The Human Element in DX: Why Your Factory's Future Depends on It
In an era where many manufacturers pour significant resources into digital transformation with elusive returns, this article cuts through the Industry 4.0 jargon to reveal how companies can achieve tangible ROI. Join Shinichiro (Shin) Nakamura, the President of o2OG, a multinational steel tube engineering and manufacturing group that includes an over-90-year-old Japanese steel tube producer Daiwa Steel Tube Industries (DSTI), and Arjun Chandar, Founder and CEO of IndustrialML, a cutting-edge technology partner of o2OG, as they discuss moving beyond "pilot purgatory" to unlock real value from digitalization, emphasizing integrated data, empowered teams, and measurable outcomes for sustainable growth.
Table of Contents
Real Barrier to Digital Transformation ROI - Usability
Making the OODA-Loop Tangible
Beyond Tech Investment: The Economic Reality of 'How' and 'Will'
Your Practical Roadmap: From Bottlenecks to Actionable Intelligence
Real Barrier to Digital Transformation ROI - Usability
Moderator: Shin, many manufacturers have invested in digital transformation, but there's often a lingering question: 'Are we really future-proof, or just adopting technology?' From your long history in manufacturing, what's the fundamental shift in mindset needed to move beyond just implementing tools to truly building a resilient, adaptable, and future-ready operation?
Shin: To begin, let's address a common misconception about digital transformation roadblocks. It's often not a fear of being replaced by machines that causes resistance. Instead, it's fundamental because the tech isn't intuitive or practical for frontline factory use, and its immediate benefits for their work aren't evident. This lack of clarity on purpose, combined with challenging implementation, directly results in underutilized systems and poor ROI.
Beyond that, Industry 4.0 often focuses solely on machine data, overlooking the crucial human element on the factory floor. If technology doesn't provide easy, two-way information flow with people––especially for smaller companies relying on human hands but lacking human-generated data––you're missing huge opportunities. Optimizing the human-driven part of the operation is vital for the very ROI they seek from digital investments.
Making the OODA-Loop Tangible
Mod.: Could you elaborate on this?
Shin: The real issue, then, is how the necessary workflows, systems, and contents are truly integrated. A new system only moves the needle if it enables faster on-site decision-making and reduces the time to and of action. When frontline teams experience this immediate benefit––a quicker OODA-loop (Observe, Orient, Decide, Act) ––they become engaged.
This directly translates into improved KPIs like yield, uptime, and changeover time, but not necessarily visible from the beginning. Simply installing a system won't improve these metrics; performance only emerges when the system, its contents, and the operational workflows are seamlessly integrated. The key is to foster a tangible sense that the system helps them act faster and more effectively, even before the overall KPIs fully reflect the change.
Beyond Tech Investment: The Economic Reality of 'How' and 'Will'
Mod.: Important point. Despite significant investment, why do companies frequently overlook this crucial aspect? What tangible examples demonstrate this disparity?
Shin: It boils down to the real economic realities concerning human, machine and money. I believe hard-performance hinges on two factors: the "how"––our methods and systems, what we call soft-performance––and the "will"––the human motivation and engagement, what we call heart-performance. There’s a strong correlation there.
The difficulty lies in the fact that those trying to leverage the system––that is, the content (the data, information, and intelligence flowing within it)––often don't fully grasp the intricate workflows. A system-heavy approach without this understanding becomes unusable. Conversely, a workflow-heavy approach without robust system integration becomes overly complex, less effective, and less efficient.
What's truly needed is a combination of impactful and relevant data as content, a simple system, and a simple workflow. Here, Machine Learning, Deep Learning, and GenAI are transformative, creating impactful content by giving profound meaning to raw data in a multimodal way, directly bridging this gap.
Your Practical Roadmap: From Bottlenecks to Actionable Intelligence
Mod.: Arjun, building on Shin’s point, many companies find 'Digital Transformation' often becomes about simply chasing the latest tech. Especially for mid-market manufacturers, how do we help them cut through this noise and, critically, identify their specific core challenges that technology should genuinely address? Leveraging the kind of 'multi-modal content' Shin just mentioned, what's the clear starting point to move beyond mere tech adoption?
Arjun: Shin hit the nail on the head. For mid-market manufacturers, the starting point isn't chasing tech; it's identifying their most critical operational bottlenecks and pain points first. Don't ask, 'What AI should we get?'Ask, 'What's slowing us down or costing us the most right now?'
Then, it's about leveraging technology like o2OG's to create what Shin called 'Action Driven Contents.' This means transforming raw data into contextualized, actionable insights. Crucially, we enable them to view this content through the lens of their workflows. Instead of just numbers, the system provides clear answers that frontline workers can easily understand and act upon.
Systems change workflows. Our approach isn't just about overlaying tech; it's about providing a system that, by its very design, helps redefine and optimize those workflows. This means the necessary data and content also evolve. For instance, our system helps define specific parts of the workflow, making the intangible visible.
While a system provides methods and doesn't always show immediate hard performance results, the goal is that when the purpose and ultimate impact of the system are clear, the OODA-loop becomes faster and shorter. Frontline workers are the ones who truly feel this acceleration, and while it's not always traditionally measured, o2OG's system is designed to make this tangible and measurable under specific conditions.
