What is Data Storytelling?
Organizations are racing to become more data-driven. But data, facts, and numbers rarely get us excited and motivated. Humans are hard-wired to engage with stories. Data storytelling is a powerful tool we can utilize to captivate an audience and enable them to engage with complex, data-driven insights.
The chart below has been created using default settings in Microsoft Excel. No data storytelling techniques have been applied to it. Can you identify the key insights that the creator of this chart intends to convey?
Let’s make those key insights easier to extract by giving this chart a makeover. The version below takes the same underlying information and applies data storytelling best practices to the chart design.
In the improved version, the take-home message is instantly apparent, with a concise, descriptive title. The chart is free of clutter and distractions, and color has been used sparingly to focus on the chart components that support the key insight.
Why is data storytelling important?
Data storytelling is a crucial skill set because data is proliferating rapidly across the globe. Unfortunately, data-literacy and communication skills have not kept pace with the growth of data availability. Consequently, we frequently encounter reports and presentations that confuse and alienate the people relying on them to make decisions.
Data storytelling enables us to create reports and presentations that deliver clear and crisp insights that can be harnessed to make better decisions.
How to tell stories with data
StoryIQ has developed the “4D’s” process for telling compelling stories with data:
Our first step is to distill the most critical insights from our data set. In our first chart, there are many noteworthy trends that we could choose to focus on. The trend that stands out most is the rapid rise in Google Chrome’s market share, which has more than doubled in the last eight years. For a broad audience, this well-known product’s explosive growth is the most relevant story.
However, imagine that we are presenting to an audience of iOS (iPhone) developers. These developers may be much more interested in Apple’s Safari browser’s market share, especially on mobile devices.
Our role as data storytellers is to determine what insights will best serve our audience’s needs. Once we’ve established what our audience needs to know, we want to convey our insights succinctly. Our new headline, “Chrome Crushes the Competition,” helps us achieve this, capturing the key insight using just four words.
We now have a critical choice to make. How do we visualize our data so that it’s easy for our audience to understand? Do we need to use a chart, and if so, what chart type will best showcase our insights?
Our top choice for visualizing trends over time is a line chart. Compared with our 100% stacked bar chart, we can see that the lines facilitate a faster comparison of each product’s market share.
Once we have selected the optimum chart type, we must relentlessly purge any visual components that are not working hard to support our key takeaway. In this example, we can simplify the chart by:
- Removing gridlines.
- Simplifying the X-Axis labels.
- Replacing the legend at the bottom of the chart with labels abutting each series, allowing us to use color more sparingly.
Finally, we want to direct our audience’s attention to our visualization components that support our key insights. In this case, we’re highlighting the Google Chrome series in bright green. This highlighting enables our audience to immediately identify that the data supports our title and key takeaway.
With a well-designed, clutter-free chart, we could even choose to direct our audience’s attention to some additional insights. For example;
Whatever message we choose to highlight, data storytelling best practices help to ensure that our audience can understand and engage with our message.