransomware) as the primary attack vector. For manufacturers, this isn’t just an IT problem—it’s an operational resilience issue that requires scenario planning and regular drills. “We have to be able to have plan A, plan B, plan C, and to your point that a human is there skilled and experienced enough to be able to drive that and to make those decisions.” The challenge intensifies with automation dependence. Craig’s example of his wife’s county clerk office illustrates the problem: when systems went down, resistance to manual processes was so strong that basic operations nearly stopped despite manual procedures being available. In manufacturing, returning to manual operation may be impossible when robots perform tasks no human workforce could replicate. The solution requires acknowledging that attacks will happen and preparing accordingly: secure data in three places, maintain operational knowledge that doesn’t depend on systems, and ensure humans understand underlying processes enough to make decisions during disruptions. This represents the flip side of the human-in-command principle—humans must maintain enough competency to take control when automation fails or becomes compromised. Craig’s perspective on large language models adds another dimension: 80% of people using LLMs can’t recall the content they produced. If we build similar dependency in manufacturing operations, how do humans respond when AI systems become corrupted? The answer requires intentional design to maintain human competency even as automation advances. CONCLUSION: BUILDING THE BODY YOUR AI BRAIN NEEDS Craig Henry’s infrastructure-focused approach provides the reality check that digital transformation initiatives need. While the industry obsesses over AI capabilities—with projects like Stargate committing $400 billion to expand the “brain”—the nervous system that connects that brain to physical operations lags dangerously behind. The key lessons for practitioners: invest in the forgotten middle connectivity layer before chasing AI solutions, move from analog signals to digital communication networks throughout your operations, design for humans in command rather than lights-out automation, demand open standards that prevent vendor lock-in, and prepare for disruption through scenario planning and competency maintenance. As Craig warns, “We have an uninformed brain floating in space, thinking it understands things.” The physical world of manufacturing requires more than thinking—it requires feeling, sensing, and responding through a properly designed nervous system. The path forward isn’t abandoning AI but building the infrastructure foundation that makes AI useful. Organizations that invest in super-connected operations—with digital networks exposing real-time data, open standards enabling scalability, and humans maintaining command authority—position themselves to leverage whatever technologies emerge next. The revolution isn’t in the AI capabilities themselves but in the infrastructure that lets those capabilities touch reality. Build the nervous system first, and the brain’s potential becomes achievable. Skip this step, and your AI investments remain impressive demonstrations disconnected from operational impact. The question isn’t whether to invest in digital transformation but where to invest first. Craig’s answer is clear: start with the body your AI brain needs to function. To submit a request for a new episode topic from Practitioners Unplugged, visit our contact page [https://www.industrialsage.com/contact/] Thanks for reading. Don’t forget to subscribe to our weekly newsletter [https://www.industrialsage.com/subscribe/] to get every new episode, blog article, and content offer sent directly to your inbox. Explore more about Schneider Electric [https://www.se.com/us/en/] & AVEVA [http://www.aveva.com/en/] [https://www.industrialsage.com/wp-content/uploads/2024/07/Presented-By-Aveva-SE-lockup_Color_Alt_Singleline-300x33.png]