Since the dawn of the fourth industrial revolution, manufacturers have been racing to digitize their operations, chasing the promise of unprecedented efficiency and agility. But according to Johannes Furman, Head of Strategic Business Development at Arvato Systems, that promised productivity boom has yet to materialize.
“Since the advent of Industry 4.0, whatever people understand from this, right — it’s different definitions — but let’s say the digital transformation of the manufacturing industry, since the advent of this, there hasn’t been a proper rise in productivity as we expected,” Furman explained on a recent episode of the Advanced Manufacturing Now podcast.
The reason, he argues, is that many digital transformation efforts have been siloed, confined to individual departments or use cases. The result is a patchwork of systems and data models that struggle to interoperate and unlock the full potential of Industry 4.0.
Enter data spaces: a new paradigm for secure, decentralized data sharing that allows companies to exchange information with partners and suppliers without giving up control or sovereignty over their data.
The idea of data spaces, though, is not to create a central platform where everyone puts their data, and then they can retrieve whatever they want. But it is a rule set of policies, its digital identities, and it is a way to identify the data that’s available, but you access this data on the systems of your client, customer, or whatever. So there is no data storage in a data space.
By standardizing data and making it interchangeable across company boundaries, Furman believes data spaces can finally deliver the efficiency gains that have thus far eluded many manufacturers. He points to examples like accessing logistics data from suppliers to optimize internal processes, or sharing machine data to enable predictive maintenance across the value chain.
But data spaces are just one piece of the puzzle. The other key concept Furman sees transforming manufacturing is the digital twin: a virtual representation of a product’s entire lifecycle, from creation to disposal.
My definition is not the full definition, but how I would define a digital twin is like a digital CV of my product. It shows me where it has been born, where it was manufactured, who bought it, how it was used, and how it will be recycled. Like from birth to death, it shows me the life cycle of my product.
By shifting from managing product categories to tracking individual SKUs, digital twins enable a host of new use cases, from targeted recalls to circular economy applications. Furman cites the example of an automaker that could pinpoint specific cars affected by a faulty airbag, rather than issuing a blanket recall of an entire model line.
Implementing data spaces and digital twins is no small feat, of course. It requires a significant paradigm shift, from unique product identifiers to new data models and API architectures. But Furman stresses that it’s not a journey manufacturers have to undertake alone.
“This is not a lone wolf thing. This is teamwork,” he emphasized. “There are a lot of experts, there are a lot of people who are new to this. And the most important thing is to network, get into touch with people who work with this, and first of all, get an idea of what this can bring to my business.”
Government-funded projects are already driving adoption in Europe, Furman notes, but the real test will come as that funding winds down. To sustain momentum, the industry will need to demonstrate clear use cases that deliver measurable revenue and efficiency gains.
Looking ahead, Furman sees data spaces expanding beyond manufacturing into sectors like healthcare, chemicals, and life sciences. As these industries begin to interlink their data ecosystems, he believes the impact could be truly transformative — not just for individual companies, but for the global economy as a whole.
“As with all trends, it won’t happen in the next one or two years. It’s not like the big rocket science that will change the world,” Furman reflected. “But it will come slowly and steadily, and will change quite a lot also in terms of AI.”
For manufacturers on the cusp of this new frontier, Furman’s advice is simple: start the conversation. Engage with experts, learn from peers, and most importantly, don’t try to go it alone. The future of manufacturing is collaborative — and it’s just around the corner.
To learn more about Arvato Systems’ offerings for manufacturers, visit arvato-systems.com/industry/industry-mit-caps.
