Frederik Becker, Chief Growth Officer, InnoVites
For more than a decade, Industry 4.0 has described a vision of connected manufacturing. Machines, people and business systems share information, allowing production to respond more intelligently. A machine stoppage can inform the production schedule. Quality results can help explain a process problem. Sales can offer delivery dates based on what the factory can actually produce.
There is evidence that this works. Respondents in Deloitte’s 2025 survey of 600 executives at large manufacturers with US headquarters or operations reported average production output improvements of 10–20% following smart manufacturing initiatives.[1] Connected manufacturing has practical value.
As a description of what a business should invest in, however, “Industry 4.0” tells us surprisingly little. ETH Zurich’s Torbjørn Netland describes how the label covers a wide range of technologies, from automating tasks to helping people perform them better.[2] Two factories can pursue entirely different investments under the same heading.
I encounter this ambiguity in conversations with wire and cable manufacturers. “We want a smart factory” or “we want artificial intelligence” expresses an understandable ambition. Sometimes, though, there is little agreement about which business problem the investment should solve, or what success would look like. The technology demonstration can then become more influential than the factory’s actual needs.
The digital twin illustrates the difficulty. A digital twin is a digital representation of a physical machine, process or system, kept up to date with information from its real-world counterpart. Depending on its purpose, it can help people understand current conditions or explore how production might behave under different circumstances.
The term can conjure up a photorealistic factory that someone explores in virtual reality. Such a model may be useful for planning a layout or training operators. But NIST’s analysis of the ISO 23247 manufacturing framework emphasises that a twin’s representation should suit its intended purpose. A lifelike 3D model is not a universal requirement.[3]
For a production manager trying to understand recurring stoppages, the useful picture might be much simpler: which order was running, which material was being processed, and what happened immediately before the line stopped.
A manufacturing execution system, software that coordinates and records production, may already provide that information when connected to reliable equipment and business data. It is not automatically a digital twin, but it can provide valuable operational visibility. More elaborate modelling becomes interesting when testing alternatives or predicting behaviour would improve an important decision.
This brings the discussion back to familiar business questions. A cable manufacturer hoping to win more specialised orders may benefit most from a faster connection between design, costing and production planning. Another may have plenty of demand but struggle to use its existing capacity. Their opportunities for digital investment will differ, even if both describe their ambition as a smart factory.
Understanding technology remains essential. New capabilities can reveal opportunities that were previously unrealistic. Equally, reliable data and integration may support several improvements over time, making their value larger than the payback from one initial project. A business-led approach leaves room for discovery and growth.
What changes is the quality of the conversation. A supplier can demonstrate how information would support a particular decision. The manufacturer can consider the likely benefit alongside the cost and organisational effort. People responsible for production can judge whether the proposed change would help them in practice.
Industry 4.0 is dead as a substitute for that conversation. The question worth keeping is what a better-connected business could do that it cannot do today.
Sources
- Deloitte, 2025 Smart Manufacturing and Operations Survey (2025; fieldwork conducted in 2024).
- Netland, T., Demystifying Industry 4.0: Navigating Automation and Augmentation, IEEE Engineering Management Review (2025).
- Shao, G., Frechette, S. and Srinivasan, V., An Analysis of the New ISO 23247 Series of Standards on Digital Twin Framework for Manufacturing (NIST, 2023).
