How You Communicate with Data: Be More Effective & Influential
04/22/2019 by Tricia Aanderud Data Communication
Creating useful data communications that influence audiences is a mix of art and skill – much like a Leonardo da Vinci masterpiece. The task always begins with a blank canvas that many data professionals find intimidating. It’s not always clear where to start or how to ensure you get the results you want. Whether you are trying to create a simple report, a dazzling dashboard, or tell an influential data story, use the following elements to enable your inner report artist to bloom.
There are three parts to effective and useful data communications: understand the business need, understand your audience, and have a clear and actionable message.
Before any data presentation begins, you must understand what question needs to be answered and why it is being asked. Often the business need may not be presented as an actual question but as an issue or even just what the business user fear is going to happen. It’s your job to translate the concerns and questions of the business into something meaningful.
When you have domain knowledge, you can state the problem in a measurable way. Domain knowledge refers to understanding key terms, common metrics, and standard workflows for that specific business. Domain knowledge allows you to know why the question is essential as well as to weed out irrelevant information.
With domain knowledge, you can empathize with the business users and consider how they see the world. Your answers and insights are more valuable to them because it solves their problem.
Your audience is who is receiving your data communication. Your audience determines the depth of your data communication and the presentation method.
There are five audiences for communications shown in the chart below. Each audience type is based on the way they will consume the data. The following figure shows each audience type along with what they will expect from your data presentation.
If you have multiple audience types viewing your presentation, then focus the content on the highest decision maker present. You should level set with the audience, in the beginning, to ensure everyone is on the same page. A simple introduction that explains the purpose and a brief history may be enough.
Hans Rosling did an excellent job presenting data to a mixed audience in his Let My Dataset Change Your Mindset Ted talk. When you watch the video, you’ll notice that Rosling never talks down to his audience. Instead, he explains the data set, the parts of the chart, and lastly interprets how it has changed over time. Even someone with low data literacy can understand his message. With the new understanding, the audience can make decisions about what action they want to take.
When working with an audience, put yourself in their place. For each audience listed in the above figure, generate the questions you think they would have about your data and your insights.
Once you understand the audience, you can review the data set for insights. Some questions are easier to answer, and the message may even be expected. It is easy to demonstrate how many trouble tickets were opened the previous week. To get value from the data, you need to reveal surprising insights.
For example, think about the technical service manager’s job. A standard report for them may contain trouble ticket trends and team response times. After reviewing the data, your message is that three team members are more likely to send tickets to second-level support. These team members have less time on the job, so you suspect a knowledge gap.
Your message then becomes: provide training for better outcomes. However, that tired message is repeated often and doesn’t have any teeth. What if instead, you were able to say, “You can reduce ticket resolution time by 30% if you better train your new employees?” This message has a stated benefit and an actionable message for your audience.
A good data visualization communicates your message quickly. Based on your audience, you will have better ideas about what techniques you can use. A general audience may do better with a simple bar chart, geographical element, or a line chart. Experts can handle bubble plots or more advanced ways of looking at the data.
The most common reason data visualizations are not clear is the author didn’t understand the message. Thus, the data meaning is unclear or even hidden. The author didn’t consider what question the audience was asking. You can spot these visualizations when you see someone spending a long time studying them to understand what they mean.
Creating data communications is a combination of considering what you want to say, why you are saying it, and to whom you are speaking. While this seems like a simple concept, it can be as daunting as an empty canvas to a beginning artist.
If this content was useful, use the Email Signup form (on the top right) to get the Zencos newsletter. Each month we talk about topics of interest to data professionals. You can unsubscribe at any time, and we never share your email address.