Stories are a fundamental component of effective human communication. According to a study conducted by Stanford University professor Chip Heath, 63% of people are likely to remember a story shared as part of a presentation. He also found that speakers who merely present facts and figures only achieve a 5% recall rate among their audience.
Stories convey meaning and context in ways that facts and figures alone cannot. In the era of big data, it’s especially important to be mindful of that reality. That’s why today’s smart business leaders are using data-driven storytelling to make an impact on the people around them.
Raw Data, Visualizations, and Data Storytelling
Imagine the following three scenarios, all based around the same core set of information:
Bill compiles a set of historical sales figures spanning the past two years, summarizes it by month, and provides breakdowns for each of the three product lines that the company sells. The resulting report is rich with numerical information, arrayed in rows and columns, with monthly subtotals and grand totals at the bottom of the page. A few of the number-crunchers in the audience dig into the details, but the point (if there is one) is lost on most readers.
Jane takes exactly the same information and renders a series of graphs that display sales trends for each of the company’s various product lines using rich, full-color graphics. It’s an impressive report, providing a far more visceral experience of what’s been happening with the company’s sales revenue. The members of Jane’s audience walk away with a clear understanding of the numbers. Unfortunately, most of them are missing the “why” behind those figures.
Patrick takes Jane’s idea one step further, graphically displaying historical sales figures, then adding trendlines, superimposed with promotional expenses for the same period. He turns it into a series of graphics, with narrative content to point out the peaks and troughs in sales revenue. Patrick explains the correlation between promotional activities and the ensuing uptick in sales orders. He also explains that other key factors (such as the number of salespeople on staff) were relatively constant throughout the past two years.
Patrick’s audience walks away with a clear understanding of what happened, but perhaps even more importantly, they understand why it happened. Patrick has mastered the art of data storytelling.
The Role of Data Visualizations
None of this is to say that raw data and visualizations are unimportant. In fact, they are essential. But storytelling brings data to life and gives it meaning in a way that makes it easy for your audience to understand. Visualizations are an important ingredient in a good data-driven story.
It’s said that “a picture is worth a thousand words.” If you’re communicating with anyone whose eyes glaze over at the thought of detailed columnar reports, it’s probably more accurate to say that pictures can convey reality when the “thousand words” (or numbers) may appear altogether meaningless.
Data visualizations help to bring information to life. History offers some stunning examples. During the London cholera of 1854, for instance, scientists were struggling to solve the mystery of how the disease was spreading. Dr. John Snow plotted cholera deaths on a map of the city, placing a small dot at the home of every person who succumbed to the disease. Upon seeing the completed map, it immediately became clear that the epidemic was clustered around London’s Broad Street pump. Access to the pump was shut down, and the outbreak came to an end.
In the same way, business data presented in a graphical format conveys information quickly, with relatively little effort on the part of the reader. In this respect, data visualizations comprise a valuable starting point for a compelling data-driven story.
Data Storytelling Drives Better Outcomes
Data visualizations alone are not sufficient to create clear alignment and drive outstanding business results. According to a study conducted by Hanover Research, only “20% of users are most satisfied with data visualizations.” That leaves 80% with a less-than-optimal experience. Why? Because they’re still missing the story that accompanies the pictures.
Organizations perform at their best when teams are clearly aligned around a common purpose – with a shared understanding of what needs to be done, who will do it, and when. Consider our previous example, in which Bill, Jane, and Patrick each reported historical sales trends to a team of senior executives and department managers.
Bill’s rows and columns of figures fell (mostly) on deaf ears. Each member of the group was left to draw his or her own conclusions. Very likely, many of them drew no conclusions at all.
Jane’s data visualizations were better, but they, too, lacked any specific direction. Jane simply presented some information about revenue trends, without linking it to anything that might have led to increased sales.
Patrick, on the other hand, delivered a powerful story using the company’s historical sales data. When it was paired with information about promotions, it conveyed an important point: the company’s promotional efforts were paying off. The result? Patrick’s audience quickly aligned around a plan of action. Together, they could drive even better outcomes for the coming year.
Embedded Analytics Brings Data Storytelling to Any Application
Data storytelling is the future of analytics. If your software company wants to truly stand apart from the crowd, then data storytelling should be part of your value proposition. Today’s users don’t merely want systems that can record and organize data; they want to derive actionable insights from their data.
To do that, software companies must go beyond the standard library of reports and simple graphs that most applications offer. To turn your product into a value-generating asset for your customers, there are several paths you might consider.
First, you could build analytics into your product using UI component libraries. That’s slow and labor-intensive, and it comes with some limitations. Each component must be customized separately, and there’s risk involved with any upgrade.
The second option is to rely on a separate business intelligence (BI) platform, but that can be complex and expensive, and BI tools often require your customers to have specialized technical expertise.
Data discovery tools can be helpful, but they sit outside of your application, forcing users to task-switch and destroying the “single pane of glass” that so many users prefer.
The fourth option is to use a full-fledged embedded analytics solution, which gives you maximum flexibility. Logi Composer from insightsoftware enables development teams to add powerful data analytics capabilities to any software product, whether your product is a cloud-native SaaS solution or a traditional on-premise application.
Logi Composer, by insightsoftware, supports unlimited customization and white labeling, so you have total control to make the application uniquely your own. Over 2,200 application teams already trust Logi to help power their businesses with sophisticated industry-leading analytics capabilities.
To learn more about Logi Composer, reach out for a free, no obligation demo today.