In order to better understand the challenges of data sharing, governance and reuse across multi-stakeholder actors in data value chains, the consortium has interviewed 4 corporations that were engaged in REACH Incubator. Below are our findings.

Trends & Insights

Data Providers that participated in the initial survey stated that corporations they work for are mostly interested in data management to generate new insights for business optimization, data analytics for R&D projects, historical financial data of the customers, and new data driven ways to monetise a value for their clients (decision making process) and users (experience).

Signals of disruption

First intuitions into the signals of disruption identified are integration of automation services based on data. We are seeing efforts and importance given to actions that are supported by data, on how and what data is collected that still relies on human decisions. Moreover, the new push towards Data Value Chain requires continuous tech as well as mindset change according to new evolved customer needs. Perception is that customers want to approach data value chain in an easy and comprehensive way. From a technical point of view more and more attention is paid to AI algorithms to evaluate and take profit from big data.


The main barrier mentioned was competition, as there are a lot of large companies with huge amounts of data and challenges.

Furthermore, a significant barrier is related to tech solution providers (e.i startup) which are often generic and not specific to data providers’ domains. Additionally, more often than not, the startups tend to focus on their own strategy development, which may go beyond the corporate problem, and therefore neglect it of sorts.

Furthermore, common data-based problems an organisation seeks to solve with Big Data Open Innovation are mostly related to the identification and development of most adequate algorithms to process the data and generate useful models for decision making.

Next, AI algorithms need great amount of data to be trained and implemented. Often a single source data solution needs other data to be efficiently implemented, and data-oriented companies can combine different data sources thanks to open innovation systems.

One of the problems that appear is how to make the data pre-processing steps more effective and efficient.

Opportunities for growth

Some of the first opportunities for growth that are detected by the REACH Data providers are flexible and cheaper access to cloud infrastructure to scale the data management.
Data Providers are on the track with the latest evolutions of data analytics and always try to focus on new opportunities. As Data Providers, they collect a great amount of data, for example related to manufacturing or facility sectors, and are more interested in added value tech and analytics fuelled solutions.

Furthermore, the quality of the data sets is increased, and the data community should use the chance to utilise the data generated in order to enhance their solutions together with a higher knowledge of the user profile.

Data Providers were asked to what extent they believe that the exploration, valorisation and exploitation of data assets through a Data Value Chain (Data Provider together Data -startup(s)) can impact their activities, and how they can contribute to generate future business/ innovation opportunities. The consensus is that they are directly linked, the more you know about the business needs and the available data the best solution is developed. If, in addition, a technical expert (startup) is involved a much more advanced service will be generated.

Furthermore, there is a perspective on this topic that the data value chain paradigm will be a key factor in future data science and management development. The level of specialisation required in each field and in each step of data fuelled business leads to a shared approach involving other partners to create and approach opportunities

Key Success Factors

Theoretically, future business/innovation opportunities are very positive if the interests of the Data Provider and Data startups are aligned. Some startups are only looking for the money in order to develop their own products, forgetting completely the Data Provider’s interests.

Access and collaboration with top developers interested in data and business innovation, as well the quality of the solutions proposed, and the business opportunities offered were listed as one of the key success factors.

Data Providers also briefly reflected if their involvement in Data Value Chains strengthen their position or leadership in the market. One of the surveyed providers mentioned that their involvement in DVC positioned the company as an innovative player interested in sharing its data for open collaboration with business-oriented goals.

Besides, the involvement in Data Value Chains shapes their business and company profile, as they are well recognised in their reference markets and gave them a chance to acquire major company attention.

Furthermore, one of the data providers declared that the performance of their machine learning models has improved with this involvement, which makes people do less paperwork. Thus, they now have more automated systems, and people can work more focused on their other works.