Don’t simply show all the data. Instead show the most useful data to make an informed decision.
As testers we explore. From our explorations we may end up with a lot of data of which only some of them are interesting to be shared. When we are at the point of communicating about our exploration to our audience, we need to figure out
- … what might be noteworthy or interesting to highlight
- … what is that specific thing that needs to be conveyed
- … what context would be essential
Once we figure these out, we need to consider how to
- … show our data in a way that will be easy for our audience to understand.
- … turn our data into useful information that can be used to make a decision
This requires iterating and looking at our data in a number of different ways and choosing an appropriate visual.
I recently read the book Storytelling with Data by Cole Nussbaumer Knaflic (@storywithdata) which is a must read for anyone who wants to get better in communicating about their data. In this blog post, I would like to share the top 3 lessons I took away from the book to apply in my job as a tester.
Lesson 1: Choose an appropriate visual
By considering the tools or resources you have at your disposal create a visual that is easy for the audience to read and take back the key message.
Cole explains with examples about when to use simple text, tables, heat maps or charts since it is very important to choose the right way to display your data.
If your data has only a few interesting numbers to be conveyed a table or graph is not needed. Simple text can be a great way to convey the message. With a few supporting words, the numbers should be made prominent to clearly make your point.
However, when you have more data that you want to show, a table or graph is a better option.
Tables interact with our verbal system which is why we read tables. Therefore,
- tables can be a good option if multiple different units of measure needs to be communicated
- tables can be a bad option to be used in a live presentation
To reduce reader’s cognitive load, color saturation can be used to provide visual cues via a heat map. This would help in finding the potential points of interest quickly.
Graphs interact with our visual system. Therefore, it is faster to process the information from a graph than from a table.
Lesson 2: Keep it simple
To make the important message from your exploration data stand out in your report, any data that isn’t adding enough informative value needs to be removed. Eliminating the unnecessary reduces the cognitive load on the audience. This makes the transmission of the important message to your audience easier.
In the book, Cole introduces the Gestalt Principles of Visual Perception and provides practical examples of how these principles can be leveraged in data visualizations.
Lesson 3: Focus your audience’s attention
Cole demonstrates how to leverage preattentive attributes such as size, colour, added marks, and spacial position
- as visual clues to the audience about what’s important.
- to provide a visual information hierarchy to make it clear to the audience how they should interact with the provided information.
Some of her tips for highlighting the important items are:
- eliminate distractions
- use labelling well
- leverage white space.
The above 3 lessons are some of my favorites which I could implement in my workplace straight away. Lessons in the book Storytelling with Data by Cole Nussbaumer Knaflic are very helpful in turning our data into useful information for decision-making. I would highly recommend reading the book for learning about the various creative ways to walk your audience through any specific data message for them to take an informed decision.
- Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic