OECD Well-Being Trade-off Navigator

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  OECD Well-Being Trade-off Navigator — Overview filters and KPI summary cards

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  Country-level Life Satisfaction and its relationship with Income per Capita

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  Correlation Heatmap and Life Satisfaction Trends across OECD countries

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  Well-being Dimension Comparison — normalized country metrics (0-100), Employment vs Life Satisfaction, regression insight with R² trend line

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  Data Table

Inspiration

Happiness and prosperity often move together — but not always. I wanted to explore what truly drives well-being across nations: income, jobs, social support, or health? Using the OECD Better Life dataset, I built this project to visualize the trade-offs between key life quality indicators.

What it does

The OECD Well-Being Trade-off Navigator is an interactive Plotly Studio dashboard that helps users:

• Compare Life Satisfaction across OECD countries and years
  
• Examine relationships with Income, Employment, Health, and Environment
  
• Understand correlations between multiple well-being drivers
  
• Explore temporal trends and multi-dimensional comparisons at a glance
  

How we built it

Built entirely in Plotly Studio, leveraging its AI-powered app builder to connect the OECD dataset, design layouts, and generate interactive visuals.
The project includes:

• Dynamic filters for year, country, and key metrics
  
• Linked charts: bar, scatter, correlation heatmap, and trend lines
  
• Grouped bar comparison for normalized well-being dimensions
  
• Regression-based insight view showing employment vs. life satisfaction
  

Challenges we ran into

• Optimizing filters to synchronize all charts dynamically without losing default data display.
  
• Replacing non-responsive radar charts with grouped bar visualizations that preserve clarity.
  
• Designing for both analytical depth and visual simplicity within limited AI credits.
  

Accomplishments that we're proud of

• Created a clean, professional, multi-chart dashboard that runs seamlessly in Plotly Studio.
  
• Showcases real-world analytical storytelling through interactive visualization.
  
• Balances accessibility (no coding) with analytical rigor.
  

What we learned

• How to design for exploratory analysis in a no-code environment.
  
• The value of strong visual structure: small multiples, consistent color themes, and data-linked insights.
  
• That the combination of income, social support, and employment rate consistently predicts higher life satisfaction across countries.

What's next for OECD Well-Being Trade-off Navigator

• Adding AI-generated insight summaries per chart.
  
• Extending the dataset to include subjective well-being trends post-COVID.
  
• Publishing as a reusable template for data literacy and policy-analytics education.

Built With

• oecd