Data Storytelling

Presenting complex data in an easy-to-understand format

What is data storytelling?

Data storytelling uses visual elements such as charts and graphs, along with a clearly structured narrative, to present data in a vivid way so that a message or a specific finding can be conveyed. This type of presentation makes it easier for the audience to understand the information and remember it better afterward. Data storytelling can be used in many areas, such as for business decisions, in project management, or for presentations.

How does Data Storytelling work?

Data storytelling works by presenting data in a way that makes it understandable, emotionally engaging, and interesting to the audience. The following steps can help you create your data story:

1. Identify the goal of the story:

Every story should have a clearly defined goal. So ask yourself what you want to convey with your story. What do you want the audience to feel after hearing the story? What impact do you want the story to have?

2. Collect all relevant data:

Make sure you have all the data you need to tell your story. To do this, put yourself in your target audience’s shoes and think carefully about what data is needed. Also, be sure to present the data in the right context—for example, by providing comparative figures. At the same time, you should take care at this stage not to select too much data, so that your data story doesn’t become overloaded.

3. Prepare the data:

Clean and format your data so that it is ready for further analysis and presentation. Also, make sure the data quality is high—that is, the data should be complete, up-to-date, and accurate. Therefore, check the data for errors, inconsistencies, or duplicates.

4. Visual representation:

A picture is worth a thousand words. So create charts, graphs, maps, and other visual elements to present your data and reinforce your message. Not sure which visualization is right for your data? Then check out the article “How to Design an Optimal Dashboard” to learn how to make the best choice. You can also read there about how to optimize information perception through a dashboard—for example, by adjusting the position, size, or orientation of the graphics. Be sure to label the data clearly; for instance, the axes in a chart should be labeled.

5. Structure:

Create a clear and logical narrative structure that allows the audience to quickly understand the data and its significance. To do this, you should organize the data logically while presenting it as simply as possible.

6. Interactivity and presentation:

Present your story in a way that encourages audience interaction. Use tools such as dashboards or presentation software to capture your audience’s attention. Interactive elements can add value for your audience; for example, drilldowns allow you to show a detailed view of the data, while filters let you focus on a specific subset of the data.

7. Feedback:

Let the audience comment on your story and give feedback. You can use this in the future to improve your techniques and the way you tell stories.

How do you write a good data story?

The structure of a data story usually consists of three parts—an introduction that poses the central question, a main body that explains the data and its analysis, and a conclusion.

1. A research question or problem:

A data story begins with a question or a problem that needs to be investigated or solved. This can also include the context of the analysis, the nature of the data, the methods used, or any challenges encountered. Start by explaining the initial situation—for example, which metrics are being examined and why they are important for business success or your fundamental goal.

2. Main Body:

The main body of your story serves to answer the initial question using the data you’ve collected. In your data story, the data thus serves, on the one hand, as the protagonists and, on the other hand, as the framework for the plot. To make it easier to understand and to reinforce your message, this data can be presented visually.
A well-structured narrative or presentation helps the audience easily understand and follow the information. There are various storytelling options available to you for this purpose:

• Drilldown: In a drill down, you go from general data to more specific, usually more detailed data.
• Zoom out: Here you proceed in the opposite way to the drilldown and first show specific data before moving on to more general data.
• Change over time: Here you explain how the data has changed over a period of time.
• Contrast: If you have chosen two or more protagonists, you can compare them.
• Intersection: In this narrative variant, you work out at which point your data protagonists intersect.
• Outliers: Here the focus of the narrative is on outliers within your data.
• Factors: With this narrative perspective, you illustrate how different data sets are related to one another, or what causal relationships exist between them.
  When writing your data story, be sure to appeal to your audience on an emotional level to encourage them to identify more strongly with your message. To do this, you can make parts of your story interactive, allowing the audience to explore the information in different ways.

3. Conclusion and Recommendation:

A good data story ends with a conclusion based on the data and its analysis, as well as concrete recommendations for future actions.

What makes a good data story?

A good data story is characterized by a combination of facts, logic, and emotion. The following factors can help you create a good data story:

• Clearly defined goal: A good data story has a clearly defined goal it wants to achieve and ensures that the audience understands it and focuses on this goal.
• Relevant data: A good data story uses only the data that is relevant to the goal of the story and presents it in a way that the audience can understand.
• Logical narrative structure: A good data story has a logical and well-structured narrative that allows the audience to easily understand and follow the information.
• Visual presentation: A good data story uses visual elements such as charts, graphs and maps to present the data and support the message.
• Emotional appeal: A good data story has emotional appeal by engaging the audience emotionally and making them identify more strongly with the message.
• Interactivity: A good data story is interactive and allows the audience to explore and interact with the information in different ways.
• Timeliness and consistency: A good data story is up-to-date and the data used is consistent as well as not outdated.
• Ethics: At the same time, a good data story respects ethical aspects such as data protection and privacy and ensures that no improper conclusions are drawn.

The advantages of Data Storytelling

• Clarity: Data storytelling presents data in a way that makes it understandable and easily accessible to the audience. This allows valuable insights to be gained and shared.
• Emotional appeal: By telling a story, you can engage the audience emotionally and get them to identify more strongly with the message.
• Increased memorability: A well-told story is easier to remember than mere facts and figures.
• Support for Decision-Making: Data storytelling can help with decision-making by providing clear and easy-to-understand information. For example, it can help keep discussions highly focused.
• Better collaboration: By teaching data experts to speak the language of other stakeholders in the company, collaboration can be optimised.

The challenges of Data Storytelling

• Time-consuming: Data storytelling can be very time-consuming, especially when it comes to preparing the data and packaging it into a story.
• Subjective: There is a risk that the data will be interpreted subjectively, depending on how the story is told and who is telling it.
• Distortion of Reality: By highlighting certain data and suppressing others, there is a risk of distorting reality and conveying an incomplete or inaccurate picture. Therefore, when compiling the data narrative, it is important to carefully verify whether the findings are, in fact, correct.
• Too much information: There may be too many visual elements or too much information, which can distract the audience's attention from the most important points. Therefore, it is important to focus only on relevant information.

Conclusion

Data storytelling is a valuable method for presenting data in a vivid way, thereby conveying a clear and compelling message. By using visual elements and a well-structured narrative, the audience can understand the information more easily and remember it better. Data storytelling can thus support you in many areas.
Business intelligence software can help you create and design your data story. Convenient analysis features, various options for visualizing data, and the ability to create your own dashboards and reports make it easier to craft your data story.

Möchten Sie​ myPARM BI^act in einer Demonstration kennenlernen? Dann vereinbaren Sie gleich einen Termin!