A few thoughts on turning information into insight — and legacy systems into living assets
The New Public Resource: Data
Data has become the modern public infrastructure — as essential as roads, but far more under-used. Every transaction, application, and service interaction generates knowledge about what citizens need and how they behave. Yet in many government environments, that knowledge remains locked in silos or outdated systems. Maybe we need a call to shift from instinct-driven policy to evidence-based design — and to treat data as a shared, reusable public asset.
From Reporting to Learning.
Sometimes you manage programs where “data” means end-of-quarter reports — static PDFs reviewed long after decisions were made. Then you might lead an initiative where dashboards are live, accessible, and updated daily. The difference is transformative. Instead of debating opinions, teams debate evidence. You can see, for example, that 68% of applicants are abandoning a form on page three. Instead of guessing why, you observe, iterate, and fix it. Abandonment drops by half within a week. This is the essence of a data-driven product culture: you shorten the distance between insight and action.
Build Once, Use Everywhere
In government, we often rebuild the same digital plumbing — logins, payment gateways, form systems — because each department starts fresh. This fragmentation wastes public funds and creates inconsistent experiences for users. Infrastructure reuse flips that equation. When we design APIs, data models, and authentication services that can be shared across ministries, we not only save money but create coherence.
Interoperability as a Leadership Mandate
Reusing infrastructure isn’t just a technical decision — it’s a leadership one. It requires coordination, trust, and a willingness to collaborate across organizational boundaries. Citizens shouldn’t need to submit the same information twice. This perspective shift unlocks cooperation.
Responsible Data Stewardship
With great data comes great responsibility. Being data-driven doesn’t mean collecting more — it means collecting better and protecting what you collect. That’s how we maintain the public trust that makes digital transformation sustainable.
As a product manager, fist questions that come to mind are:
- Do we truly need this field or dataset?
- How will we explain to users why it’s needed?
- Who owns and governs it once collected?
From Legacy to Living Systems
Most government data still sits in legacy systems — stable but stagnant. The product mindset treats those systems not as obstacles, but as foundations to modernize incrementally. Expose legacy data through APIs. Wrap old databases with modern interfaces. Build lightweight bridges instead of massive replacements. I’ve seen entire modernization projects succeed simply by connecting what already existed — proving that progress often means evolution, not replacement.
Servant Leadership in the Data Age
In a data-driven culture, servant leaders don’t hoard information — they democratize it. They make insights visible to every team, encourage evidence-based debate, and reward curiosity over certainty. Leaders who share data freely create environments where innovation happens naturally — because everyone can see the truth, not just the top.
Key Takeaways
- Use data to learn, not to report. Insight delayed is insight lost.
- Design for reuse. APIs, platforms, and shared components save time and ensure consistency.
- Break silos through shared purpose. Collaboration grows when it’s tied to citizen outcomes.
- Protect privacy by design. Transparency is the foundation of trust.
- Lead through openness. Empower teams by giving them access to evidence, not assumptions.
Final Thought
A data-driven government isn’t one that collects more information — it’s one that listens better. When data flows freely across systems and decisions are guided by evidence, we build public services that adapt as quickly as citizens do. And when infrastructure is designed for reuse, every new service strengthens the next.
That’s how we transform data from a liability into a legacy — shared, ethical, and continuously learning.