1. Data storytelling group framework
We are in the home stretch, and we have covered a lot of ideas for communicating data insights. Data storytelling is a game changer in our data-rich world.
2. Teamwork makes the dream work
Anyone who uses data or interacts daily can see massive dividends by investing in their data storytelling skills.
We’ve covered the concepts and some best practices, but how do you go about building your skills? The answer is simple; we use the power of friendship! But seriously, the best way to learn and improve your storytelling skills is as part of a team.
Working as a team, individual members can highlight their strengths and focus on growth areas while leveraging the data culture within their organization. Data storytelling has three key components that fall within four typical roles.
3. Getting the band back together
The four roles we focus on are the subject matter expert, analyst, visualizer and reviewer.
Each role is responsible for different parts of the process. Lets talk more about each one so you can start thinking about your data storytelling team.
4. Subject matter expert (SME)
Our first role, the subject matter expert or SME role, is responsible for knowing the business inside and out and being ready to respond to questions and concerns. Their objective is to develop the narrative, which we defined as the overarching message the data story is trying to convey. The SME is someone intimately connected to the business problem, so their view on the insights is invaluable to the success of the overall data story.
Additionally, the SME is responsible for setting the context for the story. Context differs from the narrative by highlighting how the insights relate to the rest of the organization and providing background for understanding the narrative. Practical context setting requires a strong understanding of the organization’s goals and other initiatives.
5. Art and science
Our final component of storytelling was visualizations. Creating strong visuals is equal parts art and science, making the visualizer's role essential. The visualizer will often work with the SME to understand the insights and create something that showcases the SME's vision for those insights.
6. Analyze this
Analysts make up the third typical role, lending their technical expertise to uncovering insights for the SME and supporting research related to feedback and inquiries from the audience.
It is essential to distinguish between SMEs and analysts because having a solid technical knowledge to uncover insight doesn’t always translate into a deep understanding of business contexts or compelling narratives around the insights. Having someone the team can turn to for analytical questions ensures that robust analytics support quality insights.
7. Focus the story
Data storytelling, like all forms of communication, is ultimately about sharing a message with an audience. When crafting a data story, it is vital to identify someone to play the reviewer role.
Their role is to act as the audience and allow the team to iterate on the story. Selecting people who are unfamiliar with the datasets or with the insights can assist the team in seeing if any assumptions are incorrect.
8. Remain flexible
The biggest thing to remember with all these roles is that people can serve multiple positions; you don't need a team of four to be successful with data storytelling.
Instead, find a group you feel comfortable with and start there. Rotating the roles and learning from each other is more valuable than following a checklist and making endless visualizations.
9. Let's practice!
Let's wrap this lesson up with some exercises on strengthening your data storytelling skills as part of a team and bring in our learning from across the entire chapter.