In the age of data, business dashboards should be designed using data storytellingtechniques . Data storytelling converts metrics into clear narratives that guide the reader to actionable conclusions.
According to this technique, a dashboard is not just about displaying data in a visually appealing way, but about structuring the information in such a way that decision makers and business professionals can quickly understand what is happening, why it is happening and what actions to take about it.
Awell narrated dashboard turns data into insights. By integrating storytelling techniques into a dashboard, we make the audience remember the information better and connect emotionally with it.
In this article we exploit data storytelling techniques and best practices to take your dashboards from informing to inspiring decisions.
Data storytelling is a technique that transforms dashboards into visual narratives that explain what is happening, why it is happening and what decisions to make. It combines data visualization, context and narrative structure to facilitate data-driven decision making.
In a more theoretical sense, data storytelling is the art of constructing a compelling narrative from complex information, relying on data visualization to communicate a message to a given audience.
In the context of dashboards, it involves designing interactive dashboards that tell a story: each visualization should support a key point and all together should take the reader through a logical path, from a contextual introduction to an actionable conclusion.
A well-constructed dashboard not only represents information, it tells a story andconveys a meaningful message. At the end of the journey, the reader should understand what is going on and be inspired to make an informed decision based on data.
It is important to distinguish data storytelling from other analytics functionality such as question and answer (QA) systems or AI-based wizards like Microsoft Copilot or the older Power BI Q&A.
These tools allow you to ask questions directly to the dashboard-for example, "Why were sales down in April?"-and get an automatically generated answer in natural language. While useful for ad-hoc exploration of data, they are no substitute for a well-constructed visual narrative.
A storytelling dashboard doesn't wait for the user to ask: it anticipates key questions and guides logically and visually to relevant insights.
While QA answers specific questions, data storytelling creates a coherent story right from the start: it contextualizes, simplifies and highlights what is important so that the user understands what is happening, why and what to do about it, without the need to interact.
Both approaches are complementary, but serve different functions. If you combine a powerful narrative design with interactive tools like Copilot, you will be maximizing the impact of your dashboards.
In most organizations there is a gap between the abundance of data and the ability to make decisions with it.
Often, we have so many reports and metrics that we fall into the "data overload paradox" where, ironically, information overload leads to inaction.
Storytelling with data acts as a bridge to bridge that gap, structuring data into a logical and persuasive narrative that makes it easier to interpret patterns, gain insights and, above all, implement concrete actions.
In addition, telling stories with data helps to distill and simplify complex information.
Good data storytelling simplifies the complicated so that the audience can assimilate it and make decisions more quickly and confidently. It also adds a "human touch" to the numbers: contextualizing the numbers with stories or examples gives them relevance and creates connection.
In fact, it is proven that people remember data better when it is part of an immersive narrative, rather than presented as isolated statistics ("Made to Stick" - Chip Heath & Dan Heath).
An effective dashboard narrative does not emerge by chance. It requires deliberately applying principles of visual design, data communication and data-driven analytics to make data-driven decisions.
Here are the key data-driven storytelling techniques that will enable you to transform your reports into interactive dashboards that drive data-driven business decisions.
Every story starts with two key elements: what you want to tell and to whom. Before designing a dashboard, ask yourself:
Without a defined objective, we run the risk of building a generic report that does not solve any specific need.
Having a clear narrative objective will allow you to focus the dashboard on the really relevant data, avoiding information overload.
Practical tip: write a short sentence that summarizes the purpose of the dashboard, as if it were your "headline". This will help you keep the focus throughout the design.
Each professional profile interprets data differently. It is not the same to design a dashboard for a CEO than for a marketing team, as they will have different needs.
When designing a dashboard, we must adapt the complexity, language and visualization format to the profile of the audience.
💡 Don't miss: Types of Dashboards According to Audience
Focus on answering your audience's real questions:
Are we doing well or poorly? Why is this happening? What action should I take?
One of the most powerful data storytelling techniques is to apply the classic narrative structure to data visualization.
An effective dashboard is not a group of isolated graphs, but a story with a beginning, middle and end. This organization makes it easy for decision makers to follow the thread and extract actionable insights effortlessly.
Start the dashboard with an overview that situates the reader. Use KPIs or a highlight card with the main data.
Example: an "Annual sales vs. target" card on a financial dashboard allows you to quickly understand the overall status (above or below target?).
This is where you break down the information. Add visualizations that show trends, comparisons and segmentations that explain the causes behind the initial data.
Example: graphs by region, product line or time periods that show what factors are driving - or holding back - results.
Close with a key insight or recommendation. It can be a summary graphic, a final indicator or a text that makes the main message clear.
Example: a "Year-over-year cumulative growth" indicator along with a note: "Exceeded target thanks to Q3 performance".
This narrative structure turns the dashboard into a coherent visual story. Each visualization should have a clear purpose within the narrative. Avoid logical jumps and arrange the information in a way that answers the user's questions:
What's happening, why, and now what do we do?
Isolated data can be misleading. Be sure to accompany each visualization with the necessary information to interpret it: units, dates, goals, historical evolution or relevant segmentation.
Example: don't just show "Total sales Q2", but "Sales Q2 2025 (€) vs. annual target".
Remember: an effective dashboard answers from the first glance the question "is this good or bad?"
✔ "Sales Q1 2025 (in million €)"
✘ "Sales"
"+10% vs. previous year" provides much more than a raw number.
"Demand fell in March due to supply issues."
Take advantage of functionalities such as tooltips or pop-up boxes to provide additional details without cluttering the visualization.
This is especially useful for corporate or executive dashboards, such as the balanced scorecard, where clear, quick-to-consume information is valued.
One of the pillars of effective data storytelling is simplicity. In data visualization, less is more: showing only relevant information helps the key message stand out without noise or distractions.
A clean, focused dashboard is much more effective than one overloaded with visualizations. Each additional graphic or metric competes for the reader's attention. If you present too many elements, you risk creating confusion, slowing down interpretation and diluting key insights.
"What decision would be made differently with this data?"
If the answer is none, consider removing it from the main dashboard.
💡 Less does not mean incomplete. It means focusing content on what really matters to the target audience and the desired action. By cleaning up the information, your data-driven story will be clearer, more memorable and more useful for decision making.
One of the golden rules of storytelling with data is that not all data has the same weight. A fundamental part of effective dashboard design is to guide the user's attention to the most important insights.
Example: 14.089.323,98 € → show as 14,1 M€ and leave the detail in a tooltip.
💡 Expert tip: Incorporate explanatory labels or comments within the graph so that the reader immediately understands the highlight.
For example:
"Summer promotion here → sales peak."
These notes function as the "voice of the narrator" within the dashboard and reinforce the visual narrative.
Objective: get the dashboard to speak for itself, without the need for external explanations. When you visually highlight what's important and provide immediate context, your data-driven story becomes clear, understandable and memorable.
It is important not to assume that the reader will correctly interpret each graphic. Add brief text within or next to the visuals to explain the message when necessary.
Example: an annotation such as "Here begins the summer campaign → sales increase".
These micro-narratives act as the narrator's voice within the dashboard and reinforce understanding without the need for external explanations.
Visual design in data storytelling is not decoration: it is part of the message. A poorly executed design can distract, confuse or even lead to erroneous interpretations of the data. On the other hand, a coherent and clear design reinforces the visual narrative and the understanding of key insights.
Key tip: maintain consistency in scales, colors and order between similar visuals. This prevents the reader from having to "recalibrate" their attention on each graphic.
A good design is invisible: it does not distract, does not saturate, does not complicate.
Apply basic visual design principles (alignment, spacing, hierarchy, contrast) to build a clear, professional and story-focused scorecard.
When design accompanies content, your dashboards don't just look good: they communicate better and facilitate data-driven decision making.
Business intelligence tools such as Power BI, Tableau or Qlik allow you to build interactive dashboards with filters, segmentation and dynamic navigation. This interactivity brings a lot of value to explore data, but only if it is used with narrative criteria.
The goal of data storytelling remains the same: to allow the user to go deeper where needed without breaking the thread of the main story.
Functionalities such as bookmarks and navigation buttons allow the design of interactive paths controlled by the report creator.
For example, a "View Q2 analysis" button can take the user directly to that quarter's breakdown, saving them from having to search for the information on their own.
When the user applies filters or explores specific segments (by region, channel, product, etc.), it is critical that the main message remains clear. Some best practices to achieve this:
A well-narrated interactive dashboard allows you to explore multiple angles of the business without losing the big picture. The visual narrative should guide the user through the key questions: What is happening, why is it happening, what decision should we make?
A good dashboard guides the user like a story with chapters. It organizes the information in a hierarchical and sequential way:
In Power BI, for example, you can implement this narrative with chained pages that work as a step-by-step story. Accompany each view with informative titles, and if possible, add a navigation menu or visual indicator that helps the user to orient himself within the path.
Storytelling with data must speak the language of your organization. The narrative will be much more effective if it respects the culture and structure of your company.
The more familiar the dashboard is to the user, the more easily they will interpret it and the more likely they will act accordingly.
In short: tell the story of your data using the language of your business, not the analyst's language.
A common mistake is to design dashboards thinking only of the creator. Remember that the dashboard is made for others: business managers, middle management or operational teams.
What to validate:
Validation will help you detect:
Itera based on your feedback. Validating the narrative with the target audience is the best way to ensure that your storytelling with data works and generates real impact.
At Bismart we apply a structured methodology to create dashboards that combine storytelling with data and technical excellence. Each dashboard we design follows a set of key principles and a collaborative process that ensures both the usefulness and quality of the report.
1. User-centered design
The report is built with the user in mind: an executive who needs a quick overview is not the same as an analyst who requires more detail. The experience is tailored to the user's profile and real questions.
2. Less is more (visual minimalism)
We only show what is necessary. We avoid overloading with distracting graphics, colors, icons or text. An effective dashboard conveys a lot with little.
3. Context and explanation
Each visualization is accompanied by a clear title, a brief description or a useful tooltip. The goal is for anyone to understand the data and its relevance without ambiguity.
4. Visual consistency
Colors, fonts, sizes and formats are kept consistent throughout the report. This facilitates reading, reinforces the visual identity and avoids interpretation errors.
5. Clarity and purpose
Each graphic should answer a question or show a clear insight. No "just in case" visualizations are included. Everything that appears has a reason.
6. Intuitive interactivity
Filters, buttons, navigation between pages... everything should be easy to use and guide the user through a smooth experience. Interactivity should help, not complicate.
7. Optimal performance
A useful dashboard is one that opens quickly and responds smoothly. Technical optimization is also part of good storytelling with data.
In conclusion, applying data storytellingtechniques to effective data visualization can make the difference between a forgettable dashboard and an effective executive report that drives action. We have seen how to define a clear objective, structure the narrative, simplify and highlight what is important, provide context, take care of the visual design and take advantage of the interactivity of tools such as Power BI, all added together, transforms the way we present data.
A dashboard with a data narrative not only answers "what is happening", but also "why is it happening" and "what should we do about it", thus answering the key questions that every decision maker has.
If you avoid common mistakes and follow these business storytelling best practices, you will be on your way to creating dashboards that truly turn data into decisions.
Applying these principles will allow you to significantly improve the effectiveness of your dashboards. Start working today on a clearer, more understandable and decision-oriented presentation of data. Turn your data into a story.