Running a business is impossible without data. Data clarifies the facts, revealing insights that help everyone from top executives to front-line employees make better decisions. Nonetheless, it is as much an art as a science to make sense of data and use it to maximum effect.
Information overload is one reason. The amount of data collected by organizations makes it hard to determine what’s significant. In addition, it is challenging to present information in a way that communicates its significance to all those who need to act on it.
Slide decks are often used to summarize key findings, but viewers’ eyes glaze over when they are exposed to slide after slide. Business intelligence reports are another option, but they can be overwhelming for people not intimately familiar with the content. In any case, neither technique fully engages the audience if the data doesn’t come to life.
A compelling narrative can be integrated with precision data. By placing data in context, data storytelling explains what the numbers mean and what can be concluded from them.
Through the use of traditional elements such as charts and tables, data storytelling visualizes the facts clearly. However, it goes beyond mere visualization by connecting images in a specific order to a general theme, guiding viewers through the data and explaining its implications. The goal is not just to communicate information but to convey a message and convince the audience of it.
This differentiates data storytelling from data visualization, which focuses on the bare facts, as in this example:
- Every branch exceeded its target in Q1.
- Data storytelling paints the bigger picture, enabling the audience to reach the desired conclusion.
- On Jan. 1, we implemented a new commission schedule. In Q1, every branch exceeded its target. With the additional revenue, we can hire more sales personnel. Here’s how much we can expect to grow revenue with the expanded staffing, based on Q1 performance.
Sound complicated? It’s not. Here are some tips that can help you transform raw data into a compelling data story.
1. Understand the question and the audience
Decide what question you want to answer first. If sales rose sharply last year, what is the reason? Knowing what you’re looking for can lead you to the right resources – in this case, reports on the product mix, client list, population growth, or staffing.
You should also understand your audience and tailor your presentation to suit them. Is it your customers, employees, or investors? How familiar are they with the topic? What is their interest, or how does this affect them? Can they handle high levels of detail and different presentation styles?
2. Analyze your data
You can’t create a compelling data story without understanding how the underlying data is structured. It may sound obvious, but make sure you know basics such as the difference between sales and revenue, and the meaning of terms such as “active customers” and “days past due.” Business glossaries help you categorize data, making it easier to understand.
Assess data structure and quality. Prepare a profile that highlights key characteristics such as format, patterns, and completeness. To ensure complete and accurate data that supports a trustworthy data story, use a Data Quality tool that can check for validity and accuracy.
3. Organize your data
Despite your profiling, you may find that some data is lacking. You may need to address anomalies by standardizing formats, parsing, enriching, or deduplicating. If percentages and decimals are used interchangeably – such as 75% and 0.75 – standardizing the format is a good idea. Fill in the missing information from another source if a data set is incomplete.
4. Craft the data story
Using charts and other data visuals effectively depends on knowing how people perceive them. Many viewers want to get the big picture (rather than nitty-gritty details) at a glance, so they immediately see the value of the message.
Consider the order in which you present information to maximize impact. Consider questions a viewer might ask in response to a particular chart. The first chart might show an increase in sales, and the next might detail the reasons why. A logical path for your presentation is often outlined by your research into various reports and trends.
John Burn Murdoch, a data visualization expert, recommends building the story in layers to avoid overwhelming your audience with complex graphics. In comparison to a single, crowded chart with unclear data, three consecutive charts work better. Highlight areas of interest or reflect significant changes with animations. Consider your chart as a sequence of frames. As a whole, the story needs to flow from one frame to the next.
Don’t overlook the text accompanying a chart. It is often the first thing viewers glance at when they see a chart. Explain what it shows. Rather than a static label like “Sales Trends,” provide an explanation such as “Sales Declined Last Year but Should Rebound This Year.” Consider highlighting significant details on a chart with color, arrows, circles, or text annotation to make sure they’re not overlooked.
It doesn’t have to be elaborate. Usually, a bar graph or line chart will do the trick, according to our data visualization experts. You can add visual interest by using color coding, graphics, and other elements.
5. Let your data story be heard
After your storytelling data visualization is complete, you can share it on social media, on your website, or by email. If that will be more accessible to your audience, you can even record it as a video presentation. Connect with them where they are (i.e., the channel they use most often) and tell your data story.
In the data you’ve collected, there is a wealth of information. These five tips can help you create an engaging data story that will resonate with your audience.