When we started the Fusióni3 project, I thought the main challenge would be technical. Articulating the innovation needs of fifty companies with the capabilities of nine universities sounded complex, but manageable. After all, both worlds need each other. What could go wrong?
Three years later, I understood that the challenge was never technical. It was political, human, about timing, language, and, above all, expectations that were never going to align perfectly. Because we weren’t working with two actors, we were working with three. And each one operated under logics that, more than just different, were sometimes directly incompatible.
The three worlds that are not alone
The universities brought something invaluable: knowledge. In many cases, research groups helped companies understand that the problem they thought they had wasn’t the real one. This support elevated the level of the discussion and allowed for more informed decisions. That’s something rarely achieved without academic backing.
But that same knowledge came with a structural difficulty. Having the capacity to solve a challenge—the people, the laboratories, the infrastructure—doesn’t mean having a service ready to offer to the market. When a company expressed interest, the valuation of the work was usually a sum of costs: salaries, use of space, equipment, student interns. The result was a technically justifiable budget, but one that the market wasn’t willing to pay. And that’s where the friction began.
The companies, for their part, contributed dynamism, enthusiasm, and a practical perspective that kept us grounded in reality. Their focus on the customer and the product helped us avoid getting lost in abstract concepts. This exchange is one of the greatest benefits of collaboration between universities and businesses: combining scientific rigor with business acumen.
But that same dynamism came with anxiety. At first, three years seemed like an eternity to develop a technological solution. Over time, reality revealed a different side: many were operating with such tight schedules that they struggled to complete tasks, maintain the project’s pace, or coordinate meetings with researchers. And when conversations arose about intellectual property or licensing—common topics in the academic world—the language became unfamiliar, and the discomfort slowed everything down.
The government, in this case the Ministry of Science which oversaw the project, had people with solid technical knowledge who helped anticipate risks and protect us from scrutiny by regulatory bodies. That role is valuable and necessary.
But that same care resulted in a flood of information requests. Much time was spent drafting responses that seemed straight out of a manual, uploading files to platforms designed in another era, and fulfilling requirements that, while important, consumed a disproportionate amount of energy. And because the supervisory body was managing many projects simultaneously, response times tended to be longer, gradually impacting the teams’ workflows.
None of these three were wrong. But they weren’t automatically compatible either.
Time is never the same
The most difficult thing to manage was the timing. Universities work in research cycles measured in years. Companies operate in quarters, with constant pressure for immediate results. Government functions in political periods and budget cycles that have their own logic. Synchronizing all of that is nearly impossible.
I learned that I couldn’t force artificial synchronizations. I couldn’t make research move faster without compromising rigor. I couldn’t make companies wait indefinitely without losing interest. I couldn’t make the government ignore its oversight and accountability obligations.
What it could do was design agreements that acknowledged those differences. Partial deliveries that would give the company something tangible while the research progressed. Intermediate indicators that would give the government visibility without demanding premature final results. Flexibility in deadlines that would give universities reasonable space without becoming indefinite.
But even those agreements were fragile. Because when a business owner cancels a meeting for the fourth time because “the week got complicated,” the researcher starts to feel their work isn’t valued. And when a researcher asks for “a couple more months” to validate results, the business owner begins to doubt that this is going anywhere. And when the supervisor requests an additional report to clarify a point that was already explained, everyone feels they’re working for compliance, not impact.
What no one says but everyone knows
There are things that don’t appear in reports but that determine the outcome of a project. A researcher might refuse to collaborate with a company not because the technology doesn’t work, but because that collaboration compromises their academic autonomy or delays a publication they need for their career. An entrepreneur might withdraw not because the solution is bad, but because the process is so slow that they’ve already missed the market opportunity. A public official might block a contract modification not because it’s unfeasible, but because it complicates their relationship with the oversight department.
I learned to read those unwritten codes. To understand that prestige matters as much as resources in the academic world. That reputational risk can outweigh financial risk for a company. That political visibility can define the continuity of a program more than its technical impact.
Understanding that allowed me to anticipate resistance that wasn’t obvious. And it also forced me to accept something uncomfortable: sometimes a project isn’t viable not because it’s technically flawed, but because the goals of the three worlds are too divergent.
The role no one wants but someone has to do
Leading these kinds of projects makes you suspect to all three groups. Researchers may see you as too commercial. Businesspeople as too academic. The government as someone who doesn’t understand oversight responsibilities or is too focused on the technical aspects.
That suspicion is inevitable. Because you don’t belong completely to either side. And that’s unsettling. But it’s also what allows you to mediate, because you’re not exclusively loyal to any one logic.
I learned to tolerate that discomfort. Not to try to convince anyone that I belonged to their world. Instead, I learned to demonstrate that I understood all three of them well enough to help them collaborate without betraying each other. What I could do was design agreements that acknowledged those differences. Partial deliveries that gave the company something tangible while the research progressed. Intermediate indicators that gave the government visibility without demanding premature final results. Flexibility in deadlines that gave universities reasonable space without becoming indefinite.
And I learned something even more important: my job wasn’t to make these worlds think alike. It was to create spaces where they could collaborate without compromising their defining characteristics. Where researchers could defend their rigor. Where entrepreneurs could manage their risk. Where governments could fulfill their mandates. But even these agreements were fragile. Because when an entrepreneur cancels a meeting for the fourth time because “the week got complicated,” the researcher begins to feel their work isn’t valued. And when a researcher asks for “a couple more months” to validate results, the entrepreneur starts to doubt whether this is going anywhere. And when a supervisor requests an additional report to clarify a point already explained, everyone feels they’re working for compliance, not impact.
The most important conversations weren’t those that sought consensus. They were those that sought mutual understanding. That the researcher understood that the entrepreneur wasn’t being anxious, but rather managing commercial viability. That the entrepreneur understood that the researcher wasn’t being a perfectionist, but rather defending scientific validity. That the government understood that innovation timelines don’t align with administrative cycles.
When that understanding existed, agreements could be drawn up. When it didn’t, there was only frustration.
What remains when the deliverables are finishe
The I3 merger yielded concrete results: products and services that are now on the market or on their way. But the most profound lessons aren’t found in the metrics. They lie in the difficult conversations we had. In the tensions we learned to make visible and manageable. In the companies that understood that research takes time. In the researchers who learned to translate their knowledge into commercial value propositions. In the officials who streamlined processes whenever possible.
Working at that intersection is exhausting. Because you’re always translating, mediating, explaining, managing expectations. There’s never a simple solution because the systems are inherently complex. And sometimes you have to pause and remind the team of something essential: most of our time, focus, and creativity should be on the client and the real impact of the project, not on pleasing the supervisor.
But it’s also where the most interesting things happen. Where science finds real-world application. Where companies access knowledge they couldn’t generate on their own. Where government can catalyze innovation that benefits more people.
When those connections work, when you see a researcher, an entrepreneur, and an official building something together that none of them could achieve alone, you know that the invisible work of articulation was worth it.
Have you led projects where the actors operate with different logics?
How have you navigated tensions that are not resolved, only managed?
