Future of Data

We live in a data-intensive age, thanks in particular to artificial intelligence and machine learning. While the amount of data grows, the European manufacturing system is using, sharing and collaborating on data across geographical boundaries, sectors, and value chains.

With the volumes of data generated in all sectors of the economy exponentially increasing, it will be more important than ever to ensure data sovereignty and safeguard ethics and the quality of data throughout manufacturing processes. This results in a growing need of the future workforce to know how to handle the data with an increasing emphasis on cybersecurity.

Over the years, the manufacturing sector has increasingly started to collaborate across hyperconnected value networks to increase competitiveness and productivity, and to develop new products and processes that have a positive impact on society and the environment. Manufacturers of the future will not only need to understand and know their data, but should also be able to share it safely and securely beyond the walls of their factories. In an era where data collaboration between businesses will increase, trust is essential. Non-competing data spaces can offer this trusted exchange ecosystem where manufacturers can manage their data assets in a sovereign fashion, based on mutually agreed rules.

Resilient Data Spaces

Sharing data is not a new thing, but the requirements of collaborating in data spaces go beyond the bare exchange of data

Data spaces are part of the European manufacturing future, as they offer an innovative and powerful way to accelerate data sharing. However, it seems that a lot of the manufacturers, especially SMEs, are not jumping on the data space opportunity, as they mention ‘the lack of data-skilled workers in the company’ or ‘privacy concerns’ as the biggest blockers for data collaboration. While the potential is endless, use cases are needed to show the business opportunity of data spaces and to develop relevant services. With data sharing and collaboration becoming the norm, the question remains how European manufacturers can shift from being monopolies of knowledge to a safe and open, collaborative and sustainable network of data.

“Data sharing, data spaces, is our future for the products or services that we want to have. We know that we want to have autonomous cars, but you need to share the data. We couldn’t make autonomous cars without sharing the data. So, this is a need already.”

– Martina Le Gall Malakova, Oecd

Data Quality & Ethics

Manufacturers need to learn to use data while respecting current and future ethical standards.

Future organisations will require new skill sets to ensure they are able to talk and walk data ethics. Being able to create personalised products, services and experiences, while at the same time respecting users’ need for privacy. Transparency and responsible data handling will become a crucial differentiator for manufacturers in the future. With more data being needed and used within manufacturing, it will be increasingly important to ensure data sovereignty, and to be aware of ethics and the quality of data throughout the manufacturing process. Furthermore, we see an interesting concept of data dignity emerging, proposed by Jaron Lanier and Glen Weyl, based on the premise that the user must be paid for using their data. It turns the data into a property that is owned by the user and is compensated by the company for monetising their property.

“If you want to be better in sustainability, you have to use what you have. And we have data. So, what we have to do now is really to start implementing and helping our companies in Europe to do it. And this data must be secure, but it should also be used with ethical values, for example, the democratic values we want to live by in Europe. So the impact is not only technical and technological, using data to have sustainability in manufacturing also has an ethical impact on our society.”

– Martina Le Gall Malakova, OECD

Sustainable Data

An increasingly data-driven future for manufacturing should go hand in hand with environmental impact.

On one hand, data sharing will enable manufacturers to decrease their carbon footprint, using lifecycle data collection and analysis to improve sustainability. But on the other hand, an increasingly data-driven future for manufacturing is not necessarily a very sustainable one. Training AI and its large machine learning models requires a lot of power. In fact, according to a paper of researchers at the University of Massachusetts, Amherst, the use of AI technology across all sectors produces carbon dioxide emissions at a level comparable to the aviation industry.

Being aware of this environmental impact is crucial, as data processing and AI is increasing and heading in the direction of ever-more complex models and wider adoption across industries. These developments should be considered when working towards environmentally responsible manufacturing as it poses disruptive potential for the future of data-enabled manufacturing

“We have a huge amount of data. But, if each company wanted to store and work with their data alone, I think the environmental impact of that of their data centre will not be very green. That’s the reason why data has to help us to decrease energy consumption, not to increase it. So we have to know which kind of data we want, which kind of data that we could share will help me or will also help the value chain. This is the reason why the data space, data sharing and interoperability is very important, now and for the future.”

Martina Le Gall Malakova, OECD