Data Stories vs. Stories With Data: What's The Difference?

In the field of data storytelling, there’s some confusion if data stories are the same as stories with data. While both leverage data, narrative, and visuals in their communications, they serve entirely different purposes and use distinct approaches. Understanding this difference is essential to mastering the art of data storytelling.

Until recently, I hadn’t delved into these differences, thinking they were minor and insignificant. However, when I was listening to a webinar, one of its speakers criticized the term ‘data stories’ as being too focused on facts and not centered on the narrative. At that moment, I realized more clarification was needed on this subject.

This data professional was criticizing a “data story” for not being a “story with data.” For me, this was like criticizing a spoon for not being a fork. On repeated occasions, I’ve even seen many data experts use broad brush strokes when discussing data storytelling, not realizing they were primarily referring to only one of the two approaches. While many of the best practices are transferrable, it’s still crucial to understand which approach you’re using to be truly effective.

In this blog post, I’d like to shed more light on the critical differences that are often overlooked, especially when both approaches fall under the same umbrella term of “data storytelling.” By distinguishing between these two approaches, I want to enhance how you understand and use them. If you don’t know their distinctions, you won’t able to take advantage of their strengths and mitigate their weaknesses.

I have a hunch: Many people are already using both methods without knowing it, and they may even wonder why they aren’t experiencing similar levels of success. I hope the following analogy is helpful in highlighting their core differences.

Data story – ‘The Sandwich’

In my book, Effective Data Storytelling, I primarily focus on data stories rather than stories with data. I outline a data story’s foundation is based on data—it reveals the story. The narrative and visual elements help explain, enhance, and contextualize the data-driven story, making it accessible, understandable, and engaging.

I compare a data story to a sandwich because the data is essential to the story as its basis or foundation. You don’t have a sandwich if you don't have two slices of bread. Similarly, without the data, you don’t have the ‘bread’ to hold your story together—it is integral to this form of story.

A simple example of a data story would be an analyst sharing an insight into why sales declined last month and what specific action must be done about it. Without the sales insight from the data, the analyst wouldn’t have a meaningful story to share with key stakeholders.

Story with data – ‘The Pizza’

In contrast, a story with data, has its foundation in narrative. With this approach, data plays a supporting role along with other elements in helping strengthen the message or argument. Data is used to support the narrative—it isn’t the focal point of the story. The narrative could exist without the evidence, but data adds credibility and depth to the story.

I compare a story with data to a pizza because the narrative is the base (pie or crust). When data and visuals are layered on top, it can add flavor and nutrition to the story. While these toppings (data) can enhance it, the pizza can still exist without them.

A general example of a story with data is a product manager delivering a presentation about the benefits of a new product with facts to support her claims throughout. The product manager doesn’t need to provide evidence, but the data strengthens her assertions.

To clarify how this approach is different than a data story, I want to share an example related to a hiking trip I made with my wife to the Grand Canyon. I could tell the story of our hiking adventure using photos and personal anecdotes. However, I can also add data examples to expand people’s understanding and appreciation of how challenging the hike was. The data visualizations help complement the story further; however, they come after the narrative was already formed (“what a grueling hike”).

Is one approach superior to the other?

Now that we’ve explored the core differences between these two approaches, the question remains: Is one better? I don’t view one as being better than the other.  They originate from different places and serve unique purposes. However, they offer different strengths and weaknesses based on their primary orientations—data-led versus narrative-led. Let’s explore them from various perspectives:

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From this comparison table, I have three key observations:

1. Stories with data will probably be a more common occurrence because you can insert data into all kinds of narratives. On the other hand, data stories fulfill a more narrow but important role of informing decisions with clear insights.
2. Data stories will be more complex and detailed than stories with data. If you are not careful, you can easily overwhelm your audience with too much information. Combining your data with narrative and visuals effectively is critical to making your insights engaging, memorable, and persuasive.
3. Data stories are about inspiring change and driving specific outcomes with insights. Stories with data could serve many informational purposes, and they may not focus on driving action unless that’s the intent of the narrative.

As a data storyteller, you may switch between the approaches depending on the nature of each data project and what your intended audience needs. In a healthcare environment, you might build a data story based on an analysis of patient outcomes, which revealed a new treatment method that significantly outperformed other options. You may also work with hospital administrators to create a story with data that discusses patient satisfaction supported by survey data.

Fortunately, at the tactical level, they are more similar than dissimilar. Most data storytelling best practices will apply to either of these approaches. For example, clear headlines and selective highlighting can be effective in the visuals for either format.

If you have the opportunity to work on both types, you may notice they require slightly different ‘data storytelling’ muscles. Data stories will demand more analytical rigor to find and communicate insights. They will test your ability to form your findings into a coherent flow based on a narrative structure. On the other hand, stories with data will require more creativity and emotional appeal. They will challenge your capacity to integrate data seamlessly into broader narratives.

In summary, a data story primarily explains an insight, while a story with data uses facts to support a narrative. Both serve valuable purposes, but the main difference lies in what takes center stage: the data or the narrative. The next time you’re working on a critical data communication, evaluate which approach best suits your goals and audience. Understanding when and how to use each method will elevate your data storytelling and help you communicate more effectively.