Why You Need Data for System Change

Transparency is about making the invisible visible. By revealing the true scale of a problem, it becomes harder for governments, companies, and the public to ignore. It transforms isolated incidents into clear evidence of systemic failure. This kind of data created accountability. 

Once a problem is made visible, the next step is to understand its scale and explore solutions through models and hypotheses. This starts with problem sizing - using volumetric models to quantify issues. Then financial models help estimate costs, test possible interventions, and compare the cost of action versus inaction. Afterwards, we develop hypotheses to explore what might work. Although models often rely on assumptions and imperfect data, they are valuable when they’re directionally correct and able to evolve as new evidence emerges.

Emotionally powerful narratives can go viral, but if they’re not grounded in truth, they risk spreading misleading ideas. For example, the claim that there would soon be “more plastic than fish in the ocean” captured global attention, but wasn’t accurate. This shows how simple but inaccurate soundbites can drive action but also distort reality. As changemakers, it’s important to balance emotional resonance with scientific integrity. Collaboration between researchers and storytellers is essential to ensure messages are true, simple, and compelling.

Reports and models don’t change systems but people do. So insights need to be translated into clear, engaging formats that influence decision-makers. This means keeping reports as short as possible, using visuals, and breaking complex ideas into digestible pieces.