Data Storytelling: How Your Company Can Use It
In this article
Whether we realize it or not, we’re bombarded with an onslaught of visual information every day. From print advertisements and television commercials to stop signs and green lights, the world around us relays a constant stream of data—often accompanied by some kind of visual representation to help us absorb it quickly. So how do companies and organizations communicate with their employees, clients, and stakeholders in the age of instant data gratification? The answer is simple: data storytelling.
Spreadsheets and static reports show data, but narrative data visualization tells a story. The difference between the two is subtle, but important. Data storytelling provides the context your audience needs to see the connections between important trends. It draws users in and helps them turn raw data into usable information. Simply showing people numbers can’t accomplish this.
Just like the data that surrounds us every day, data storytelling appeals to and is accessible to a wide audience, including those who aren’t as data-savvy as the people behind the reports. The best part is anyone can use data storytelling to better their organization; all you need are the right tools and a roadmap to start driving in the right direction.
Data Storytelling Tips and Tricks
Your data narrative has a distinct structure, just like the stories you watch on TV or read in books. Where do you want your audience to begin? Where does the story end? How will you get them there? The answer to these questions are the first glimpses into your data’s story. It’s easy to get swept up in the color scheme and design of your data visualization, but actually creating an interactive dashboard is one of the last steps in the storytelling process. Instead, the story starts with a concept, and that concept should give a voice to the relevant information you want to communicate. After all, you can’t start writing a story without a plot.
Essential elements to convey an effective data story:
- Include the right details. On the flip side, this means you want to avoid the wrong ones. Don’t overload your audience with information right off the bat. By keeping your data efficient, so to speak, you can guide users toward meaningful conclusions. (Ex. This table provides too many details about each sales opportunity, but the bar chart shows the metric the department truly cares about—open opportunities—in a more visual manner.)
- Provide the right context. Every set of data should relate to your organization’s larger goals, and your dashboard or data visualization (a subset of data science) should highlight the correlations between each metric and these KPIs. (Ex. This chart shows actual website traffic alongside the target numbers to provide important context.)
- Provide actionable information. Your audience should know why a specific chart or graph is important without any guesswork. Additionally, it should be easy for them to see how the data relates to their role in the organization. (Ex. It is easier for a school to act when they can see all of their education assessment scores in one view. Eisenhower Elementary School has a clear takeaway from this chart because they can see what they should change and what should stay the same.)
Getting Creative: Illustrate Your Data
Once you understand the “why” behind the metrics in your data storytelling, it’s time to start thinking about design, functionality, and visual appeal. While this might seem like the fun part (and it is!), it’s also crucial to the success of your data narrative. After all, data visualization is about making your data more accessible, not just colorful. Take your organization’s branding into account as you choose colors, as logos and company colors can instill a sense of ownership and lend context to metrics. It’s equally important to think about how those colors communicate with your audience semantically. Avoid loud colors without purpose, and don’t be afraid to include plenty of negative space (white space between your charts and graphs) to guide the user’s eyes from one metric to the next (as seen in the example below).
In some cases, you can use viewers’ preconceived assumptions about color to your advantage. Most people associate red with “stop” and green with “go,” for example. Use these expectations in your data by linking it to related information. (Ex. These gauges use color to show where the company’s finances are in relation to their forecast.)
Similarly, certain graphs lend themselves to specific sets of data. Pie charts, for instance, are useful for showing how percentages of a whole stack up against each other, whereas a bar graph might be useful for more detailed sets of information. The same thing goes for scatter charts, sparklines, and histograms—each type lends itself to different types of information. Use these inclinations purposefully in your data visualization and storytelling.
Related: How to Make Histograms in R
Get To Know Other Data Science Students
Machine Learning Engineer at IQVIA
Data Scientist at Spin
Data Scientist at NPD Group
How Companies Can Use Data Storytelling
Taking your reports to the storytelling level isn’t an overnight project; it takes careful planning and strategy. By using data effectively, you can say “goodbye” to raw statistics and “hello” to clear, practical, and actionable reporting. After all, old-fashioned reports grow stale in the time it takes to print them out. Live data through a dashboard, on the other hand, can keep your employees, team, and company continuously aware of their progress and in touch with trends that might influence their given roles and responsibilities.
How an effective data narrative can help your organization in the long run:
- Present information in an accessible, easy-to-digest format
- Share real-time information with everyone, instantaneously
- Provide the information people need to make informed decisions
- Cater specific sets of data to specific stakeholders through user access
- Offer customizable dashboards for fine-tuning in the future
Every company can benefit from data storytelling, and data scientists are the driving force behind it. That might sound like a broad statement, but the practical application of data visualization is endlessly customizable and the principles behind it are universal. In short, data storytelling is the difference between “I’ll have it on your desk in the morning” and “I have everything you need right here, right now.” Not only does it provide instant access to crucial metrics and progress, but it makes this information easy to understand, simple, and practical.
Related: How to Create an Awesome Data Science Portfolio
The beauty of data visualization is that you don’t need to be a statistics guru to understand it. Data storytelling does the heavy lifting for you and your co-workers, so even people who aren’t used to sorting through and interpreting data can use it to benefit their own work. At the end of the day, data storytelling means faster and more informed decisions so users can spend less time sorting spreadsheets and invest more time raising the bottom line.
This post was written by Jennifer Horne, a senior digital marketing coordinator at iDashboards. Jennifer handles content, search, and digital marketing strategy for the data visualization software provider. She has won multiple “30 Rock” trivia competitions, makes a mean green curry, and loves living in Detroit.
Since you’re here…
Thinking about a career in data science? Enroll in our Data Science Bootcamp, and we’ll get you hired in 6 months. If you’re just getting started, take a peek at our foundational Data Science Course, and don’t forget to peep our student reviews. The data’s on our side.