What is data storytelling?
Data storytelling is the process of translating data analyses into understandable terms in order to influence a business decision or action. Data analysis focuses on creating valuable insights from data to give further context and understanding to an intended audience.
With the rise of digital business and data-driven decision-management, data storytelling has become a skill often associated with data science and business analytics. The idea is to connect the dots between sophisticated data analyses and decision-makers who might not have the skills to interpret the data.
Data storytelling can also be used to convey interesting usage metrics for customers.
Some experts, such as thought leader Tom Davenport, a professor of Information Technology and Management at Babson College in Wellesley, Mass., emphasize the importance of the narrative -- no matter the medium. "Narrative is the way we simplify and make sense of a complex world. It supplies context, insight, interpretation -- all the things that make data meaningful and analytics more relevant and interesting," he wrote in "Why data storytelling is so important -- and why we're so bad at it," which was published in Deloitte Insights in January 2015.
Other experts, such as Howard Dresner, founder and chief research officer of Dresner Advisory Services, describe data storytelling as a set of features within visualization tools that enable a more interactive experience with the data.
With only charts, dashboards and data visualization tools, decision-makers in an organization might not understand what a specific amount of data means. So instead of looking at it purely from a data-driven perspective, data storytelling wraps that data in a narrative that's more understandable.
Data storytelling uses data collected from charts, dashboards and data visualization tools to tell a story that has a beginning, middle and end. So that businesses can understand the importance and significance of the presented data, the data narrative is told as an example or experience and should be unbiased and in proper context. For example, if there's an issue with a product, to convey why it should be fixed, data storytelling should take the collected data and tell a story about how end users will encounter this issue and how it will affect them.
The three components of data storytelling
Data storytelling comprises data, narrative and visualizations.
- The data serves as the base of a data story. It's information from accurate data gathering and analysis. Data can be gathered from such places as charts and dashboards using data analysis tools.
- The narrative is a verbal or written storyline that's used to effectively communicate insights from the data. The narrative should be within the context of the data and aim to show a clear reasoning for following actions or decisions. Narratives should be based on data and present a clear explanation of what the data means and its importance.
- Visualizations act as further representations of both the data and narrative and are used to communicate the story more clearly. Visualizations include graphs, charts, diagrams and photos.
Importance of data storytelling
Data storytelling is a great way to gather insights about data for people who aren't formally trained in how to read data gathered from the dashboards of data analysis tools. Others who might be easily overwhelmed by a massive amount of data points could find it difficult to find any meaning or remember data presented to them in a typical dashboard, chart or graph. Data storytelling frames that information in a way that's clear and memorable for those people. A story will engage those people and present the data in a way they can process, comprehend and empathize with any effects the data shows.
As opposed to, for example, a data scientist explaining the significance of gathered data to a board with only a spreadsheet full of numbers, data storytelling helps convey the significance of what those numbers mean. This makes the presented data much more compelling and memorable.
What makes a good data story?
A good data story must use data, a narrative and visualizations to be effective. However, to make the narrative, a data story must also include the following:
- A setting. The setting should be based on the data. If, for example, the data is about internal systems, then the setting would be inside an organization with the same internal setup.
- Characters. The characters could include customers, the organization, stakeholders or other key players the data surrounds.
- A conflict. The conflict is any issue and the effects of that issue that the data might present. The conflict will affect the characters or setting.
- Resolution. The resolution is a proposed solution to any apparent issues or anything that might help inform the decision-making processes.
Data stories don't always need conflicts. However, if this element of the data story is skipped, the resolution is a recommended course of action.
Each insight that the data shows can also be illustrated with a visualization to help the audience better follow along with the story. Communicating an effective data story requires hard and soft skills.
Examples of good data stories
Data storytellers have become more popular inside and outside of the workplace.
The music app Spotify, for example, sends out recap stories annually to its users. On December 1 of each year, Spotify Wrapped delivers users a wrap up of their music and podcast consumption. These stories contain statistics for each user based on all of the music they listened to that year. Seeing this data presented in such a way provides an engaging way for users to understand the music they listen to the most.
Similarly, Slack sends an email to its customers that consists of a visual story that expresses key insights on how they've used the service.
Durham, N.C.-based Automated Insights uses natural language generation software that turns data -- such as statistics from a basketball or baseball game -- into Associated Press wire stories. The company hopes to provide a similar service for businesses, where it turns sales or marketing data into news stories.
Beyond analysts, data scientists and other business users, data stories in the future will be provided by new data tools. Data storytelling and artificial intelligence predictions can be used together in powerful tools to help create predictions from data without any extensive configurations.
Learn about predictions of the future growth of data storytelling in business intelligence according to Gartner.