The Data-Driven Park

From Martin Rowland, CEO

From opinion-led to evidence-led public spaces: what data should influence park infrastructure?

Public-space decisions will always involve judgement.  Parks, streetscapes and community spaces are human environments. They need creativity, place-based thinking and an understanding of how people feel and behave. Context matters, and good design responds to that.

So then, judgement becomes stronger when it is supported by what has already been learned and it makes sense that in order to create the best community spaces, the future of public-space infrastructure should be more evidence-led.

Most councils already hold information needed to support better decisions.

Maintenance records, community feedback, usage data, asset registers, incident reports, cleaning schedules, heat exposure, vandalism history, replacement frequency and budget performance all contain signals.

Across the industry, we see the same pressures coming through this data – maintenance burden, budget constraints and competing community expectations. The challenge is that this information is often separated from the design and procurement process:

• The people designing the next park may not see the maintenance patterns from the last one.
• The people choosing the product may not see the replacement history.
• The people writing the specification may not have access to the community feedback after the previous project opened.
• The contractor may understand site realities that never make it into future design standards.
• The manufacturer may see recurring product or installation issues across many projects, but that insight may not be captured in a structured way.

The opportunity is to connect the feedback loop.

As an example, a public-space product is not just durable or not durable. It is durable in a specific context – for instance, coastal exposure is different from inland heat.

A high-use regional playground is different from a small neighborhood park, just like a CBD streetscape is different from a sports precinct.  A shaded picnic area is different from an exposed foreshore.  And a BBQ installed in a heavy-use destination park will face different demands from one installed in a quiet local reserve.

So instead of asking "Is this product strong?", let’s move to the level deeper - "is this product strong enough for what environment, what use pattern, what maintenance model and what asset-life expectation?"

That is where evidence adds value.

• It can help councils prioritise investment where the community benefit is highest, based on real community use and long-term performance – not assumptions.

• It can help designers understand how spaces are actually used after completion.

• It can help contractors identify installation risks earlier, and ideally before they reach site.

• It can help manufacturers improve products based on real-world performance across multiple environments.

• It can also help the industry have more mature conversations about value.

Lowest upfront price is easy to compare. Long-term or whole of life value is harder.

But if we can bring better information into the conversation - maintenance cost, replacement frequency, warranty performance, cleaning requirements, spare-part availability, installation efficiency and user outcomes - then procurement can become more informed and more balanced.

That does not mean every project needs a complicated data model. Sometimes the starting point is simple.

• What failed early on the last project?
• What generated the most maintenance calls?
• Which products performed better than expected?
• Where did users gather most often?
• Which spaces felt underused?
• What did the contractor wish had been clarified before installation?
• What did the asset team inherit after handover?

These are practical questions drawn from real projects which feed into the data that will underpin judgement and decisions. Insights from each project continue to build from the last. Decisions become more informed, risk becomes more visible and outcomes more consistent..

The industry does not need to choose between design thinking and evidence. The best outcomes will use both.

Design creates the vision.
Evidence sharpens the decision.
Partnership ensures it is delivered properly.

As public spaces face higher community expectations, harsher climate conditions and tighter budgets, I think the ability to learn from real projects will shape better outcomes across the industry.

We should be asking not only, "What did we build?"

We should also be asking, "What did we learn, and how will that improve the next space?"