Essential Elements of Data Storytelling

Data analytics are not enough to motivate an entire team or organisation to utilise and derive value from it. However, a compelling narrative, characters, a setting, a problem, and a solution, may inspire teams to make the most of analytics applications. Here enters data storytelling!

Data storytelling is the art of communicating insights from data analysis in a compelling, easily understandable manner using narratives, visualisations, and other forms of multimedia. 

The goal is to effectively communicate complex data insights to stakeholders in a way that is engaging, persuasive, and memorable. It involves turning data into a story that highlights key insights and conveys a clear message that can drive decision-making.

In this post, we seek to explain why data storytelling is important to build an analytics-driven culture and discuss the crucial aspects of a compelling story. 

business asian presenting analytical report while 2022 09 23 20 17 58 utc scaled

Key elements of data storytelling

1. Plot

A plot is a critical element of data storytelling, arguably the most important. It underlines the structure and sequence of events in a story and helps to organise the data insights into a coherent narrative that leads the audience from the problem to the solution.

It is imperative that you be clear about the questions you want to answer and how you plan to do so in a data story. If you are uncertain or unclear, your findings might not be easily accessible. 

Is the data indicative of causation or correlation? Is it temporally consistent? Are you showcasing historical activity, current findings, or future predictions? 

In order to make your data most accessible to your audience, you must first determine what you will emphasise the most.

2. Narrative

This provides the structure and style for the story. A well-crafted narrative helps to engage the audience and make complex data insights more accessible and memorable. 

It should include clear and concise language, an engaging style, a crisp and structured story format, relatable characters and a clear point of view.

3. Characters

It’s imperative to comprehend the thoughts of your audience in order to convey information effectively. This is because a good story centres around a character the audience sees themselves in.

What is important to them? What is the purpose of the information you are sharing? How will it affect company success? In your quest for answers to these “big picture” questions, you should be equipped with data that is most relevant to them.

4. Conflict

A problem needs to be posed to build the right amount of tension. Your story must have enough tension to make your audience care about its resolution and must contain themes relevant to your audience’s lives. Otherwise, your narrative will have no resonance. 

There must be only one solution to this conflict: the data insights generated from the project or the model that your team uses. The characters must receive some quantifiable benefit from using data insights to solve this problem.

5. Visuals and presenting data

Visuals help to communicate complex data insights in a simple, engaging and memorable way. Key elements such as the appropriate visual representation for the data type, clarity, context, interactivity and consistency ensure effective data presentation. 

This, in turn, helps to turn complex data points into a compelling and memorable story that can drive decision-making and inspire action.

6. Resolution

This element answers the question, “What is the proposed solution?”

Highlighting the resolution can also help to answer questions like ‘How did the characters solve the problem in your story?’, ‘How did this problem get solved?’, ‘What was the impact of this solution on the organisation?’ and, ‘What was the bigger picture?

7. Summarising

Ask your audience if your response to the questions was satisfactory. It is better to focus on the solution than the problem, so provide a quick snapshot of what you learned, what the future plan is, and how you’ll measure success.  

Conclusion

To summarise, storytelling is a critical aspect of data analysis and decision-making. It helps to turn complex data insights into a clear and memorable story that can engage and inspire audiences. 

Elements of Data Storytelling

Photo by Lukas

The essential elements of storytelling, such as plot, narrative, visuals, conflict and resolution, play a crucial role in shaping the data into a compelling story that can drive action. 

Whether you’re a data analyst, marketer, or business leader, understanding and incorporating these vital elements into your data storytelling efforts will help you to communicate insights in a more impactful way.

Reach us at Accord Training for workshops and data visualisation and storytelling and visual analytics.

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