“The data speaks for itself” is a phrase you may have heard before. However, it raises the question: “Does it really?”. Numbers alone often fail to convey meaning effectively and yet we use them in our lives every day as a system that we ourselves have created. In contrast, something that has come natural to us humans since the beginning of time is telling stories - whether through song or by cave paintings. It’s a powerful device that anyone unconsciously uses to engage others and make sense of the world around us. If only there was a way to combine the best of both worlds in order to convey meaning, right? Good news - there is. Let us introduce you to data storytelling.
What is data storytelling?
Data storytelling is a powerful technique that combines the art of narrative (storytelling) with the science of data analysis. It is described as the practice of combining data and narrative to create meaningful insights. At it’s core, it’s about simplifying complexity and making information more digestible and easier to understand. Data storytelling serves as a bridge between raw data and informed decision-making in that it transforms complex analyses into understandable terms that can be used to make informed business decisions.
The power of data storytelling
The power of data storytelling lies in its ability to provide context and interpretation. As Tom Davenport, professor of information technology and management at Babson College in Wellesley, Mass., said in an interview with Deloitte Insights:
“Narrative is the way we simplify and make sense of a complex world. It supplies context, insight, interpretation -- all the things that make data meaningful and analytics more relevant and interesting.”
An important aspect of data storytelling is its focus on past events to inform future actions. Can you see the connection to your corporate communication? As an organisation, you want your target audience to understand your message. Stories can evoke an emotional response that moves a reader into action. Hence, data storytelling is proven to be a particularly useful method for communicating important business insights to shareholders and stakeholders. Sending out a corporate report containing just the numbers in a PDF file simply isn’t going to cut it. By leveraging data storytelling, your organisation goes beyond the mere presentation of data by analysing and uncovering the story underneath. The result often relates back to your vision, efforts and supports the organisation’s overarching narrative - making it much more accessible to the audience you want to reach.
What is the difference between data storytelling and data visualisation?
Perhaps you hadn’t heard of ‘data storytelling’ yet, but maybe you have heard of 'data visualisation'. When talking about one, we’re also often talking about the other - and they’re sometimes used interchangeably. However, while data storytelling and data visualisation are closely related, they’re very distinct concepts. Let’s clear up any confusion by exploring what makes them distinct:
Data storytelling is about creating a compelling narrative around data. It involves:
- Identifying the underlying story in your data
- Evoking an emotional response in your audience through storytelling
- Explaining and simplifying data for non-data analysts
Data visualisation focuses on the visual representation of data and nothing more. It includes:
- Transforming data into understandable visuals, such as graphs, charts, maps, and animations
- Making complex data understandable at a glance
- Enhancing the reading experience by making datasets more compact
Seeing both concepts side-by-side, we can identify the differences. Data visualisation complements data storytelling by providing intuitive visualisations of data, while data storytelling gives meaning and context to the visualisations. One can exist without the other, but together, they create a powerful method for communicating insights and making data more impactful.
What makes data storytelling so effective?
What would you rather read: a document with extensive charts, graphs and models that requires you to draw your own conclusions? Or a linear story in a visually pleasing format that is supported by data to emphasises notable results and provides context? It’s safe to say that the majority would prefer the latter. There are several factors working together to make data storytelling such an effective method. We have identified the following:
- Humanising data: Data storytelling adds a human touch to raw numbers, making complex information relatable and understandable for the layman.
- Improving communication: By leveraging narrative techniques, data storytelling creates an emotional connection with the audience. A good story gives your company more “personality”, allowing people to sympathise.
- Building credibility and transparency: Transparency and authenticity are being valued increasingly nowadays. Making sure to present your story in such ways will reward you with credibility among your readers.
- Simplifying complex information: One of the key advantages of data storytelling is its ability to present complex data in a digestible, easy-to-understand format. This makes it particularly valuable for readers who may not be experienced in interpreting large datasets.
- Appeals to different audience types: Data storytelling combines the best of both worlds - hard facts for those who are data-driven, and emotional narratives for those who are moved by stories. This approach ensures that your message resonates with almost anyone.
Data storytelling is effective, because it is about much more than just presenting numbers. It's about crafting narratives that inform, engage, and inspire, and align with your organisation. Additionally, pursuing transparency will provide your stakeholders to make well-informed decisions.
Examples of data storytelling done right
Additionally, a story can take on many forms depending on your target audience. Let’s take a look at some examples where data storytelling was applied well for various audiences with different intentions.
Interactive corporate reporting
Anyone that works in a corporate environment knows that collecting data is crucial - especially if you are expected to communicate business operations to shareholders. One of the most effective ways to present data stories related to your organisation is through interactive reporting. Its web-based format provides you with the flexibility of using interactive data visualisations as well as elements suitable for storytelling, such as multimedia, animations and (long-form) text. In contrast to static PDFs, it allows readers to engage with the data in a meaningful way. To provide an example, our recent CSRD report mock-up demonstrates how to creatively blend data with visual narrative and a design that represents your brand.
Data stories with an educative undertone
The Pudding's "30 Years of American Anxieties" is a great example of data storytelling that was applied to educate the reader. It uses data from 20,000 letters to an advice columnist to tell a story about societal concerns, supporting the article with data visualisations. Formats like these are highly suitable for more educational purposes as it reads like a story but has a clear intent to inform the reader.
Data storytelling as art
Jonathan J. Harris's work demonstrates how data can be made meaningful by transforming it into art. Creating visually stunning as well as thought-provoking representations based on numbers that provide a powerful message. Take a look at this example of a portrait of the psychological effects of large-scale internet use on humanity. You could argue that such an art piece ventures into the real of ‘immersive experiences’.
Tips on how to get started with data storytelling
Data storytelling is a skill and takes practice to master. Everyone can get started with data storytelling, though getting it right is key. Whether you’re new or experienced, here are some of our tips to make your next data story a success:
- Start with a clear purpose: A story is told to convey a message. What message you’re trying to communicate to your audience is something you ought to have thought about beforehand. Usually takes the shape of a hypothesis - something you’re trying to prove or disprove.
- Always remain objective: When talking about facts, bias should be avoided at all costs. That means you should not selectively choosing only data that supports your hypothesis.
- Build a strong narrative: A good story can persuade anyone. Storytelling is a skill on its own, so make sure to use narrative devices cleverly to make your audience understand your message.
- Data support your story: If your story is the “hero”, your data is a “sidekick”. It should act as a support without outshining the main topic at hand.
- Use visuals effectively: Visuals are great at conveying meaning at a glance. Use them to educate and improve the reading experience.
- Focus on one key point per visual: Highlight the most important information in each visualisation. Multiple highlights may cause distractions from the main point.
- Add interactivity: Additionally, consider making your visuals interactive. Allow readers to hover over numbers for more context and toggle filters for different views. This allows the reader to further shape the narrative in a way that is relevant to them.
- Keep it simple: The whole point of data storytelling is to make matters easily understandable. Data in itself is complex enough for many, so aim to simplify information instead of overcomplicating it. In this case, less is more.
In the end, telling the story is only half the work - and it comes after the main foundation has established. The first step is to uncover which stories hide in your data. Once identified, consider your target audience and hypothesis. Crafting an effective data story is dependent on both the sender and the receiver which means that format and tone of voice matter. Make sure get those basics right before starting to shape your narrative.
The future: data storytelling and AI
The impact of AI on anything is a topic of growing importance, and data storytelling is no exception. Storytelling is defined as something inherently to humans. What would a collaboration with AI look like?
Although, storytelling requires a human touch, AI can be a powerful assistant in spotting key factors in data. Rather than replacing people, AI is likely to enhance our ability to find meaningful data stories. It can uncover multiple stories within a single dataset, providing a broader perspective whereas we might overlook them. This approach combines the strengths of both AI and human creativity. As with any AI application, there's always a risk of algorithmic bias. That is why human monitoring will remain crucial to ensure accurate representation of data. Additionally, the integration of AI might lead to new forms of interactive and personalised data storytelling, potentially changing how we consume and interpret information.
Even if AI can help us uncover hidden data stories, organisations will need to decide which narratives to emphasise and how they align with their best interests. The key to successful data storytelling will likely lie in finding the right balance between AI's analytical power and the uniquely human ability to craft compelling narratives. However, the premise is exciting, as this combination could lead to more engaging stories in (corporate) communication. Whether it's for internal decision-making or external communication, data storytelling is becoming an indispensable tool in our increasingly digital world.
Looking for inspirational data storytelling examples for 2025 - or want to create your own? Be sure to check out our interactive examples.
