May 16, 2025
Today’s machinery generates a wealth of invaluable information
Over the past decade, the volume of data available throughout every aspect of manufacturing has increased, with modern machinery capable of generating a tremendous amount of information. Much of it can be transformative. “This kind of detailed feedback can give you a deeper understanding of what’s going on and suggest what you might want to do differently in the future,” says SUN Automation Group Vice President of Technology and Business Development Gokul Gopakumar. Valuable information sometimes goes unused simply because boxmakers do not have the time or staff to sift through it all or pinpoint all of the meaningful connections. Yet, today’s information flood can be managed. “It’s up to us as business owners and drivers of technology to find ways to harness that information in a way that is actionable,” Gopakumar says, “using it to improve profits, efficiency, service, and reliability.” A variety of new tools and technologies can help.What Problems? What Tools?
“It is easy to feel overwhelmed by data and not know where to start to get from information to action,” acknowledges David Wiens, founder and CEO of BPS AI Software. He recommends considering the big picture before diving into the data details. “The first step is to make sure you have a team of stakeholders who can review and rank your priorities,” he says. “What problems are you trying to solve? Most people we talk to are all over the place, with one business leader who’s driving something while everybody else has other priorities. You need a unified approach. Then, you can see where you need to go.” Next, Wiens suggests asking, What are the roadblocks to getting where you need to go? What are the tools that can help you? “For every one of those barriers, there’s a tool or a consultant or a custom solution that can help you do it,” he says. Flexibility and focus are essential early on when analyzing data. “It’s not about making sure you look at all the information,” Gopakumar says. “It’s about changing your attitude toward how you approach day-to-day decision-making. Every day, we make decisions based on assumptions and experiential knowledge, often taking it for granted that that is the only way to make that decision.” Expect the data to suggest numerous other options. Then, be flexible when considering the potential applications. Focus will help to fine-tune your approach. “Ask yourself what are the three or four key points of information that you really care about within any given process, the data that can make the most meaningful difference,” Gopakumar adds. “The most successful case studies I’ve seen have all revolved around a very lean focus that takes one or two or three key things to focus on and then takes specific actionable steps to make the most of that information.” If the data presentation itself is impenetrable or difficult to decipher, consider putting it into a more immediately digestible format. “The majority of people I talk to want to visualize their data,” Wiens says, pointing out that graphs and charts often make the most sense. He notes that Microsoft’s Power BI software—as well as other visualization and business intelligence applications—can do that for your data, providing the first layer for understanding. “It’s a complex thing to pull data and build graphs,” Wiens says. “But once you get it done and deliver that to a stakeholder—or up the chain to your boss—it clarifies how each piece of information is inherently connected to another.”Starting Clean
Wiens’ clients are drawn to his company primarily for data-integration solutions, something they don’t have the technical staff to develop themselves. Others come wondering about the potential benefits of integrating artificial intelligence (AI) into their data solutions. In many cases, these companies are putting the cart before the horse. “A lot of companies aren’t ready to move forward with their data when they come to us,” he says. “Maybe, they just don’t have the right data available, or they don’t have clean data, or it isn’t consolidated in one place. So, it’s a mess.” Getting that data to the point at which it is accurate and actionable may require a separate project of its own. Again, a business intelligence suite of programs can help. “Having a single platform that can extract, transform, and load that information into whatever you’re trying to do is one of the most useful things I’ve found,” says Wiens. “There are a lot of business intelligence suites out there. Finding the best fit just depends on your goals, how it can integrate with your core operating systems, employees’ level of technology understanding, and things like that. It is not difficult or costly to get your feet wet and figure out what you need in order to visualize and access your data so you can actually take action on it.”Improved Intelligence
Fortunately, technology, which has created the modern flood of data, has also led to one of the key solutions for actually using it: applications built on AI. Unless a company has unlimited resources and time, it truly is the only viable tool to analyze massive amounts of information, find patterns, and uncover important connections between different departments and functions. Wiens believes AI will only grow in terms of its abilities and its integration with existing systems. Just what that will mean for productivity and other improvements throughout box plants remains to be seen. “AI is evolving at an incredible pace,” he says, “making it difficult to predict exactly where the landscape will be even a few years from now. “In the immediate future, I see multimodal models and chain-of-thought reasoning models driving the next major breakthrough: the rise of agentic AI systems that will fundamentally reshape how businesses interact with technology.” Wiens explains that multimodal models can process and understand text, images, and speech together, making AI far more intuitive and context-aware, while chain-of-thought reasoning allows AI to break down complex tasks into logical steps, leading to more accurate and thoughtful decision-making. An agentic system is a system in which AI actively coordinates multiple functions without human intervention. “Previously, these capabilities required a complex mix of programming and engineering, but modern AI models now have this built in. More importantly, users can see the reasoning process in real time—a major shift from the old ‘black box’ AI model, where the system simply produced an output without transparency. AI can now detect inconsistencies, flag potential errors, and provide recommendations, significantly enhancing human-AI collaboration,” he says. In addition, he sees so-called specialized language models gaining traction. “Instead of relying on a single, massive AI model, we now have orchestrator models—AI systems that decide which specialized model or function to use for a given task,” Wiens says. “These systems can automate entire workflows, seamlessly pulling in the right resources, whether it’s running a complex analysis, retrieving data, or handling customer interactions.” “The real game-changer will be integrating all these AI capabilities into a single, holistic system,” he says. “Businesses will no longer need to manually piece together different AI tools; instead, AI-driven applications will handle tasks automatically. This eliminates complexity and lowers the barrier to AI adoption, allowing companies to scale AI without needing a large technical team.”Data-Driven Benefits
The desired result for all of this data integration and analysis is empowered decision-making, which can produce improved efficiency and productivity, enhanced customer service, scheduling and workflow flexibility, and a company’s overall adaptability. Wiens reports that clients’ data-based decisions have led to actions that do the following:-
- Merge sales, design, and request-for-quote processes to better track trends, visualize key performance indicators, and enhance decision-making.
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- Integrate marketing and delivery data into existing management systems.
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- Digitize production reporting and preventive-maintenance data for improved efficiency and oversight.
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- Integrate production scheduling with shipping and logistics data to create a more cohesive workflow.
