Q8 - Main Elements of Storytelling

Q8 - What are the main elements of good data-based storytelling?

Answer to the question:

Storytelling allows communicating ideas with three connected elements: an initial state or context, followed by a challenge or conflict, and an altered state, conclusion, or final reward.

Data stories can follow this principle as well as maintain a focus on reports of changes, such as how and why they happened and what to do.

Data narratives can be told through voice, text, videos, images, animations, or visual elements to make the story captivating.

As they come from data analysis, it is common to use more complex statistical graphs for the audience to understand.

A data story can even be told with PowerPoint in a static way, but in practice, it needs a more complex component, which is data simulations.

The best way to tell data stories using simulations is with Dashboards or interactive digital panels.

Regardless of the environment, at least five elements can be applied to all data stories, which we will see below.

1 - Where to tell the data story

Data visualization software like Tableau includes Dashboards that are digital panels to publish the data story with graphical elements and data simulations.

Tableau Public is a site with a large repository of applications developed using Dashboards.

Model of a Dashboard in Tableau

Digital panels allow organizing the structure of the data story by focusing on the framing and formatting of the data.

Dashboards are exploratory data visualization interfaces used to navigate graphically, showing the analytical possibilities offered by the data story.

They allow telling the data story in separate stages like a timeline represented by frames called Story Points, where in each of them it is possible to present the simulations of data analyses in stages.

Model of data story points in Tableau

At each story point, there is a specific dashboard with simulations allowing interactivity with the data so that the user can draw conclusions and insights from the data.

A data story is like a map with a predetermined route that is clearly marked. The goal is to lead the audience to a specific conclusion or a set of conclusions.

A dashboard or exploratory data visualization interface is similar to a compass that guides the user to navigate these data, seeking the offered insights.

Various data science software and sites use Dashboards, such as EyeData Portugal or Our World in Data from Oxford.

It is advisable to have Digital Literacy to use these panels, extracting data stories from them.

2 - Five elements of data stories

No matter the medium where the data story is told, we recommend using five elements, which are:

1. Trends

2. Classification ranking

3. Comparisons

4. Counterintuitive

5. Relationships

Let's get to know them below.

1 - Trends

Data trends are almost always time-based, occurring over a certain period.

People understand this well because the word trend tells us about something that tends to happen in a certain direction.

Almost always, there is some variable containing time-based data that offers trends.

It is common to use line charts to show trends, such as interest rate rises and falls, increases or decreases in birth rates, etc.

2 - Classification ranking

The second way to tell stories with data is to order or classify them for better understanding.

People understand ordering well because they like to rank things like amounts to be paid, top players, who scored the most points, and so on.

For example, in a bar chart, you want to draw attention to who sold the most over a period, but the bars are scrambled. By classifying, you can visually identify who sold the most or who sold the least at a glance.

3 - Comparisons

The third way to tell stories with data is to use comparisons.

People understand facts when we use comparisons, for example, I can compare the two main presidential candidates regarding age, projects, family, political experience, among others.

These comparisons can show trends such as focus in a certain area or activity translated into better achievements in politics.

They will show comparatively which of the two candidates is better prepared to take on the future role.

4 - Counterintuitive

The fourth way to tell stories with data is counterintuitive visualization, where outliers or "outliers" appear.

An outlier is an element that stands out from the others in a grotesque way and draws attention.

It becomes discrepant from the rest, attracts attention, and raises suspicions because it may be inconsistent, improbable, and lead to errors. It may be correct, but still attracts attention.

For example, in a class of 5 students, 4 scored 8 and another scored 1 (one). The class average was 6.6.

The final average pulled the class average down, giving the impression that the class did not do well on the test, which is not true.

Since outliers attract attention, they can be used in data stories as an important element to captivate the interlocutor.

5 - Relationships

Another way to tell data stories is through relationships between variables and data.

For example, there may be a direct relationship between sales and profits, in the sense that when sales increase, profits also increase.

Or conversely, sales increase, but profit does not grow in the same proportion, posing greater risks to the business.

Drawing attention to the relationship between variables and values can bring new alternatives to include in data narratives.