Turn Data into Decisions Using The Power of Data Storytelling

When you hear the term “data analysis,” what do you think of? Your mind may jump to scouring spreadsheets, implementing algorithms, and making mathematical calculations—all “hard skills” of data analysis. Yet, hard skills are useless without their soft-skill counterparts. It’s not enough to just analyze data; you need to know how to communicate the story it tells in a clear, compelling manner—a skill called data storytelling.

When we discover meaningful insights in the data, we expect them to inform better decision-making. Unfortunately, too many insights fail to translate into action. In the very last mile of the analytics process, insights are squandered when they aren’t communicated effectively. To avoid this recurring problem, data storytelling can help make your insights more engaging, persuasive, and memorable.

?WHAT IS DATA STORYTELLING?

Data storytelling is an art and science that blends data visualization, narrative, and contextual analysis to make complex data accessible and engaging. It’s not just about presenting numbers; it’s about weaving those numbers into a narrative that resonates with your audience, driving them toward a specific understanding or action.

?A data story can also be seen as a form of explanatory analysis. Data analysts have their own methodologies for exploring data and identifying insights in the first place. The story comes into play when it’s time to communicate those insights to a decision-maker.

?Why Data Storytelling

?Here's why data storytelling matters:

?Actionable Insights: Facts are great, but stories make them stick. By crafting a compelling narrative, you can convince people to take action on your findings.

Engaging Everyone: Data doesn't have to be dry and technical. Storytelling connects with your audience on an emotional level, making complex information accessible to everyone.

Clear Communication: A well-told data story presents a clear message, leaving no room for confusion. Your audience walks away with an "Aha!" moment and a clear understanding of what's next.

?Components of Data Storytelling

?There are three key components to data storytelling:

Data: Thorough analysis of accurate, complete data serves as the foundation of your data story. Analyzing data using descriptive, diagnostic, predictive, and prescriptive analysis can enable you to understand its full picture.

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Narrative: A verbal or written narrative, also called a storyline, is used to communicate insights gleaned from data, the context surrounding it, and actions you recommend and aim to inspire in your audience.

?Visualizations: Visual representations of your data and narrative can be useful for communicating its story clearly and memorably. These can be charts, graphs, diagrams, pictures, or videos.

Data storytelling can be used internally (for instance, to communicate the need for product improvements based on user data) or externally (for instance, to create a compelling case for buying your product to potential customers).

HOW TO CRAFT A COMPELLING DATA NARRATIVE

Data storytelling uses the same narrative elements as any story you’ve read or heard before: characters, setting, conflict, and resolution.

?To help illustrate this, imagine you’re a data analyst and just discovered your company’s recent decline in sales has been driven by customers of all genders between the ages of 14 and 23. You find that the drop was caused by a viral social media post highlighting your company’s negative impact on the environment, and craft a narrative using the four key story elements:

?Characters: The players and stakeholders include customers between the ages of 14 and 23, environmentally conscious consumers, and your internal team. This doesn’t need to be part of your presentation, but you should define the key players for yourself beforehand.

?Setting: Set the scene by explaining there’s been a recent drop in sales driven by customers of all genders ages 14 to 23. Use data visualization to show the decline across audience types and highlight the largest drop in young users.

?Conflict: Describe the root issue: A viral social media post highlighted your company’s negative impact on the environment and caused tens of thousands of young customers to stop using your product.

Remind the team of your company’s current unsustainable manufacturing practices to clarify why customers stopped purchasing your product. Use visualizations here, too.

?Resolution: Propose your solution. Based on this data, you present a long-term goal to pivot to sustainable manufacturing practices. You also center marketing and public relations efforts on making this pivot visible across all audience segments. Use visualizations that show the investment required for sustainable manufacturing practices can pay off in the form of earning customers from the growing environmentally conscious market segment.

?A step-by-step guide to data storytelling

Data storytelling isn’t just about creating visualizations and sharing them. It requires a structured approach and consideration of various factors. While there is no set formula for telling the story of your data, here are some steps you can follow:

?A. Identify your audience

To create an engaging story, you first need to understand exactly who you are trying to engage. Who are you presenting your insights to? Why should they care about the data and your findings? What problem or challenge will the data help them to address? What insights from your analysis will matter most to them?

?B. Construct a compelling narrative

When sharing your insights, you don’t just want to explain them; you want to take your audience on a journey. To build a narrative:

?Start by setting the scene: What’s the context behind your analysis? Why did you analyze this data in the first place? What was the problem or challenge you set out to solve, and why does it matter?

Present and discuss your findings: What did your analysis tell you? What are the main points you’ll share with your audience? What answers can you provide to the original questions or challenges you set out to investigate? Remember that not all the data used in your analysis will be relevant to the story you want to tell, so it’s important to pick out and highlight the key points.

Provide action points and solutions: Based on your analysis, what actions can be taken moving forward? What advice can you give to your audience? How can they utilize the data you’re showing them, and what will be the impact?

C. Create and organize your data visualizations

You may have already created data visualizations as part of your analysis. If these visualizations already illustrate the key points you want to convey, it’s a case of organizing them and deciding how you’ll present them—for example, figuring out the order in which they’ll be presented to your audience. Otherwise, you may need to create additional visualizations in order to convey your data.

?D. Share your data story

With a compelling narrative in place, there’s only one thing left to do: Share it!

Remember, Data storytelling is a powerful tool! By learning to translate insights into engaging narratives, you can influence decisions, drive change, and make your data truly sing!

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