Data ecosystems only create value when organisations define how collaboration works

 

Many organisations are willing to share data, but still hesitate to make the decisions that matter

Organisations are increasingly working with partners, suppliers and other stakeholders across their sector to share data. The benefits are clear: better services, more efficient value chains and smarter decision-making across organisational boundaries. Our research into the digital reality of European organisations, the Tech Reality Check 2026, confirms this trend. Two-thirds of organisations are already working on data ecosystems to some extent. Yet only a small minority have succeeded in establishing structural collaboration.

According to Ernout Douqué, CTO at Conclusion Intelligence, this is where the tension lies. “Executives rarely ask whether they want to participate in data ecosystems. That question has already been answered. The real question is: under what conditions are we willing to give up some control?”

This makes collaboration in data ecosystems a board-level challenge. Good data, APIs, standards and secure infrastructure are essential. Yet the real obstacles arise earlier: around ownership, liability, decision-making and trust in how the ecosystem is governed. Until these issues are addressed explicitly, collaboration remains stuck in pilot projects. Active enough to claim progress, but too cautious to create lasting value.

“Pilots are comfortable from a governance perspective,” says Ernout. “Liability and ownership remain limited, manageable and clearly defined. But once you move towards long-term collaboration, you have to clarify who is responsible for what. That is where friction emerges.” The friction is understandable. Any executive who agrees to share data accepts a tangible risk: legal liability, privacy implications and potential reputational damage. The value in return often materialises later. Better services, more efficient value chains, smarter decision-making and new propositions are attractive outcomes, but rarely easy to quantify from day one.

According to Ernout, this explains why many organisations continue to optimise within their own boundaries. “Everyone wants to collaborate, but when it comes down to it, accepting a concrete risk in exchange for future value and additional organisational complexity is challenging.”

On paper, many organisations appear further ahead than they are in practice. They have a data strategy, recognise the opportunities of collaboration and understand the potential value of sharing data. Yet there is often a significant gap between strategy and execution. The Tech Reality Check reflects the same pattern. Many organisations have a strategy for data exchange, while structural collaboration remains limited. “That points to a lack of follow-through,” says Ernout. “Organisations commit to the strategy, but not yet to its consequences. That means investing in technical readiness, establishing legal frameworks upfront and explicitly assigning ownership within the ecosystem. Without those decisions, a data strategy is little more than a statement of intent.”

This is an important distinction. A data ecosystem does not emerge because organisations declare collaboration important in a strategy document. It emerges when participants agree on which data will be shared, who remains responsible for data quality, which standards apply, how errors are handled and how collaboration ends if participants part ways. Those discussions are often less appealing than the promise of the ecosystem itself. They are concrete, sometimes complex and usually require negotiation. Yet without that foundation, collaboration remains fragile.

Choosing not to act can feel sensible. Especially when legal frameworks remain uncertain, standards continue to evolve or partners are not yet at the same level of technical maturity. Yet waiting is not a neutral decision. According to Ernout, two things happen. First, an organisation's negotiating position weakens. “Organisations that only join once standards and governance frameworks have already been established by others often have little choice but to accept them.”Second, they miss out on valuable learning opportunities. Collaboration in data ecosystems cannot be learned from the sidelines. Organisations that start earlier with governance frameworks, agreements and system integration build capabilities that are difficult to replicate later. Germany is an interesting example in the research. Where strategy, execution and governance are aligned, organisations report measurable improvements more frequently.

“Those results are not something you catch up on within a year,” says Ernout. “Organisations that continue optimising isolated parts of the puzzle today may find themselves structurally behind in a few years’ time.”

This makes data collaboration more strategic than many organisations currently treat it. It is not just about improving information exchange. It is also about determining the role an organisation will play within a value chain, industry or public-private partnership. Those who help shape the ecosystem influence the rules. Those who join later are more likely to inherit them.

The first question is often: which data can we share? According to Ernout, that is not the best place to start. “Begin by asking under which conditions you would be willing to share data, and with whom. Ownership and liability should not be treated as a final legal review. They should be design principles for the collaboration itself.”

That requires explicit conversations about governance. Who remains the owner when data flows through the ecosystem? Who is responsible for quality? Who is liable if incorrect or outdated data causes harm? Which standards will participants adopt? And what happens to data when an organisation leaves the ecosystem?

Far from making collaboration unnecessarily complicated, these agreements make collaboration easier. They prevent every new initiative from getting stuck in the same uncertainties. “A well-designed ecosystem ensures partners can access data without ownership automatically changing hands,” says Ernout. “Modern data architectures, including concepts such as data spaces and zero-copy data sharing, make that possible. But technology only works when governance has been agreed upfront.”

When executives ask Ernout where they should focus in the coming months, he does not start with a new platform. He starts with decisions. Establish the legal framework before the next pilot begins. Select one ecosystem in which the organisation wants to participate structurally and invest deliberately in standards and API readiness. And make data maturity a board-level KPI, rather than a partially defined IT objective. That last point matters. Data maturity encompasses ownership, data definitions, decision-making, security, compliance and the ability to use data effectively in collaboration with others.

“The common mistake is believing that governance can wait until the technology is ready,” says Ernout. “Successful organisations develop data strategy, governance, organisational capabilities and technical execution at the same time.” That requires leadership in the boardroom. Not as an abstract digital topic, but as a concrete discussion about value and risk. What level of liability is the organisation willing to accept? What value should collaboration deliver? Over what timeframe? And who ultimately owns the issue when it risks falling between the responsibilities of the CIO, CFO and COO?

The Tech Reality Check shows that organisations are generally good at identifying their digital challenges, but less effective at translating those insights into coherent decisions. Data ecosystems illustrate this pattern clearly. The ambition exists. The first steps have been taken. But moving towards structural collaboration requires more than participating in a pilot or building a technical integration.

According to Ernout, progress starts with clear choices. “The question is not how far you have progressed with data ecosystems. That usually leads to updates about pilot projects. A better question is: which liabilities are we prepared to accept, what value should this create, and who takes executive responsibility for it?” That shifts the conversation from cautious exploration to deliberate action. Because data ecosystems only create value when organisations are willing to define how collaboration works. Who shares what, under which conditions, for what purpose and with what responsibilities? Technology can enable a great deal. But real value emerges only when leaders are prepared to set the rules of the game.