Designing strategic data visualizations (SDVs) for more effective global health decision-making

Global health policymakers, donors, and other stakeholders are navigating difficult, uncharted waters as compounding crises—from sudden funding cuts to new health threats posed by climate change to geopolitical instability—threaten to erase hard-won gains and leave the world more vulnerable to preventable illnesses and inequitable access to healthcare. Health systems are still recovering from the COVID-19 pandemic, and with the global health AI revolution in full-swing, decision makers must distinguish efficient use cases of new technologies and innovations from those that create redundancies or contribute to unethical health delivery.

Global health stakeholders collect and analyze data to better understand emerging challenges and where global health investments are most impactful. When that data is available and accessible to key decision makers at global, national, and subnational levels, they are better able to:

Detect problems early – Reliable data reveals disease outbreaks, inequities in care, or resource shortages before they escalate.

Allocate resources effectively – Health budgets are limited; data helps target interventions where they’ll have the greatest impact.

Measure progress – Accurate information shows whether programs are working, where they’re falling short, and how to adapt.

Build trust and accountability – Transparent, evidence-based decisions strengthen public confidence and donor support.

Drive innovation – Data uncovers patterns and needs that can inspire new treatments, policies, and delivery models.

However, a significant portion of that data is left out of the decision-making process – this is known as the knowledge-to-policy gap.

Key Decision-Making Tool: Strategic Data Visualizations

At Cognition, we are health communicators, designers and strategists. We support premier global health organizations by developing strategic data visualizations (SDV) that help translate complex information into clear, visual stories, allowing decision makers to synthesize insights and efficiently make decisions to improve healthcare.

We follow three core pillars of practice to develop effective SDV:

1. Embrace data complexity, not visual complexity

Ensure that you do not imply meaning with your visuals. Crystalizing your top findings and incorporating them in callout boxes or captions helps an audience quickly identify your intended takeaway message. It also reduces the time your audience views your visual, calculating or making connections between axes or numbers.

2. Design for and with the audience

When designing visuals in the field of global health, we consider the variety of stakeholders (i.e., donors, policymakers, healthcare workers, hospitals/clinics, civil society organizations, etc.) who are likely to utilize your data. Leticia Ange Pozza contends that understanding your audience(s) is an exercise in prioritizing data accessibility. If the analysis, format, or media associated with the data is inaccessible, the audience may disengage entirely from the subject.

3. Create clear, compelling visuals to reduce decision-making inertia

Our third pillar is related to decision-making inertia which can be defined as delays in decision-making. A complex visual (see Pillar #1 above) can lead to cognitive overload in a busy decision maker. Decision makers may be overwhelmed by disharmonious colors or designs that do little to reorient the stakeholder to the decision at hand. This overload can lead to decision-making delays.

Researchers who studied climate change visualizations found that color, hand-drawn visuals, animation, and interactivity induced feelings of joy and satisfaction in data interpreters, despite upsetting insights related to climate change. Developing engaging visuals in global health is meant to enable global health decision makers to act on complex data, not become encumbered by it.

Agility in a Changing Data Landscape

Amid increasingly complex global health and data landscapes, global health practitioners will find knowledge translation tools such as SDVs more critical due to 1) retained data nuance, 2) audience specificity, and 3) visual appeal which help close the gaps between data and policy action, and result in more efficient global health decision-making.

If you are ready to translate your data into effective visuals and improve health outcomes globally, contact us here.