Data visualization is fast
becoming the common language for companies using business intelligence to make better data-driven decisions. Data visualization—done right—not only quickly draws attention to the most important metrics, but helps uncover previously unseen patterns and observations that wouldn’t be apparent by looking at numbers in a spreadsheet.
Notice I put great emphasis on “done right.” With any language, there are subtle ways to communicate correctly in order to highlight important elements, and data visualization is no different. My years working with “data viz” for companies of all sizes and industries has shown me some of the very best and very worst of what can be done with this tool.
What you're about to read is all a part of the data visualization workshops I hold throughout the year for TARGIT customers and partners. If you’re interested in attending a TARGIT data visualization class, you can sign up for any of the upcoming dates at various locations online or in the classroom. Register today.
The Goldfish Effect
According to the National Center for Biotechnology Information, humans are capable of holding exclusive attention on one task solely for a total of eight seconds before becoming distracted or moving on to the next task. Compare that to a goldfish, who has an average attention span of nine seconds and we’re not looking too great as a species overall.
That’s why I've written about the Goldfish Effect as the perfect litmus test for the effectivity of a data visualization. If the most important metrics cannot all clearly be consumed and digested from a data visualization in eight seconds or less, it’s not a good data visualization.
As illustrated below, data visualization is vital part of any business intelligence project which is why it’s so critical to get it right. Without the proper use of data visualization, there is a huge jump from the information available to gaining an insight that this information holds.
Source: Thomas Black-Petersen, Inspari
There’s a lot of things you shouldn’t do when building data visualizations and dashboards. But instead of focusing on the bad, I’d like to inspire you with what works best. I have compiled a list of my top data visualization best practices that I regularly use when creating dashboards and analyses for my customers. I'll share my first five with you today.
While I hope this leaves you inspired to create effective new data visualizations for your organization, a change in business intelligence processes should be looked at as an evolution to better, data-driven decision making. Not all change can happen overnight, but get empowered to take the first step to better data visualizations today.
In each of my examples, I will be using the TARGIT Info Gauges as the object when explaining various techniques and guidelines. However, most of these points can be transferred to any graphical object within TARGIT. Info Gauges are one of the data visualization objects that I use regularly when creating TARGIT dashboards aided by the TARGIT Gauge Builder, as shown below. You can download the Gauge Builder here.
Data Visualization Best Practices
1. Contrast gives focus
Only include the most critical metrics in a dashboard. I repeat: Only include the most critical metrics in a dashboard. But even within that list of “most critical,” information can typically be ranked in importance. Therefore, weight data differently to highlight critical information. By using contrast in your data visualizations, you can guide the Information Consumer’s attention to what matters first before they decide more information is required.
Not sure who your Information Consumer is or what information they need? This guide will help you determine the various BI personas in your organization and how to best create data visualizations that suite them: How to Ensure the Highest User Adoption Rates for your BI Project
Below are two examples of the same info gauge containing the same information. Notice that the information on the first gauge is weighted equally. However, the second gauge has a clear weighting, guiding the consumer to evaluate growth before moving on to the other information.
2. Colour is hard to master
Using coloured elements in an info gauge that do not strategically enhance the information leads to bottlenecks in the brain. Our eyes are automatically attracted to bright colours. If colours are popping all over the dashboard, it will be difficult to rank importance and focus.
Examine the two info gauges below. Notice that when you look at the first gauge, your eyes have a very hard time focusing on the information. Your eyes feel the urge to wander out to the edges of this gauge because of the blue colour surrounding the gauge.
The second gauge—with a very subtle difference—is a very different experience for your eyes. Less pizazz here enables you to focus on the actual information without distraction.
But don’t think colour bad. Colour is a great way to categorize information that comes from the same business areas or have a common purpose. Use it sparingly and use it with intention.
3. Limit numbers
When presenting figures on an Info Gauge, remember that gauges are used to present high-level information only. That is why it’s a good idea to reduce the number of memory chuck needed to process this information. By limiting the number of digits used, the second gauge will allow the consumer to process this information faster and increase the chances of retrieving the information from memory when needed later.
4. Only when negative
If you’re having trouble narrowing down the most important information to include in your dashboard, a good idea is to simplify by only indicating information if there is a problem. This helps guide users’ attention to the most important information so they can address any problem quickly.
It also helps prioritize the starting point when faced with two or more pieces of information on a dashboard. Our brains react to differences in our environment as an alert mechanism. By only using indicators like on the second info gauge below, you’re tapping into this instinct which is why you’re automatically drawn to the gauge with a negative growth.
An added bonus with this approach is you reduce the concerns for the 12% of the population that are colour blind. Just a little data viz humour.
5. Make it personal
Typically, the use and, more often, overuse of colour on dashboard elements is discouraged, as it distracts from the overall message that needs to be delivered. However, including elements that have a look and feel that match your company’s brand gives dashboards and analyses an authoritative presence. This tells the user that any information within these dashboards can be trusted and is part of a greater corporate strategy.
By creating Info Gauges based on internal design guidelines, you can easily achieve greater coherence and authenticity. Use this sparingly. I don’t suggest copying text and imagery directly from websites. Rather pull out a few individual elements in a design that best reflect the essence of a company to integrate into dashboards. Below are two examples of Info Gauges inspired by company websites.
Read my next five data visualization best practices here.