Manufacturing the Future

Epicor
  • 5.0 (4)
  • Business
  • Updated Biweekly

Manufacturing the Future is dedicated to helping manufacturing leaders future-proof their operations. Each episode features interviews with innovative manufacturing executives, subject matter experts, and thought leaders who share actionable insights, tips, and best practices to embrace technology so they can streamline operations, prepare for what lies ahead, and continue to keep the world turning.

  1. 3d ago

    Harmar's Stephen Hightower on the data problem hiding behind AI in manufacturing

    "They have a data problem that's wearing an AI costume. Because if you don't have accurate data, it doesn't matter what you do, you just do it faster." – Stephen Hightower A sharp wake-up call from Stephen Hightower, Chief Technology Officer at Harmar, who put a moratorium on development until his team fixed the data underneath. The problem he's solving isn't just data quality, it's the operational waste that builds up when three integrated enterprise systems don't agree with each other, manual workarounds become tribal knowledge, and spreadsheets quietly replace the systems people no longer trust. When your data is broken, AI doesn't fix it. It just does the wrong thing faster. In This Episode: Stephen walks through how he's rebuilding data confidence at Harmar, a manufacturer of mobility and accessibility solutions. He describes launching a Master Data Initiative using CRUD and RACI matrices to assign clear ownership for every critical data element across engineering, ERP, and customer systems. He explains why cycle time, quality, and unit cost are the only three metrics that matter in manufacturing, and how tracking integration error rates across systems exposes where data breaks down. Stephen also shares how his Lean Six Sigma background, starting in the late 90s at Lockheed Martin, shaped his approach to treating broken tech stacks as waste to be eliminated through root cause analysis and corrective action. He describes putting monitoring tools in place to gain insight the ERP system wasn't providing, deploying a digital worker to handle customer care calls so his team can move up the value chain, and using the financial close cycle time as a diagnostic for how well a business is really running. He's also candid about AI's limitations: he uses Claude for data analysis and engineering cycle time problems, but stresses that every AI output requires human verification because it will, in his words, "lie to you all day long." Topics: Why most AI failures start with a data problem wearing an AI costumeRunning a master data initiative using CRUD and RACI matrices for clear ownershipTracking integration error rates across enterprise systems to expose wasteApplying Lean Six Sigma to broken technology stacksFinding the hidden spreadsheets that signal system waste and broken trustUsing monitoring tools to gain real operational insight the ERP wasn't providingDeploying a digital worker for customer care operationsWhy financial close cycle time reveals operational healthThe "go find the spreadsheets" test for any manufacturing business A conversation with Stephen Hightower of Harmar about why most manufacturers have a data problem wearing an AI costume, and how master data management and Lean Six Sigma applied to technology fix it from the inside. Download, Listen, and SubscribeApple | Spotify | YouTubeOr search "Manufacturing the Future" wherever you listen to podcasts!

    Harmar's Stephen Hightower on the data problem hiding behind AI in manufacturing

  2. Jul 30

    Tyler Madsen and Jason Bassett on cutting spec review from 2 hours to 15 seconds with AI

    "What used to take me two hours takes me about 15 seconds now." – Tyler Madsen A striking before and after from Tyler Madsen, Director at Madsen's Millwork & Custom Cabinets, who rebuilt their estimating workflow by feeding drawings and specifications into an AI bot that strips out irrelevant data and returns only what's needed to quote a job. The broader problem he and IT & Asset Manager Jason Bassett are solving isn't just speed, it's the operational drag that builds up when a manufacturing shop is still running on paper drawings, manual data sorting, and an IT person who becomes the bottleneck every time someone needs an answer. When information lives on paper, you get version control failures, field installers working off outdated drawings, and a team spending its time managing data instead of acting on it. In This Episode: Tyler and Jason walk through how Madsen's Millwork has digitized its day to day operations, from estimating to the shop floor to field installation. Tyler describes feeding specs and drawings into an AI bot that strips out irrelevant data for quoting. Jason covers the physical changes on the shop floor: big screen displays at every workstation now pull live drawings, replacing paper that created double data sets and made version control nearly impossible. He also gives field installers the same live job data on site, so a mid job change reaches them in real time, and describes building knowledge banks inside Epicor Prism pre-loaded with the questions his team most commonly brought to IT, so employees self-serve instantly instead of waiting on him. They're also candid about what isn't solved yet: getting skilled trades workers to trust and adopt AI day to day remains an open challenge, and they also flag hallucinations as a real operational risk that requires experienced human oversight to catch. Topics Cutting spec review from two hours to 15 seconds using an AI bot Building Epicor Prism knowledge banks to eliminate the IT bottleneck AI owns data retrieval; humans own judgment, their workflow decision framework The mutual checking model: humans verify AI output, AI challenges human decisions Replacing paper drawings with live digital displays at every shop workstation Field installers accessing real-time job drawings remotely during installation Using client AI renderings as the engineering starting point for custom projects Why getting skilled trades workers to trust AI remains their biggest unsolved challenge Hallucination risk in manufacturing operations and how to stay vigilant Download, Listen, and Subscribe Epicor | ⁠Apple⁠ | ⁠Spotify⁠ | ⁠YouTube⁠ Or search “Manufacturing the Future” wherever you listen to podcasts!

    Tyler Madsen and Jason Bassett on cutting spec review from 2 hours to 15 seconds with AI

  3. Jul 16

    Mike Wargocki on how Framebridge pushed gross margin from 27% to 40% during peak season

    "Everything is basically a fact-finding mission. You're trying to figure out what you can do, how fast you can do it, and how efficiently you can do it." – Mike Wargocki Manufacturing leaders who scale fast tend to break their own operations without realizing it, not through a single bad decision, but through a string of reasonable ones: reinvesting in an existing plant one quarter too late, forcing identical equipment into buildings that were never built for it, or promoting an early team member into a role they were never suited for. The trouble is that most of these metrics and mistakes don't show up on a standard dashboard. Mike Wargocki has spent his career finding the operational truths that hold across food, biotech, and custom consumer manufacturing, and figuring out which numbers actually predict performance versus which ones just look good in a report.Much of this conversation draws on Mike's time at Framebridge, a company rethinking how custom framing is designed, produced, and delivered. Framebridge built a direct-to-consumer model that turned a traditionally complex, expensive process into something far more accessible, and has produced over two million custom frames as a result. The company has continued scaling quickly, bringing new manufacturing facilities online across the US to support both e-commerce and retail growth. In This Episode: Mike Wargocki, VP of US Operations at DINGS' Motion USA, walks through the operational lessons he built over a career spanning research chemistry, food, biotech, and custom consumer manufacturing. He explains why OEE stops being a useful metric once production gets custom, and why he shut down a limestone cave facility outside St. Louis despite its near-free refrigeration, once quality started slipping. He breaks down the real cost of forcing identical equipment across a multi-site network, how to time a new facility build against a real growth plateau instead of a projected one, and how his team planned peak season staffing at Framebridge without blowing the annual budget. He also shares where he sees manufacturing leaders waste money without noticing, why early employees aren't always the right fit for the next stage of growth, and how his team has used AI tools to help non-native English speakers write difficult workplace communications. Topics discussed: Why OEE fails as a metric in custom manufacturingThe real cost of forcing equipment uniformity across facilitiesTiming new facility builds against a growth plateauBalancing peak season staffing without blowing the annual budgetClosing a newly built facility over a hidden quality trade-offApplying a chemist's fact-finding approach to operations leadershipRight-sizing early team members as a company scalesUsing AI to help non-native speakers write difficult communications Download, Listen, and Subscribe Apple | Spotify | YouTube Or search “Manufacturing the Future” wherever you listen to podcasts!

    Mike Wargocki on how Framebridge pushed gross margin from 27% to 40% during peak season

  4. Jun 18

    Daniel Topp on why ERP projects fail at training, not technology

    "We're common where possible and unique where necessary." A deceptively simple principle from Daniel Topp, VP of IT at TASI Measurement, that gets very complicated when you're managing ERP across 16 autonomous business units and integrating newly acquired companies on a rolling basis. The real question is how you operationalize it so it doesn't collapse under the weight of competing business unit priorities and leadership requests for customization. TASI Measurement is a global industrial measurement holding company with more than 1,000 employees, headquartered in Largo, Florida, operating through a highly decentralized structure where each business unit runs independently under the broader group. In This Episode: Daniel walks through the specific systems he's built to keep ERP standardization from becoming a constant negotiation. That includes a formal customization approval process requiring sign-off from key stakeholders before any deviation from off-the-shelf is permitted, and a 30-60-90 day acquisition integration playbook that separates non-negotiables like IT security tools from ERP decisions, which get evaluated through a risk and value heat map. He explains why data migration is where repeat ERP transformations actually improve, and why building a dedicated headquarters-level migration team, rather than relying on business unit staff, is what makes the process repeatable and scalable. He also makes the case that locking in structural decisions like chart of accounts early in a project is the difference between finishing on time and losing months at the end. On AI, his position is direct: having it available inside your ERP without a structured rollout plan is a liability, not an advantage. Topics: Why ERP projects fail at training and change management, not implementation Formal customization approval process requiring stakeholder sign-off 30-60-90 day acquisition integration playbook and what's non-negotiable from day one Risk and value heat map for sequencing ERP integration priorities across acquisitions Gold standards center of excellence and how it serves newly acquired businesses Why locking in decisions like chart of accounts early can make or break a project timeline Building a dedicated, headquarters-level data migration team as a repeatable capability Unstructured AI rollout inside ERP as an organizational liability Translating IT efficiency into quantified dollar savings to shift IT from cost center to strategic partner Meta Description: A conversation with Daniel Topp, VP of IT at TASI Measurement, about how he built repeatable systems for managing ERP standardization and acquisition integration across 16 autonomous business units, and what it actually takes to position IT as a strategic partner in a decentralized global organization. Download, Listen, and Subscribe Apple | Spotify | YouTube Or search “Manufacturing the Future” wherever you listen to podcasts!

    Daniel Topp on why ERP projects fail at training, not technology

  5. Apr 16

    JetStor’s Jim Gallagher on Why 'Good Enough' Infrastructure Costs More Than You Think

    "Every company is becoming both a data company and a bank. If you're not doing this stuff and not keeping an eye on it, other people are."  A lasting warning from Jim Gallagher, CEO at JetStor, who argues that although manufacturers are generating more data than ever, most haven't built the infrastructure to actually use it. The common mistake isn't a lack of storage; it's treating storage as a flat, one-size-fits-all decision rather than a tiered architecture matched to how data gets used. Without that foundation, companies can't run real-time analytics, can't prepare for AI workloads, and are quietly accumulating technical debt that compounds over time. Jetstor is a US-based enterprise storage company with more than 30 years in the business. The company designs and manufactures scalable storage systems built for demanding workloads, including virtualization, high-performance computing, media production, and data-intensive manufacturing environments.  In This Episode:  Jim walks through how manufacturers should be structuring their data strategy, starting with a three-tier classification framework: tier 1: for real-time, latency-sensitive workloads; tier 2: active archive for data that still needs to be accessible; and tier 3: deep archive for long-term retention. He explains why staying with legacy infrastructure isn't actually "free.” Jim closes with a concrete challenge for manufacturing leaders: when was the last time your team actually tested your backups?  Topics Why storage is not a flat ecosystem, and the performance-cost trade-offs that actually matter Three-tier data classification: real-time, active archive, and deep archive The "data lake" trap: why unstructured data hoarding happens and what it actually costs Why training workloads and inference workloads need entirely different architectures The 1-2% annual hardware failure rate and what that means for legacy infrastructure planning How the DevOps movement in IT foreshadows the IT/OT convergence coming to manufacturing Why "when did you last test your backups" is the question manufacturing leaders should be asking right now Ransomware as a business risk, data insurance products, and what underwriting requirements actually look like Why manufacturers that have been gathering data for decades may be sitting on unexpected revenue streams  Apple | Spotify | YouTube

    JetStor’s Jim Gallagher on Why 'Good Enough' Infrastructure Costs More Than You Think

  6. 12/11/2025

    Eaton's Cameron Peahl on Building Additive Strategies That Work

    Meet Cameron Peahl, Global Additive Manufacturing Strategy Manager for Industry 4.0 & Program Manager for I4.0 Digital Factories at Eaton Cameron Peahl, Global Additive Manufacturing Strategy Manager for Industry 4.0 & Program Manager for I4.0 Digital Factories at Eaton, brings over 12 years of hands-on experience transforming how one of the world's largest power management companies approaches additive manufacturing. "It's a cultural journey through Industry 4.0. It's not a technology journey," Cameron emphasize, highlighting a fundamental truth many organizations overlook. Manufacturing leaders face a critical challenge: how to adopt emerging technologies like additive manufacturing without falling into expensive pitfalls or creating unused "paperweights" collecting dust in factory corners. The misconception that 3D printing can simply replace traditional manufacturing processes has led countless organizations to failed investments and disillusionment. Meanwhile, those who dismiss additive entirely miss transformative opportunities for operations support, rapid prototyping, and product innovation. Cameron's path at Eaton began as a manufacturing engineer on the factory floor in Rhode Island, progressing through quality roles before leading the company's Additive Manufacturing Center of Excellence. His team achieved an industry first: putting a 3D printed part in a commercial aircraft fuel system. This journey taught him that successful additive implementation requires understanding where the technology genuinely adds value versus where conventional manufacturing remains superior. In This Episode This episode explores Eaton's four-pillar strategy covering prototyping, operations support, supply chain resiliency, and superior production. Cameron shares why operations support has delivered unexpected massive returns, how to select reliable technology that teams will actually adopt, and why investing in organizational culture trumps technology purchases. His practical advice helps manufacturers avoid common mistakes while building innovation engines that transform workplace engagement and deliver measurable ROI. TopicsUnderstanding Eaton's four-pillar additive manufacturing strategy covering prototyping, tooling, operations support, supply chain resiliency, and superior production at scale.Why supply chain resiliency through direct part replacement is the most challenging pillar and often leads to failed implementations.How operations support with 3D printing has delivered massive unexpected value and transformed factory culture.The importance of selecting reliable, easy-to-use additive systems that don't become barriers to adoption across diverse global factories.Balancing investments between additive and traditional manufacturing methods by understanding where each provides genuine value.Key roles and mindsets needed when moving from prototyping to production, including systems-level thinking and design.Lessons from aerospace component development on why part consolidation and performance improvements create better business cases than cost reduction.Current materials innovations improving layer adhesion and Z-strength that unlock new opportunities for additive manufacturing applications.How AI enables real-time factory insights, closed-loop process control, and autonomous manufacturing operations for additive and beyond.Building innovation-driven organizational cultures that embrace technology adoption, accept calculated failures, and pull for digital transformation initiatives.Resources60 Minutes segment on 3D-printed housesGet in touch with your host, Kerrie Jordan:  LinkedIn  Twitter  Download, Listen, and SubscribeApple | Spotify | YouTube

    Eaton's Cameron Peahl on Building Additive Strategies That Work

  7. 11/27/2025

    Tulip's Natan Linder on Why AI Is Everywhere and Nowhere

    Meet Natan Linder, Co-founder & CEO of Tulip Natan Linder, Co-founder & CEO of Tulip, brings a unique perspective to manufacturing technology, shaped by years spent working directly in production environments. As he explains, the genesis of Tulip came from observing a fundamental gap: "There's a missing piece of software platform in the stack that is designed for the people who actually do the work in operations." His career working on collaborative robotics, 3D printing, and embedded systems consistently brought him face-to-face with frontline workers who lacked the digital tools that office workers take for granted. Manufacturing organizations struggle with rigid systems that cannot adapt quickly enough to changing business needs. Traditional enterprise software requires lengthy implementation cycles, detailed specifications, and often delivers solutions that are outdated by the time they go live. This inflexibility prevents manufacturers from achieving the continuous improvement and agility necessary to remain competitive in today's rapidly evolving markets. The lack of accessible tools for industrial engineers, quality experts, and process specialists means valuable domain expertise remains locked in spreadsheets and tribal knowledge rather than being captured in scalable digital workflows. Tulip was founded in 2014 by engineers from MIT Media Lab, including Natan and his co-founder Roni Kubot. The company emerged from a simple but powerful insight: manufacturing needed a no-code, cloud-based platform that would allow frontline operations experts to create custom applications without requiring traditional software development. By giving industrial process engineers, quality teams, and operations managers the ability to digitize their workflows and capture data on their own terms, Tulip enables what Natan calls composable operations, where production systems can be built bottom-up by the people who understand the work best. In This EpisodeNatan Linder discusses why he believes digital transformation is a meaningless term that should be replaced with continuous transformation. He explains how AI is finally becoming useful in operational environments when properly governed and integrated into platforms that understand manufacturing context. The conversation covers composability versus modularity, the importance of empowering frontline workers with first-class technology tools, and why manufacturing competitiveness depends on giving organizations the ability to iterate and improve rapidly rather than waiting months for new software features.  TopicsHow spending years in production environments led to identifying the missing software layer designed specifically for frontline operations.Modular vs. composable systems and why composable operations enable organizations to adapt and evolve production systems.Why digital transformation is a meaningless buzzword and should be replaced with continuous transformation as an ongoing practice and mindset.How AI has been used in manufacturing for decades but generative AI requires proper governance and context to be useful.The critical importance of empowering frontline workers with the same quality of technology tools that knowledge workers have enjoyed.Focusing on solution-first thinking aligned with business goals rather than adopting technology just because others are doing it.How global supply chain reconfiguration is driven by geopolitical factors, customer proximity needs, and the desire for reduced dependencies on single sources.The role of no-code platforms in enabling industrial engineers and process experts to capture domain knowledge and create digital workflows independently.ResourcesAugmented Ops, Natan’s podcastGet in touch with your host, Kerrie Jordan:  LinkedIn  Twitter  Download, Listen, and SubscribeApple | Spotify | YouTube

    Tulip's Natan Linder on Why AI Is Everywhere and Nowhere

  8. 11/06/2025

    Theresa Caragol & Brenda Nobleza on How Partners Accelerate Digital Transformation

    Meet Theresa Caragol & Brenda Nobleza In a special episode of Manufacturing the Future, Theresa Caragol, Founder & CEO of AchieveUnite, shared a powerful insight about the changing landscape of business relationships: "I do fundamentally believe we are entering the era of partners and the organizations that partner the best will be the most successful long term." Brenda Nobleza, VP of Channel Sales at Epicor, reinforced this vision, explaining that "our manufacturing customers, they're not just looking for software, they're looking for solutions, they're looking for partnership, they're looking for a joint investment in their company and their growth." Together, they unpack what it takes to build channel partnerships that truly drive growth in manufacturing. Manufacturing companies are looking for partners who will align with their strategy and become part of the team taking them to the next level. The old transactional model of channel relationships is giving way to strategic partnerships where vendors, partners, and customers collaborate to solve complex business problems, accelerate digital transformation, and leverage emerging technologies like AI. AchieveUnite emerged from Theresa's desire to balance global business leadership with family life, evolving from consulting work into a company that now employs a team of experts focused on partner performance and channel consulting. Meanwhile, Epicor is undergoing its own transformation, embracing partners more than ever and creating a culture of team selling across the organization. In This Episode Throughout the episode, both leaders emphasize that successful partnerships require cultural alignment, transparency, and mutual investment. They discussed the importance of focusing on business outcomes rather than transactions, the role of AI in partner enablement, and why trust has become an essential currency in modern business. For manufacturing leaders, the message is clear: the ecosystem you build through partnerships can become as strategic an asset as your products themselves.  TopicsUnderstanding why investing in long-term partnerships achieves higher revenues and profitability than focusing on transactions.The Partnership Intelligence framework and how identifying trust-building styles accelerates and partner success.Why cultural alignment is the number one criterion when selecting new channel partners for manufacturing technology companies.How transparent communication and mutual goal-setting create the foundation for trusted relationships between vendors and partners.The evolution from direct vs indirect sales models to collaborative ecosystems where multiple partners co-create customer solutions.Why manufacturers benefit when vendors have strong partner networks that deliver faster, more agile, and flexible solutions.How AI is transforming partner enablement through personalized content delivery, training certifications, and improved processes.The importance of mentoring emerging talent and creating career paths that develop future leaders in manufacturing technology.Shifting organizational culture from product-focused to partnership-focused mentality through top-down leadership.Why business outcomes rather than technology features should drive partnerships between vendors, partners, and customers.ResourcesPartnering Success: The Force Multiplier to Achieve Exponential Growth by Theresa CaragolGood to Great by Jim CollinsCrossing the Chasm by Geoffrey MooreMindshift by Barbara OakleyNational Association of Corporate Directors (NACD

    Theresa Caragol & Brenda Nobleza on How Partners Accelerate Digital Transformation
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5
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Manufacturing the Future is dedicated to helping manufacturing leaders future-proof their operations. Each episode features interviews with innovative manufacturing executives, subject matter experts, and thought leaders who share actionable insights, tips, and best practices to embrace technology so they can streamline operations, prepare for what lies ahead, and continue to keep the world turning.

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