How to Effectively Tell a Story with Data
When most people hear references to data and data analysis, they think of spreadsheets, algorithms, and mathematical calculations. While those hard skills are involved with processing and interpreting data, all of those skills are useless without their soft skill counterparts. It is not enough to just analyze the data and look at the numbers, you need to be able to communicate the story the data tells in a clear and compelling manner. In short, you need a skill called data storytelling.
Within the next decade, the demand for research analysis is expected to grow 25%. That is a faster growth rate compared to the average among all industries. As a result, many companies have begun to include data storytelling as a required skill in analyst level roles. Having both the soft and hard skills to analyze data and communicate its insights are required for a well-rounded candidate.
Here's a quick rundown of all the components of data storytelling, why storytelling is impactful, and how to create a data story of your own.
What is Data Storytelling
Data storytelling is the ability to communicate insights from a dataset using narratives and visualizations. This puts data insights into context for and inspires action for your audience.
Three components to data storytelling are:
1. Data: Thorough analysis of accurate and complete data serves as a foundation for a great data story. Using descriptive, diagnostic, predictive, and prescriptive analysis enables you to understand the big picture behind the data.
2. Narrative: A storyline in verbal or written form is used to communicate the insights from the data, the context, and recommended courses of action or inspiration for your audience.
3. Visualization: Visual representation of your data and narrative allows for a more memorable and clear data story. This can be as simple as a chart, graph, diagram, pictures, or videos.
The Power of Storytelling
Storytelling has been used for humans to communicate ideas for tens of thousands of years for survival and records of accounts of daily life. While storytelling has changed since when the practice started, the power behind storytelling still holds true today.
Storytelling removes barriers the brain experiences just based on the fact that the brain takes in so much information every day and needs to determine what information is important to process and remember and what can be discarded.
When someone hears a story, multiple parts of the brain are engaged. More specifically, the hippocampus which stores short-term memories and is more likely to convert the experience of hearing a story into a long-term memory.
Instead of presenting a spreadsheet of data and rattling off numbers, consider what you can do to engage multiple parts of their brains. That will evoke an emotional response that will help your points be remembered and acted upon.
How to Craft a Compelling Data Narrative
Data storytelling uses the same narrative elements as any other story you have read or heard before: characters, setting, conflict, and resolution.
Picture this, you're a data analyst and just discovered your company's recent decline in sales has been driven by customers of all genres 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:
1. Characters: The players and stakeholders include customers between the ages 14 and 23, environmental conscious customers, and your internal team. These people don't need to be a part of the story, but they are useful to keep in mind for yourself.
2. Setting: Set the scene by explaining there's been a recent drop in sales driven by customers of all genders between the ages 14 and 23. Use a form of data visualization to show the decline across all audience types and highlights the largest drop in young users.
3. 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. Incorporate research about how consumers are more environmentally conscious as ever and how sustainable-marketed products can drive up more revenues than their unsustainable counterparts. Remind your team of your company's current unsustainable manufacturing practices to clarify why customers stopped purchasing your product. Include a form of data visualization here too.
4. 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 data visualization here as well to show the investment required for sustainable manufacturing practices can pay off in the form of earning customers from the growing environmental conscious market segment.
In cases where there isn't conflict in your data story. Skip that and go straight into the recommended course of action.
Whatever story the data tells, you can communicate it effectively by formatting your narrative with these elements and walking your audience through each piece with the help of visualizations.
Communicating the Need for Action
Data storytelling builds a bridge between data insights and actions. Without effective communication, insights can go unnoticed and forgotten by your audience. This is why both hard and soft skills are crucial for leveraging data.