Provide Feedback with others
To refine and perfect my data communications, I responded to a feedback request from the storytelling WITH data community. The requester posted a real-life example extracting from the annual report of an insurance authority. He asked us to provide more ideas to generate a suitable graph, in order to link with the commentary given by the original graph, thereby providing us data to build a new visual.
Original graph
Based on the original graph and its commentary above, I assumed that the takeaways were the increase/ decrease growths in 2019. Thus, I believed that data could be visualized in different ways and I therefore made three different versions.
Version 1
The version 1 was built from the original graph. In the original graph, I liked how the bar height showed the GWP gaps between different years, yet found that colors were confusing and the x-axis (business) was disordered. Thus, I changed the bar colors, ordered the x-axis (business) by HK$, and kept annotations for only 2019 data. Also, in the original graph, when the GWP gaps between different years were small, we could hardly interpret it. Therefore, to solve the problem, I used blue and red to distinguish between increase and decrease.
Version 2
Then, I changed the chart type and created version 2. As can be seen in version 2, I kept only 2019 data, ordered x-axis (business) by growth, and used blue and red bars to distinguish between increase and decrease. Therefore, audiences could clearly view an increase or decrease in 2019 GWP in different major lines of businesses. However, in this graph, audiences would not be able to view HK$, missing some information from the original graph.
Version 3
Lastly, I made version 3, which is a slope graph. I split the business lines into two graphs since the range of the HK$ is wide. To be more specific, businesses on the left have GWP over 10000 HK$, while businesses on the right have GWP ranges from 2000 to 11000 HK$. I used blue and red to emphasize increase and decrease in 2019 and shaded other years’ data into grey. Furthermore, in version 3, I kept HK$ to allow my audiences to review, and let the two graphs have the same y-axis range and increments to allow audiences to compare the depth of slope in two graphs without bias.
After asking for feedback from others, one of the audience members said she likes version 3 since the slope is more intuitive to understand, and as for me, I like version 1 since it is clean and clear. So far, I used the general title in the graphs, so I suggested the requester of the original post could put his key takeaway instead. For instance, “Property Damage has the highest GWP increase in 2019”
Overall, this is an example showing that data can be visualized in different ways, depending on which information we want to deliver and which data story we want to tell.
Thank you for reading 😊
See the original post of the requester: How can we deliver the key messages ?