Creating the Conditions to Innovate Better

When we talk about open innovation in the public sector, one of the most important questions is: what problem do we want to solve, why, and for whom?

At Gobe, we create the conditions for public sector teams to collaborate with specialised tech companies.This allows them to test new technologies and innovative approaches that would otherwise be difficult to explore. When well facilitated, this process generates insights and evidence to support better decisions about which technologies to adopt, while creating long-term impact.

Some examples of this impact include helping a city find ways to save energy and public funds, improving data quality to increase transparency, or enabling a farmer to register the birth of a calf more easily.

Creating the right conditions means carefully shaping each step of the solution development process. It’s about designing spaces and processes that make it possible to incorporate input from people within the administration: What’s your roadmap for the year? Have you tried something that didn’t work? What have you learned? What references inspire you?

It also means drawing on external experts, whose perspectives can offer unique insights: What are the most relevant trends in the sector? Which use cases should we have on our radar? What could have the greatest impact on citizens?

In short, it’s about bringing the right voices into the process at the right time, and asking the right questions. It’s about building the richest possible starting point so that, when we define the challenge, it reflects a strategy, a need, and a context that responds not only to today but also to the future—and to the needs of the administration, citizens, and the broader ecosystem.

In this article, we explore what we mean by creating the right conditions, how we use design to strengthen research, and how we tailor our approach to fit each project.

Research is not optional, but it is adaptable

When we start an open innovation project, it’s common for many things to be unclear at the beginning. Unlike other innovation processes, here we start from scratch. There’s no brief, no pre-formed teams, and sometimes not even a clearly defined area. There might be general ideas or selected technologies, but the problem is rarely defined from the perspective of the people who will actually use the solution.

This is where the research phase begins. We gather data on needs and expectations, analyse processes and tools, and turn that information into insights that guide solution proposals.

A data point tells us what is happening—it's objective, unfiltered information. An insight helps us understand why it’s happening and what we can do about it.

For example, shifting from the statement "most trips within the municipality are made by private car" to the insight "people use cars because public transport doesn’t adequately cover cross-neighbourhood travel, timetables, or accessibility needs".

With experience, we’ve learned to research with precision: going deep enough to understand the problem and its context, but without getting lost in endless analysis. In a short amount of time, we need to be able to frame problems clearly so that, when presented to the entrepreneurial ecosystem, they can be turned into actionable pilots.

This is where the usual debate comes in: "A couple of interviews will suffice" versus "We need to dig deeper." Both perspectives have their place depending on the project and stage of the institution.

For instance, in TwIN Navarra, we work with digital twins. Since the technology was already in place, our goal was to identify use cases for the City of Pamplona. We researched international benchmarks and inspiring digital twin applications and conducted desk research on possible use cases.

Based on that research, we conducted interviews to understand the city's baseline situation. Then, we designed workshops with city teams and the broader ecosystem, including universities, tech centers, and SMEs, to define opportunity areas.

These spaces capture diverse perspectives because the conditions are designed to incorporate different needs and viewpoints.

As we see it, this is how innovation—and the cities of the future—should be built: with imagination, collaboration, and valuable insights.

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By contrast, in DesafIA Madrid, the focus is different. Here, the aim is to help startups improve their solutions to better respond to public sector challenges. This format creates a win–win dynamic: companies improve their products, and the City gains insight into what’s available on the market while contributing to solutions that are aligned with its needs.

To achieve this, we first identify high-impact opportunities through interviews with municipal leaders and workshops with the City’s technical teams. Based on that input, startup teams meet with public servants every two weeks to test prototypes, refine features, and validate the product using real data and practical use cases.

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Testing these solutions not only brings improvements—it also creates a space for learning. When public sector teams explore technologies in real-world situations, rather than just in theory, important questions begin to surface:

At what points does it make sense to automate a procurement process, and when is it still essential to have a person involved? In which scenarios do IoT sensors provide real-time value, and when do they generate more noise than useful data?

These practical reflections are what help shape technology so that it truly responds to people’s needs.

To define challenges that truly make sense, we need to understand what’s happening both inside and outside the organisation. Thorough research helps lay the foundation for challenges that include the kind of nuance that maximises the chances of developing tools that are actually used and that meaningfully improve people’s lives.

It’s how we avoid short-lived or disconnected solutions—those that aren’t designed to be used, don’t integrate with existing infrastructure, or simply don’t fully address the initial problem.

What’s the point of having a WhatsApp channel to report damage in public spaces if it isn’t integrated with the CRM and no one can respond in time?

When we clearly define the problem, we increase the chances that the pilot will work, be used, and endure.

But it’s not just about researching and shaping insights—it’s also about co-creating, and knowing how to connect those insights and ideas to frame clear, purposeful challenges.

Innovation also means rethinking how we work together

What we call “creating the right conditions” has a lot to do with enabling collaboration between people and roles that don’t usually sit at the same table, and giving space to voices that are not always heard—technical staff, legal teams, tech companies, or citizens.

It’s at those intersections where improvements emerge that would have been impossible to see from a single perspective, and where synergies arise that last well beyond the pilot phase.

We often say that part of innovating is being willing to change how you’ve done things up until now. It’s not just about solving a technical problem—it’s about changing how you work and how you relate to other teams.

When we work this way, our goal isn’t just to define challenges, but to support teams through the process of change.

It’s also a shift in mindset. It means moving towards designing solutions based on people’s needs and real use cases—what do we need to solve, and how?—rather than starting from the technology—how can I apply this already-developed solution?

This doesn’t mean technology should be left until the last minute. It means integrating it as a partner along the journey—one that doesn’t bias or dictate the process, but that helps reveal the possibilities emerging from the needs we uncover.

Challenges should no longer speak only of needs and questions, but also of the technology stack in which those solutions will live.

The ultimate goal isn’t one-off, short-lived pilots. It’s pilots with real impact—those that build on existing infrastructure, enhance it, and enable solutions that can scale and stay. That’s what sustained value looks like.

Defining GovTech challenges isn’t a rigid process. It’s a practice we refine with each project to ensure it’s useful and actionable. Every organization has a different context, and not all of them need the same things. Our job is to adapt to that reality and help each organization innovate with purpose.

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