How Collaboration Turns Research into Real Decisions

Most research doesn’t fail because the data are wrong—it fails because no one knows how to use it. A new study of environmental projects across the United States shows that relationships, not models, are often the difference between science that sits on a shelf and science that changes lives.

That insight comes from a rare comparative analysis of six real-world research projects led by scientists working with communities, governments, and Indigenous partners. The projects span freshwater estuaries, coastal cities, forests, aquifers, and watersheds—and they all ask the same quiet question: Why does science sometimes matter, and sometimes not?

The Problem We Don’t Like to Admit

For decades, science has been built on a simple belief: if we produce good evidence, decision-makers will use it. That idea sounds reasonable. It’s also often wrong.

Think about cooking. You can have the best recipe in the world, but if it uses ingredients no one has or assumes a kitchen that doesn’t exist, dinner isn’t happening. Environmental science faces the same problem. Models are elegant. Frameworks are rigorous. But they’re often designed far from the places where decisions are actually made.

This study calls that gap out directly. Across six cases, the authors found that technical excellence alone rarely leads to action. What mattered most was whether scientists understood the people, places, and pressures shaping real decisions—and whether those people trusted the science enough to use it.

The “Aha” Moment: Relationships Are the Method

The research team didn’t run experiments in a lab. Instead, they analyzed years of documents, meetings, reports, and collaborations from six long-term projects supported by the U.S. Environmental Protection Agency’s research arm. They compared who was involved, what decisions were being made, where the work happened, and what outcomes followed.

The pattern was striking.

Projects with long-standing partnerships—sometimes built over a decade—were far more likely to see their research shape real decisions. In contrast, newer collaborations often produced useful information that… went nowhere.

This wasn’t about intelligence or effort. It was about alignment.

In places like the Great Lakes or San Juan Bay, scientists worked side-by-side with agencies and communities. They co-defined problems, adapted tools to local realities, and stayed engaged long after reports were written. The result? Research influenced restoration designs, health planning, water management, and policy debates.

Short-term projects, by comparison, struggled to move from insight to impact.

But here’s the twist: that’s not a failure—it’s a phase.

Why Place Changes Everything

One reason these collaborations worked is that they were deeply tied to place.

In rural Oklahoma, water management revolved around a shared aquifer that sustains cities, farms, and Tribal lands. In Puerto Rico, ecosystem services were linked not just to water quality, but to housing conditions, heat, disease risk, and everyday well-being. In Oregon and Washington, forest practices upstream shaped salmon habitat, jobs, and cultural identity downstream.

These weren’t abstract “stakeholders.” They were neighbors, fishers, planners, elders, and families.

The study shows that place itself becomes a bridge, a shared reference point that helps scientists and decision-makers translate between data and daily life. Ecosystem services were not jargon but a common language: clean water, safe food, flood protection, recreation, and health.

And when science spoke that language, people listened. But here’s where it gets even more practical.

Three Lessons for Scientists Everywhere

Whether you work in Nairobi, New Delhi, São Paulo, or a small coastal town, the lessons from this study travel well.

1. Closer to the problem beats cleverer tools

The research most likely to be used was the research shaped with decision-makers, not just delivered to them. Relevance mattered more than sophistication.

2. Early projects should measure trust, not outcomes

New collaborations shouldn’t be judged only by immediate impact. Building shared understanding is real progress—even if policy change comes later.

3. Translation is not dilution

Working across boundaries didn’t weaken the science. It strengthened it by forcing clearer questions, better assumptions, and more realistic applications.

In other words, engagement wasn’t a distraction from science—it was the science.

The Bigger Picture: Science in a Changing World

Many readers of this article work in places facing rapid change—climate shocks, urban growth, water stress, food insecurity. In these contexts, waiting for “perfect evidence” is not an option.

This study offers a hopeful alternative: science that moves at the speed of relationships. Science that learns as it goes. Science that respects both data and lived experience.

That model may be especially powerful in low- and middle-income countries, where formal data systems can be limited but community knowledge is rich. The message is clear: you don’t need more distance between research and practice—you need better bridges.

And those bridges are built one conversation, one meeting, one shared decision at a time.

So let’s end where good science begins—with curiosity.

Let’s Explore Together

• Could this kind of long-term, place-based collaboration work in your community?
• If you were designing one of these projects, who would you bring in from day one?
• What everyday problem around you feels “researchable” but is ignored?

Science moves forward when we ask better questions—and when we ask them together.