Data Storytelling

Data Storytelling: What It Is And Why Data Leaders Should Adopt It

Traditionally data scientists have used visually-appealing dashboards and visualizations to communicate their findings to business executives. But today many have realized that it is only by wrapping these visual artifacts into a powerful data story and narrative that they can influence business stakeholders to take action. 

And data storytelling helps data science leaders achieve it. 

Data storytelling augments visualizations into a compelling narrative and focuses on 

  • Giving credibility to the analysis done, 

  • Generating confidence in the results 

  • Ensuring the findings resonate with the target business executives. 

  • Providing an actionable set of insights

The Need For Data Storytelling

With the democratization of analytics and business intelligence tools, self-service capabilities in these technologies are gaining ground and the people generating insights is no more limited to analysts and data scientists. However, it needs an effective communication to convey these insights, without which the insights by themselves do not hold any value. Insights can’t produce actions and changes if they fail to be compelling and comprehensive. This is where data storytelling plays a pivotal role ‒ to derive actionable value out of insights and drive impactful decisions. 

What Does Data Storytelling Comprise of?

Data storytelling is often misunderstood as just using visualizations effectively, while there’s more to it than just visually-appealing charts. Data storytelling is in fact a structured approach to convey insights with the amalgamation of data, visuals and narrative. 

Coupling narrative with data allows data storytellers to convey the underpinnings of data and establish the importance of a particular insight. Context and commentary are essential elements to enable the audience to fully appreciate the insights.

Visualizations reveal the underlying patterns and outliers in data and are necessary to aid the audience in understanding specific insights which would otherwise remain hidden in the rows and columns of data tables.

Combining the right narrative and visuals with data can provide the audience with a highly engaging experience and render a compelling data story that can have a lasting influence and drive changes.

Guidelines For Data Storytelling

1. Apply storytelling rules

Data storytelling is a lot like narrating any other enrapturing story. The storytelling norms are applicable to data as well and requires it to have a beginning, a middle, and an end. Data Story should also include a premise, supporting facts (data), a coherent structure and an engrossing presentation. It is also essential to use a creative approach to convey the usefulness of data in business and not disportionately invest time on just the technical aspects behind data. 

Although visualizations are indispensable, the human touch of storytelling to establish context, articulate insights and opportunities and interpret results is pivotal to influence the decision makers and drive strategic decisions. A good data story, like any other general engaging story should achieve its desired objective – it can be changing an opinion, rationalizing a course of action, encouraging more exploration or evoking an emotion.

2. Know your audience

To make data storytelling a time-efficient process, it is essential to understand the audience and fabricate complex data into a meaningful, comprehensive and compelling story that can drive strategic decisions and create a lasting impression. Data story without a strong connection to business outcomes will not be actionable despite being informative.

3. Collaborate with teams for a good story

Powerful data storytelling needs a collaborative cross-functional team. While data scientists extract patterns in the data, experts in visualization can convey the meaning of data in a simplified manner. Data storytelling should also include marketing experts who are adept in understanding the needs of the desired target audience and how to convince them.

People with business domain experience can help data storytellers in addressing the right set of questions. Having an editorial staff onboard is useful to design communication in a captivating way. It needs the collaboration of experts from various domains to create a great data story.

4. Staying away from distractors

Data stories should be corroborated with findings that strengthen the claims and omit the details that do not pertain to the story or support its goal. Doing this produces a clear and an impactful story without giving room to distractions that can be distracting  to the audience. A pitfall in an ineffective data story is spending an excessive amount of time explaining the analysis of data. It is important to get to the point soon and keep the story concise.

Conclusion

The motto of data storytelling is to communicate and explain the insights in a way that inspires action and change.  Facts and figures by their own do not have the capacity to influence decisions or drive action, well-crafted data stories however can achieve the intended effect. Building compelling data narratives requires data storytellers to use their creativity and contextual understanding. Data storytellers will have a crucial role in building data-driven cultures in the years to come. 

If you’d like to learn more about this topic, please feel free to get in touch with one of our data and analytics consultants for a personalized consultation. You might also be interested in exploring our business intelligence and analytics solutions for further insights.

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