Insufficient data sharing –› Data sharing practices and obligations should be developed

Challenge: Insufficient data sharing

• Difficulty in determining the value of data: Data are goods of a very heterogeneous nature. There are different types of data, such as personal data, data from devices and production processes, and data concerning the company’s financial performance. The business value of data is difficult to determine before the data reserve has been incorporated into a specific use case and possibly combined with other data reserves.
• Restrictive cooperation practices: Sufficient standards and established practices have not been developed for data sharing. In the manufacturing industry, contractual practices slow down data sharing. For instance, intellectual property rights clauses between companies restrict data sharing and the sharing of solutions built by using shared data. In addition, the strict and demanding global competition environment does not encourage data sharing with potential competitors. Data is often collected from devices and processes related to the company’s core business. In contract negotiations, companies have the same attitude towards data sharing as towards traditional business, and they are cautious about sharing data with others.
• Incomplete or restrictive legislation: Legislation does not currently allow for safe data sharing, nor does it support the creation of effective practices. In certain cases, legislation or market regulation prevents data sharing. For example, the EU’s General Data Protection Regulation does not allow telecommunication operators to share individual location data, which restricts their use.
• Lack of competence in data-based business: An operating environment in which data reserves from different companies are integrated to develop new business activities and innovations has not yet emerged in the manufacturing industry. The main underlying problem is the lack of competence in the management of processes and capabilities.

Some companies accumulate considerable data reserves. The fact that data is accumulated by a limited number of actors can distort the market, prevent competition and reduce their useful spin-off effects. In particular, this reduces SMEs’ opportunities for innovating and developing new data-based businesses.

Recommendation: Data sharing practices and obligations should be developed

• Data sharing should be made an obligation in exchange for public funding. Public financial aid to businesses should include an obligation to share data. Data sharing should be the default practice when developing legislation and in requirements put in place by the public sector. In the public sector, the principle of data openness should be a core value.
• Assessment tools should be created for determining the value of data. Better models for determining the value of data-based business encourage companies to engage in co-development and extensive investments. Companies should have better financial assessment models to support data sharing. For example, simulation models and artificial intelligence are good tools for examining probable outcomes. Research projects should be launched for determining the value of data and developing the valuation models for data-based businesses.
•  The emergence of data operators should be ensured. Data operators collect data from different organisations, creating marketplaces for the data. They put in place principles for data sharing and develop operating models for sharing data. They help to dismantle obstacles brought about by licensing, ownership, lack of competence, and contractual practices. The pursuit of operation on market terms over the long-term creates incentives for developing private platform-based data operators. The emergence of data operators can be accelerated with public aid or through PPP models.
• Supporting the integration of corporate data reserves and the development of new data-based business models. New data-based business opportunities and innovations can be created by combining multiple corporate data reserves. Collaboration platforms and consortia can develop practical solutions for data sharing. They also produce standards, models and regulation.