Whether you're new to data or a seasoned expert, we'll explore how you can use powerful narratives to make your next data story even better.  

What do cholera, WWII planes, and the world's population all have in common? They are each at the center of data stories that transformed how we view the world.  

It's no secret that good data stories are powerful. And great data stories don't just happen overnight – the art of data storytelling is built by activating data fluency.  

Let's explore how these examples can help you make your next story even better.  

Knowing Your Audience Saves Lives 

Cholera was a serious threat to the people of London in the mid-1800s. Multiple outbreaks had taken countless victims, and without the knowledge of germ theory, the disease was difficult to contain.  

In 1854 an accomplished physician named John Snow interviewed residents in the Soho neighborhood, where a new outbreak was active. He mapped the data he collected about infections and deaths to determine that a specific water pump was a likely source of illness.  View Snow's map of the data he collected here. 

An informational campaign in the area surrounding the pump may have convinced some to stop using it. But when the local council saw this data story, they removed the pump's handle to disable it entirely – a critical action that significantly contained the spread of cholera in Soho.  

When crafting a data story, understand that your audience matters. Tapping into their interests, values, and capacity for action will intensify the impact of your data story.  

Challenging Biases Wins Wars 

In WWII, Allied analysts examined bomber planes to minimize losses from enemy fire. They noted that since most damage was done to the wings and tail, more armor should be added to those areas. But Abraham Wald, a Columbia University researcher, had a different perspective. 

Wald argued that the focus should be on reinforcing the areas with the least damage – the engines and cockpit. His reasoning? The planes they studied were the ones that made it back despite damage to the wings and tail. Planes hit in the engines or cockpit were far less likely to return, leaving those vulnerabilities underrepresented in the analysis. 

Wald's approach challenged survivorship bias, a cognitive error that occurs when conclusions are drawn from only the surviving or successful cases, overlooking those that didn't survive. In this case, most analysts were focusing on the planes that made it back, not considering that the planes with damage to critical areas like the engines or cockpit never returned to be analyzed. 

Survivorship bias is just one of the many types of bias that we need to avoid in data storytelling. So, when working on your next data story, think about where bias may have crept in and work to remove it. Challenge assumptions. Think outside the box. Make sure the insights you're sharing are sound. 

Choosing the Right Visualization Captures the World 

In 2022 the world population passed 8 billion – a staggering figure that's hard to wrap your head around. You're not alone if you find that difficult to conceptualize. But with the right visualization, it becomes much easier to grasp what that really means.  View this example of what that visualization could look like as a visual image here. 

Data visualizations give you the opportunity to bring your data story to life. They can make complicated or complex information easily digestible and actionable. They can captivate and inspire. And they can simply be visually striking. Visualizing your data insights is the key to engagement and impact with your data story.  

Just make sure that you're using the right one for your data and the narrative you want to share.  

Boost Your Data Storytelling 

Whether you're new to data storytelling or a seasoned expert, it's important to remember that there is always room for improvement. Paying attention to the details about your audience, thinking outside the box of bias, and creating a meaningful visualization are just three areas of focus you can leverage – but the foundation for data fluency must be strong. 

Activating data fluency goes beyond storytelling. Think about how your team or organization currently deals with data: collection, quality, storage, storytelling, and even confidence in using it. The quickest and most powerful routes to data fluency activation lie with regular practice, reflection, and collaboration. That means giving people meaningful opportunities to take action based on what they're learning about data. And to reflect on their contributions so future data-driven actions become more likely. And to connect with colleagues as they work with data, so you can benefit from more powerful data-informed ideas. 

By activating data fluency, you and your organization can unlock immeasurable potential. How are you activating data fluency for yourself, or in your organization? We can help.