From Stories to Data and Back Again: Why do we need to tell the stories of our data?

The dream of purely objective, data-driven decisions may be alluring, but the reality is more nuanced. Vast amounts of data in federal databases, whether from surveys, records, or health reports, stem from someone's lived experience. These experiences are translated into ones and zeros, and skillful analysis can transform them back into meaningful evidence. However, there is power in weaving these numbers back into narratives – stories that resonate with the human heart. By telling the stories of our data, we unlock its true potential by sharing the context.

Crucially, using stories alongside data does not negate the value of the analysis used in data-driven decision-making, nor does it diminish the accuracy or quality. Narratives enhance the translation of data and evidence, making them more accessible and impactful in improving policy outcomes, reducing bias, increasing transparency, and fulfilling other vital roles in evidence-informed decision-making. Personal experiences are a form of evidence, and data often represents snapshots of the lives and scenarios in analyses. How do we bridge the gap between the logic of data analysis and the human experience? We tell stories.

The AirKeepers Initiative-An Example of Narrative in Action
In a Data Foundation-published use case on air quality monitoring by citizen scientists, the benefits of telling the data’s story are highlighted. Charlotte's Historic West End, concerned about high chronic disease rates, partnered with Clean Air Carolina to launch the "AirKeepers" initiative. Using low-cost sensors, residents collected hyperlocal air quality data not available from existing monitors. This citizen science effort yielded granular insights, empowering the community to advocate for improved policies and secure an EPA air monitor. By engaging residents in data collection, AirKeepers enriched quantitative data with local perspectives, taking action for cleaner air.

Here are a few reasons why telling the stories behind the data is impactful, with examples from the AirKeeper Use case to illustrate the points:

Making Data Meaningful: Stories can overcome dense jargon and dry graphs to contextualize what the data measured. These personal narratives can humanize data and tie them back into the audience’s own experiences. When the impact on real people in real situations is presented, numbers resonate.

  • The West End residents put a human face on air pollution data by sharing how poor air quality personally impacted their lives and health. This brought the numbers to life.


Understanding the “How” of Evidence Use: Policymaking is not always linear, it can be messy. It involves competing priorities, political realities, plus the intuition and “gut feelings” of those involved. Stories can show how evidence is used to shape decisions. 

  • The residents' firsthand accounts showed how they actually used the granular air quality data in advocating for new policies and an EPA monitor in their neighborhood.


Engaging Diverse Audiences: Stories can transform data and evidence into captivating narratives, which may engage policymakers, researchers, and the public.

  • Compelling stories from West End community members helped garner support from policymakers, researchers, and the broader Charlotte community.

An Opportunity for Nuance: Any data can be misused, and manipulated, they can be used to support particular agendas or to fuel distrust. By reading or listening to the stories of diverse viewpoints, this bias can be challenged. Stories offer the context that is required to help reveal the nuanced truth beyond simplistic classifications.

  • The residents' stories added nuance to regulatory air quality data that had overlooked pollution spikes in their area. Their perspective challenged simplistic interpretations.

On February 22nd, the Data Foundation will be presenting Storytelling with Data, a webinar highlighting a number of use cases that they have collected over the past two years around public health data. The speakers, who have written the use cases, will highlight some of the benefits of storytelling with real-world examples. 

By encouraging federal agencies to tell the stories about their data, and policymakers to engage with those stories as evidence, we don’t diminish the importance of quantitative data. We support its enrichment. Stories add texture, depth, and ultimately a human connection that supports good policymaking. Stories accomplish this by combining quality data with the context to better convey meaning. Because, at the end of the day, behind every data point is a human story waiting to be told.

Author: CHRISTOPHER MURRELL is a manager for evidence and evaluation capacity at the Data Foundation.