Food manufacturing operations are filled with systems intended to create visibility. MES platforms, ERP systems, quality tools, smart scales, sensors, vision systems, spreadsheets, and production reports all play a role in helping teams understand what is happening across the plant. Yet many processors still find themselves exporting numbers, stitching files together, and chasing answers after a shift has already gone off plan.
More technology was supposed to support faster, clearer decisions. Instead, many processors are managing an operation where each system holds one part of the story, while people are left trying to connect the details under production pressure. Operational complexity grows quickly when the information needed to make a decision is spread across equipment, software platforms, departments, and manual reports.
That challenge is the focus of Episode II of the POPCORN Innovation Podcast, featuring Vernon Smith, CEO and Co-Founder of CAT Squared in conversation with Meaghan Ziemba of Mavens of Manufacturing. During this episode, Vernon drew from three decades of experience in meat, poultry, and food manufacturing to discuss the pressure points facing processors today, including labor, margins, automation, disconnected systems, traceability, artificial intelligence, and the gap between having data and having clarity.
The episode also previews the conversation taking shape at POPCORN: The Innovation Summit, powered by CAT Squared. Food manufacturers need more than broad technology promises. They need practical conversations about what connected food manufacturing actually requires under real plant-floor conditions.
CAT Squared is bringing customers, partners, and industry leaders together in Hot Springs, Arkansas, from August 10 to 13 to explore how processors can move from operational complexity toward information they can understand, trust, and act on.
In the recap below, Meaghan shares key takeaways from her conversation with Vernon and what the discussion reveals about the future of connected food manufacturing.
Vernon started CAT Squared with two other founders more than thirty years ago in South Africa. The company began as a general manufacturing automation business before opportunities in meat and poultry pulled the team deeper into food production. One project led to another, the U.S. market opened up, and CAT Squared eventually built its identity around the operational complexity of protein processing.
Experience matters in food manufacturing because production conditions can change quickly. Products vary, yields shift, labor changes, and equipment behaves differently from one line to the next. Even a well-developed process plan can run into conditions that were difficult to predict before the work reached the plant floor.
During the podcast, Vernon pointed to several pressures processors are facing right now, especially labor and margin pressures. Finding and keeping skilled people on the plant floor keeps getting harder, while costs tied to labor, energy, inputs, and compliance keep climbing. Automation has become part of the response, but automation without connected information adds another layer of complexity to the operation.
A modern food plant can be packed with intelligent equipment and still struggle to make better decisions. Vernon described plants with MES systems that do not communicate with ERP systems; quality platforms that do not communicate with production systems; and machines that collect data but do not connect to the rest of the operation. Plenty of processors have invested heavily in technology, yet the information remains divided across systems and departments.
Vernon summed up the problem perfectly when he explained that many companies are “drowning in data, but starving for insight.” More numbers do not automatically create better decisions. A processor can have every metric imaginable and still miss the moment when a yield issue, quality deviation, planning gap, or traceability problem starts costing real money.
Operational clarity starts when the right information reaches the right person at the right moment. Vernon described the difference between reporting what happened yesterday and giving an operator information they can act on right now. A plant running on yesterday’s answers will always be a step behind, and the rearview mirror is a lousy place to manage live production because processors need visibility into issues that can still be corrected.
One of my favorite quotes from Vernon’s interview focused on fragmented systems and the people caught between them. “People become the integration layer,” he explained. Anyone who has worked around disconnected manufacturing systems knows exactly what that means because the workaround usually lands on the people already trying to keep production, quality, planning, and reporting from falling apart.
Someone pulls data from one system, exports information from another, drops it into Excel, cleans up whatever broke during the transfer, and sends the spreadsheet around after the damage has already happened. Meanwhile, yield losses are already baked into the shift, planning is already behind, and the team is trying to determine what happened. All of that manual effort takes people away from the work that actually needs their judgment, experience, and attention.
Traceability makes the issue even more serious. According to Vernon, assembling trace and recall information can become a frantic, manual scramble instead of something fast and reliable. Food manufacturing does not have the luxury of vague answers when customers, regulators, safety, and reputation are involved, and a disconnected data trail can run one problem into an operational fire drill.
AI came up in our conversation for good reason. It is becoming part of nearly every technology conversation, but Vernon’s answer stayed grounded in the reality of food manufacturing. AI is only useful when the data behind it is connected, accurate, and tied to the decisions people actually need to make.
“AI becomes incredibly powerful, but only on top of connected data,” he said. A plant running a disconnected system, manual spreadsheets, inconsistent reporting, and unclear ownership is not ready for AI just because someone approved the investment. Bad data does not become more useful because a new technology is layered on top of it.
Vernon sees AI playing a near-term role as augmentation, not replacement. He talked about AI helping operators see productivity losses, quality drift, root causes of downtime, and deviations before they become bigger problems. Strong use cases help good people move faster, but the human remains part of the decision, especially in food manufacturing, where safety, quality, traceability, and compliance are always at the table.
A controlled demonstration can make nearly any platform look like the right answer. The workflow is clearly defined, the system behaves as expected, and nobody is dealing with a quality hold, an unexpected staffing shortage, or a production schedule that changed an hour ago. Problems begin when the solution receives more attention than the operational issue it is supposed to address.
Leadership or IT may select a platform before the people closest to the work have clearly defined what needs to change. A tool can perform well during a demonstration and still fail to match how the plant functions under normal production pressure. Operators may not argue during the buying process, but they will quietly work around a system that makes their jobs harder.
“The technology isn’t the point. The problem is the point,” Vernon emphasized. Food processors need partners who are willing to walk the floor, understand the process, talk to the people doing the work, and define the requirements before discussing features.
Plant-floor adoption does not happen because a vendor promises that a platform is easy to use. Adoption grows when people recognize their operational reality inside the solution. Better technology should reduce friction, improve decision-making, and help teams respond with greater confidence instead of adding another screen that requires attention while production continues.
Moving from complexity to clarity requires processors to see more than isolated pieces of operation. CYNERGY sits at the center of CAT Squared’s larger vision for connected food manufacturing. Vernon described a direction in which processors can see the entire process in one place, with insight at every step, rather than scattered fragments of information across multiple systems. Visibility becomes the starting point, and predictive enterprise intelligence becomes the bigger ambition. “You can’t really have enterprise intelligence on top of disconnected systems,” Vernon explained. “The integration has to come first.”
For processors, the value comes from connecting plant-floor execution to the rest of the business. Raw material supply, production activity, inventory, quality, traceability, demand, fulfillment, and enterprise planning all need better alignment if companies want faster decisions and stronger performance. Disconnected systems slow people down, even when everyone involved is working hard.
On Tuesday, August 11th, at the Summit, Vernon will present “Future Vision: From Plant-Floor Visibility to Enterprise Intelligence,” which explores how CYNERGY can evolve from visibility to forecasting, automated decision support, cross-site benchmarking, and broader enterprise intelligence. Food manufacturers dealing with fragmented systems and manual handoffs will get a clearer view of what connected information could mean for their own operations.
Technology cannot create operational clarity on its own. Operations, quality, IT, supply chain, and executive leadership often view the same problem from different positions. Each group has separate responsibilities, pressures, and expectations for what the system needs to accomplish.
Vernon described real alignment as everyone beginning with “the same problem definition.” Operations needs to explain how the work actually happens. Quality needs visibility into the information required for safety, compliance, and product decisions, while IT needs to understand how the technology will fit into and be protected within the existing environment.
Shared problem definition changes how technology is selected and implemented. People are more likely to use a system when they help define the problem it was designed to solve. Alignment also makes it easier to determine whether an investment reduces complexity or simply moves the same problems to a different platform.
Data ownership belongs in the conversation as well. Vernon talked about the importance of customers owning their data and having the choice in how they use it and which systems they connect to it. An open ecosystem gives processors greater freedom to choose the technology and equipment that best fit their operations without being constrained by a closed environment.
One of the strongest parts of the POPCORN Summit structure is the decision to close with a listening session. Rather than ending the event with a final presentation, CAT Squared is creating space for customers to share what they need, where pressure is building, and where the platform should go next.
Vernon made it clear that CAT Squared’s best ideas come from customers. He also acknowledged how easy it can be for a software company to fall in love with its own roadmap and gradually move away from what customers actually need. Product development remains relevant when the people closest to the problem play a meaningful role in shaping the direction.
Processors attending the “Shaping What’s Next” session should come prepared to talk about their real problems. Integration challenges, reporting gaps, traceability concerns, process issues, and areas where current systems make work harder all belong in the conversation. Technology providers cannot solve the right problems without an honest understanding of the operational pressures customers face.
The main takeaway from my conversation with Vernon was that food manufacturing does not need more disconnected technology conversations. Better performance starts when companies connect systems, people, data, and decisions in ways that reflect how the work actually happens. Another platform will not create clarity if the problem remains poorly defined and the information stays divided across the operation.
POPCORN: The Innovation Summit gives processors a chance to step into that conversation with CAT Squared, customers, partners, and industry leaders who are looking at the entire food value chain. Sessions will cover live production, predictive intelligence, operational intelligence, plant-floor data, ERP integration, traceability, AI, interoperability, and the customer priorities shaping what comes next. Each conversation builds toward a broader understanding of how connected information can support better operational decisions.
Food manufacturers already have enough complexity to manage. The next move is creating greater clarity around what is happening, why it is happening, and who needs the information to respond. Connected systems cannot remove every production challenge, but they can give experienced people a better chance to act before wasted time, lost margin, or preventable disruption becomes part of the final report.
Want the full conversation? Watch Episode II of POPCORN: The Innovation Podcast featuring Vernon Smith and Meaghan Ziemba here: https://www.youtube.com/live/8ZT3clc6P_8?si=LlcCKIZtuSyGFsvS
POPCORN: The Innovation Summit powered by CAT Squared takes place August 10–13, 2026, in Hot Springs, Arkansas.