The same applies to visualization of data. Developers and analysts must understand that data will influence only if presented in the apt manner. Often few charts, spreadsheets or any other visualization is not the right way; a story is. We know that data has lot of potential. But with a good and expressive story line, it’s convincing and remarkable.
How to tell a story with your data?
When showcasing an application/dashboard don’t be dull and boring with unnecessary data or numbers. You need the viewer’s time and attention, so make sure it is interesting and persuasive. Just like writing or speaking, in data design you want to keep things simple, crisp and to the point. This makes the key content to be conveyed to the audience easily and effectively. Attention to detail and use of Big Data is important in today’s KPI-centric world but it need not be boring and lengthy.
A good visualization requires both common sense and imagination and tells a clear story in the most effective way.
1. Who are your audience? What does the targeted audience know about the topic? The visualization should be developed keeping in mind the knowledge of the users on the topic and also the interests of the audience. So what do different users expect?
- New users: straight on to the subject, but doesn’t want generalization or simplification
- Existing users: decent knowledge on the topic, but looking for an overall understanding and major insights
- Managers: most detailed, actionable understanding of the visual and relationships between visuals with access to detail on demand
- Analysts: more investigation and research, and less storytelling with great in-depth detail
- Executive: only has time to view the implications and conclusions of overall results
2. Make sure that the color and style you’re using aren’t introducing any visual impressions. Provide an appropriate reference for all the data showcased. This helps in better analysis and judgement.
For example, Red and Green are used as alert colors, using them inappropriately can cause confusion to the user. In the map below we can see the application designer has used red, which implies a negative impression to the user.
3. The ideal application / dashboard should be self-explanatory and user friendly. Arrange the visuals in such a way that the user gets a flow from the beginning till the end, with each of the visuals connecting each other in a proper understandable sequence. Continuity is the most important factor in a story – No one likes a story with abrupt ending and beginnings.
4. Symbols, icons and pictures are effective means of communication. In a glance, the viewer understands the message and can focus on its meaning. On the other hand, tables of data or numbers need people to look at each of them, relate it to other numbers and then reach to conclusions about the message. It is more time consuming and tedious. An apt visualization easily tells the story in a single glance. In the following dashboard, the alerts convey the performance of different states. The trends of various KPI’s helps the user to understand the performance of the selected states.
5. Last but not the least take care to explain the data, not just beautify the visuals. Maybe there are even better ways to express the story told by the data. The following dashboard shows different types of visualization for different metrics. For example, use a Line chart for trend, use a Pie or Donut chart to show percentage values.
In real-life, stress is often placed on solving big problems. However, simple stories are often the most successful. Some people complicate things to showcase their brilliance but you don’t understand anything they try to express. Real brilliance is conveying a complex problem in easy and understandable form. So, focus less on the data, and more on what the data should express about the problems that matter the most for the audience.
By the proper use of data, understanding our audience requirement and with a good story we can create meaningful and powerful dashboards or applications that influence and engage the audience to get actionable insights on the problems.
Source : http://visualbi.com/blogs/dashboards/storytelling-through-data/