We have all heard that Industry 4.0 is highly disruptive, that it will change the way we do business and so on. But if we look beyond the breathless enthusiasm to what is actually happening, it is a bit like crashing down to earth. The vast majority of Europe’s companies are still a long way off this new tech era.

So why is that? Because people haven’t realised that this is important? Hardly – with the constant media onslaught it is hard to ignore. The more mundane (and honest) reason is that while writing (or reading) clever articles on this topic is easy, imaking the actual transition is far more difficult.


The trickiest part is to get one’s head around this amorphous topic. Breaking it down into more manageable bits might help us to get a better grasp on it by making it more tangible.

Seamlessly integrated processes and self-learning feedback loops are tricky if the reality looks more like an IT system that consists of a motley collection of enterprise resource planning (ERP) systems, more or less expertly tagged on logistics-, warehousing- and customs-handling systems, computer aided design and other technical software as well as customer relationship management (not to mention most data manipulation still takes place in Excel sheets). Let’s be honest, in the vast majority of cases seamless integration is nothing more than a dream.

And how can it not be the case? Enterprise-wide, all-encompassing solutions that integrate the entire pantheon of data within the company (sensor & RFID data, knowledge management data or order-processing data) still need to emerge. Before we entertain lofty dreams of the digital factory, we first need to rebuild the basic information infrastructure on which we are working.

In data it is probably even worse. I am not even talking about in-line-sensor-data to guide predictive maintenance or hordes of self-learning AI-based robots. Right now, we don’t even get the ‘basic data’ right. Keeping base data clean is a dull and boring job usually handed to some intern, but shouldn’t it be a key task? If the DNA of the company isn’t accurate, how can we expect meaningful results at the end?

Plus, we aren’t really collecting all that much useful stuff. True, we collect order-processing data simply because we have to by law, and because we need this information to run the order processes. But even only a complete product history or consistent product overviews – with all F&E data, specification changes and different product versions is pretty rare out there. For this, you need a PLM/PDM system, which to implement is about as much fun as migrating to a new ERP system.

Fun or not, if we don’t have a clean, consistent body of data, how can we expect Industry 4.0 to take off? As long as we fail to grasp Clive Humbly’s dictum “data is the new oil”, our problems will persist. And he was right with another thing: “It’s valuable, but if unrefined it cannot really be used.” Do we have data analytical skills in our companies (or do we know where we can find such services?).

So what are we to make of all of this? If you are feeling overwhelmed by the topic, you are in good company, as so is everyone else. If you are planning your march into the fourth era of the industrial age, you will have to get your basics right. Sit down and start working. This might not be quite as glamorous as the 4.0 articles, but you’ll never arrive without it. 

And finally, FDI for once isn’t the answer. This one you’ll need to build from the ground up.

Martin G Kaspar is head of business development at a German mittelstand company within the automotive industry and a PhD candidate at Durham University. E-mail: martin.georg.kaspar@gmail.com