Business challenges

Data are increasingly being used to realize innovative business models (such as Airbnb, Uber, and others). More and more, these new business models are developing through a cross-domain exchange of data (data sharing) between different players. Trading and exchanging data optimizes processes and conserves resources. Notwithstanding this knowledge, many companies still shy away from sharing and making their data usable by others. This is illustrated by a study about International Data Spaces conducted by PwC. Yet the IDS architecture addresses various challenges, the most important of which is data sovereignty.

Data security and compliance constitute major challenges for companies in the data economy. Only when all players in an ecosystem can be certain that their data are protected, and will not fall into the wrong hands, they are prepared to share their data within that ecosystem. A representative survey of companies by the German Economic Institute and IW Consult confirms this observation with the result that more than 50 percent of the surveyed companies feel uncertain regarding the issue of data security. The study also found that data protection requirements, such as the General Data Protection Regulation (GDPR), currently represent an obstacle to the exchange of data between companies for 45.8 percent of the respondents.

To address this, the International Data Spaces offer uniform rules for data handling and for controlling access to the IDS ecosystem with the help of various connectors. The Trusted Connector for example implies control over the flow of information, thereby providing companies with a basis for complying with the GDPR. As another example, the OPC UA factory connector permits data usage control so the data provider is assured that their data reach only the desired stakeholders or persons.

The International Data Spaces thereby guarantee data security and data protection for all participants, establishes mutual trust between them, ensures equal competitive conditions with a jointly developed and generally accepted design and enforces data sovereignty for all data owners. It enables the exchange of data based on ethical principles and shared European values.

Learn here how to prepare your own IDS use case and what technical requirements you should meet.

A study conducted by the World Economic Forum and Boston Consulting Group showed that 72% of about 1000 surveyed managers are considering data sharing to improve operating procedures. The following cases provide examples where the exchange of data between companies would be sensible to make operating processes more efficient.

Improving plant utilization: By combining data from multiple users of the same machine type, manufacturers can improve algorithms, for example to enable predictive maintenance. Therefore, the shared use of data can optimize plant performance by increasing machine uptime and improving product quality, resulting in a win-win situation for all participants. This is particularly important for manufacturers that lack the data volume required for robust analysis algorithms.

Tracking products along the value chain: End-to-end transparency of their value chains allows manufacturers to proactively minimize risks, respond to unexpected events quickly and reduce their inventories. Although manufacturers already track products along the supply chain, they need to work together, use data jointly and deploy shared systems in order to establish true end-to-end transparency and mutually beneficial cooperation.

Decentralized real-time control through the analysis of operating data on digital platforms: The exchange of data between companies along their value chain makes it possible to establish shared digital ecosystems which enable efficient and demand-driven control of value creation.

Even though the added value of these application scenarios is generally known, the exchange of data between companies frequently does not take place. The International Data Spaces architecture can enable the realization of these scenarios because it is based on generally accepted data governance models and thereby facilitates the secure exchange and straightforward linking of data within business ecosystems.

According to forecasts, the estimated value of the data economy in Europe will be 680 billion euros in 2025. In order to be part of this development and realize its potential, companies must be willing and able to share their data in ecosystems. Currently however, companies are often not yet able to share their data even if they are willing. In a representative survey, nearly 44 percent of the participating companies stated that they lack access to the right data. 45 percent of the surveyed companies criticized the quality of the data available in their company. These components however are crucial for participating in the data economy and for implementing data-driven business models. The importance of good data quality in particular is still underestimated by many companies.

One of the main aspects of data readiness is that companies need to get actively involved in ecosystems and become aware of their respective role in order to utilize the potential of the data economy. Internal measures need to be implemented and data has to be viewed as a valuable asset in order for cooperation between companies to lead to the innovative bundling of services. These interactions ultimately lead to shared value creation that profits all players in the data ecosystem.

The International Data Spaces establish the rules with its governance architecture, for instance by regulating the visibility of data sources, the data quality and the consideration of data regarding their economic value. Due to the correlation between good data quality and maximizing the value of data as an asset, the International Data Spaces explicitly address the aspect of data readiness. Based on this premise, the International Data Spaces make it possible for its participants to evaluate the quality of data sources based on publicly accessible information and the transparency it provides regarding the offered brokerage functionality. This transparency can force data providers to take data maintenance more seriously, especially in competitive environments. The International Data Spaces lay the foundation for automated data (quality) management by expanding the functionality of the connector with self-implemented data applications.

Data scientists need data of high quality to generate innovations from data. Today the storage of data is mostly distributed in what are known as data silos. However, access to these data is still lacking today. The International Data Spaces enable an independent data space based on European values that permits the exchange of information between companies.

Secure, certified gateways called connectors form the system’s cornerstones in order to accomplish this. Usage policies attached to data sets enforce data sovereignty by defining access rights.

The International Data Spaces represent an important component of future initiatives related to the cloud and data sovereignty, such as GAIA-X, helping to establish a networked data infrastructure. The International Data Spaces currently facilitate the following services:

• Data processing & transformation
• Implementation of data apps
• Delivery of data apps
• Installation & support of data apps
• Clearing & billing
• Usage restrictions & governance