Taking a Data-Driven Approach to Creating More-Effective Data Visualizations

It is widely recognized that the human brain processes images better than words. And research shows that 65% of people are visual learners. Even in our personal experience, we know that when information is visualized well, we get the “So what?” of an article or report faster and easier.

Effective data visualizations can also help drive meaningful change — in our own lives, at work, and in the world around us.

Consider one of the earliest examples of an infographic: Florence Nightingale’s 19th-century rose diagram that proved, beyond the shadow of a doubt, how poor hygiene was killing more soldiers than combat. Talk about persuasive! It didn’t take long for the British government to effect changes in sanitation for the troops, saving countless lives.

Contrast this with the failure of Hungarian doctor Ignaz Semmelweis, who in 1846 tried to use overwhelming statistical tables to convince the medical community in Vienna, Austria, that deaths among women in childbirth plummeted when doctors washed their hands before treating them. Because of how he had presented it, even medical experts could not understand the practical application of Semmelweis’ statistical data.

Why Pictures Are Worth a Thousand Words

New studies show that the human sense of sight has the same bandwidth as a computer network in terms of what reaches the brain and how quickly. It takes only a few hundred milliseconds for raw visual stimuli to reach the brain and be processed and filtered for what is important. In contrast, reading lots of text takes time and uses different parts of the brain.

However, not all data visualizations are good or effective at conveying the big “So what?” of large volumes of data. You need to apply what is referred to as “Gestalt” theory, which describes how humans perceive visualizations in relation to other objects and environments and see structure, logic, and patterns. Gestalt theory suggests that human brains are built to make sense of complex images — even if that means organizing parts of images and filling in gaps where needed — to create a new, organized system of understanding. This helps to explain how different people looking at the same complex image can “see” and “understand” different things from it.

Brain Science Can Help Create Compelling, Easy-to-Understand Data Visualizations

Whether you are a data scientist that needs to create better human resources (HR) reports or an HR leader seeking to use data-driven insights to persuade or inform more effectively, applying Gestalt principles of design will help you create visualizations that are more compelling and easily understood.

A simple Internet search will take you to content about laws such as:

  • The law of proximity: People perceive visual elements in terms of their spatial proximity. The more closely positioned elements in a data visualization are to one another, the more the brain will perceive groupings and layer meaning upon them.
  • The law of similarity: The human brain wants to group together things that look similar, even when they technically are not. To tell a clear story with your data visualizations, use this to your advantage by making elements that you want readers to group together similar in color, shape, or size.
  • The law of closure: When the human brain sees complex arrangements of visual elements, it will create recognizable patterns and even fill in blanks to create a complete image that makes sense. So beware of incomplete data plots that readers’ brains can potentially fill in incorrectly.

The point is, the readers of reports all have brains hard wired to make sense of complex images such as data visualizations. By applying Gestalt principles to how you create data visualizations, you can make it faster and easier for readers’ brains to interpret your data visualizations quickly and correctly – and thus understand and remember your big “So what?”

When you combine Gestalt design principles with findings from the latest research on design variables, such as using color versus black and white visuals, you can really hone your data visualizations to get readers’ brains firing on all cylinders. For example, studies show that:

  • Colored visuals vastly increase people’s desire to read content.
  • Combining content with images drives a spike in view rates.
  • Posts with images more than double engagement rates.

Next-Gen Reporting Tools Make It Easier to Tell Rich Stories

Next-generation reporting tools such as the stories in SAP SuccessFactors People Analytics, which works across the SAP SuccessFactors solution suite, and the SAP Analytics Cloud solution, which supports cross-topic analytics, enable these types of data visualizations.

For example, stories in SAP SuccessFactors People Analytics allows users to leverage their people data to make better business decisions across all HR disciplines; for example, by visualizing demographic data with recruiting and compensation data. Similarly, SAP Analytics Cloud allows users to cross-reference HR data with other enterprise data, such as finance data, to create revelatory report visualizations that tell stories with real business value.

Imagine, for example, crossing external workforce spend data with finance data to better understand total spend, when spend occurred, and by which departments. The visualizations generated from crossing such data can enable more effective workforce planning and more accurate budgeting.

Visit sap.com/people-analytics to learn more.