Smart cities don’t need another platform project — they need outcomes

The challenge is that many digital programs still start from the same place — rebuilding technical foundations from scratch. Often by combining some open-source and cloud infrastructure components into pilots that do not scale. Data ingestion, integrations, dashboards, permissions, maintenance… the work is necessary, but it is rarely what citizens see as better services. After these publicly funded projects, many of the pilots never move into sustainable operations, leaving cities without long-term value. In worst cases, poorly maintained systems can increase the cybersecurity risk.

If cities repeatedly fund the same digital foundation work instead of scaling proven capabilities and investing in citizen-facing outcomes, we should ask that question openly. Public funding should maximize long-term impact, not repeated reinvention that does not add value.

A more effective approach is to treat the foundation as shared infrastructure and focus city money on what creates visible impact. OECD’s work on smart city data governance and data-driven public sector transformation points in this direction: the value is in how data improves decisions and services, not in endlessly recreating the same base layer city by city.

The “build everything custom” model deserves scrutiny. For example, in a recent European procurement case, the budget level was around €2 million for a 3-year framework. At that scale, city leaders should ask how much funding goes to commodity platform work versus services that create visible citizen value. Based on comparable long-term service models, that same budget class can correspond to 20+ years of access to a commercially maintained platform, while leaving room to invest in local integrations and new use cases.

The good news is that cities don’t need a blank-sheet digital program — they already have valuable infrastructure in place: cameras, sensors, building systems, and multiple data sources. The real question is how to use those assets more intelligently and convert them into better daily decisions: what is happening now, what is likely to happen next, and where teams should act first.

A practical way forward is to start with a small number of high-priority use cases, use configurable solutions instead of rigid one-off builds, and evolve in short cycles with clear ownership and measurable outcomes. Many cities have found this model more sustainable than launching another large platform-first program.

A common question is whether dedicated tools for areas such as mobility, safety, environment, or operations are always better than a shared city platform. In some single-purpose scenarios, dedicated tools may offer deep features. But in real city operations, they are often rigid to adapt, expensive to integrate across domains, and costly to operate as a fragmented stack.

With a shared city platform, city teams can adjust views, reporting, and workflows quickly — often in minutes instead of long custom development cycles — using low-code/no-code tools. This matters when service needs change, political priorities shift, or new regulations appear. In practice, the platform provides one common foundation for city data, devices, workflows, and applications, instead of building and maintaining separate foundations for each service area.

What makes the platform especially powerful is that development does not have to stop at one city. If one city improves a feature, template, or workflow, others can reuse and adapt it instead of paying to reinvent the same thing. This is very much aligned with the broader European push for interoperability, reusable digital building blocks, and local digital twin ecosystems that scale through collaboration rather than isolated one-off projects. Living-in.EU highlights that insufficient interoperability still hinders cities’ digital and sustainable transformation, and points to common frameworks and recommendations that help cities work across domains, organizations, and borders.

The same principle applies to budget efficiency. Many cities worry that adopting a platform adds “one more cost layer.” In practice, the opposite is often true: a shared platform helps remove overlapping costs from multiple siloed systems, duplicate integrations, and parallel maintenance. For example, if a city buys separate systems for mobility, safety, environment, and operations, the total lifecycle cost can be significantly higher than extending one shared city platform with the needed use-case modules. The strategic point is simple: invest once in reusable capability, then scale services on top of it.

A common follow-up question from city leaders is: “Do we still own our data if we use a commercial platform?”

This view should be very clear: the city should own its own data, and the platform operator should not. This is not only a legal or technical detail — it is a strategic principle. If the city does not own its data, it cannot fully control how the data is used, who can access it, what is shared through APIs, or how future services are built on top of it. Data ownership is what gives the city the freedom to govern its digital ecosystem, collaborate with partners on its own terms, and avoid becoming dependent on a single vendor. Discussing the data ownership and API access later on often proves to be a costly challenge for the cities.

In practice, cities should be able to define in detail who can access what, what data is shared, and what can be published as reusable data products or services. This level of governance is essential for trust, procurement acceptance, and long-term scalability.

Another recurring concern from city leadership is sovereignty and trust: where data is stored, under whose control it remains, and how security is maintained over time. These are not side questions anymore; they are central procurement questions. A city platform approach only works if governance is clear: the city should own its data, control how it is shared, and be able to choose the deployment model (EU cloud, local cloud, or on-prem when needed). OECD’s smart city governance work reinforces exactly this need for clear institutional control and accountability in data use.

Cybersecurity must be treated the same way: built in, not bolted on. Established guidance, such as NIST’s zero-trust architecture emphasizes identity-, asset-, and policy-centric protection instead of assuming anything is safe by default. For city environments with many actors and connected systems, that mindset is increasingly essential. ENISA’s smart infrastructure and transport security guidance similarly highlights that urban digital services require systematic security practices across the full lifecycle, not ad hoc controls.

There is also a myth worth retiring: that a ready-to-use platform and apps somehow reduces local innovation or local jobs. In practice, the opposite is often true when the platform is open and extensible. Low-code/no-code capabilities, APIs, and marketplace-style sharing make it easier for local integrators, universities, and SMEs to build value-added services on top of production-grade city infrastructure. Instead of coding the same baseline repeatedly, local actors can spend time on higher-value work that is specific to local needs.

A strong example is the City of Vaasa, which utilized ready-to-use solutions and engaged the local innovation ecosystem to further develop these solutions, to the benefit of the citizens and other cities alike. This shows that even smaller cities can build smart city operations, when the collaboration model and reuse of existing solutions are planned well from the start.

In the end, this is a strategic public-value choice. Cities can keep funding repeated technical reinvention, or they can build on proven foundations and direct more budget to outcomes people actually notice: smoother mobility, safer public spaces, better maintenance, lower energy use, and faster response in disruptions.

If the goal is better services with tighter budgets, the recommendation is straightforward. Start with three decisions:

1. Reuse a proven, maintained foundation instead of rebuilding the base layer.
2. Treat what you already have as an asset — cameras, sensors, building systems, and existing data sources — and make them usable through sensible integrations and governance.
3. Focus on a small set of high-priority use cases with clear owners, measurable targets, and a path from pilot to operations.

That is how smart city programs move from pilots to operations — and from spending to impact.