Makeover Monday – week 14, 2017: Millions of UK workers at risk of being replaced by robots

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A couple of weeks ago, Nick Bignell sent us this article on the Guardian’s website as a suggestion for Makeover Monday. What’s ‘different’ about this makeover is that the original chart is actually really good. Why did I choose it for Makeover Monday anyway?

Well, there is always something to improve and I’m curious to see how our community will approach the dataset and tell the story differently. I also like the article, which provides a lot of context for Makeover Monday participants and there is even a video on the topic for those who don’t like to read or simply can’t be bothered…

So let’s look at the original chart….

originalWhat I like about it:

  • Great mobile friendly layout
  • Nice simple colour scheme
  • Simple viz that shows 2 percentage figures in comparison for each industry
  • The title, while being long, outlines the key findings of the author and gives me one aspect of the argument to focus on
  • The bold titles for industries mentioned in the title help remind me of the authors findings
  • The industry names are nice and simple
  • The source is clearly stated and includes a disclaimer
  • Ordering industries by the risk of jobs being automated is relevant given the content of the article

What I don’t like about it:

  • The grey bars are a bit distracting for me, as they don’t add anything beyond row banding because they don’t go to 100%
  • The colour legend should state the job automation risk first in my opinion as this measure determines the sort order of the following chart and is the focus of the article
  • I would have liked a short and concise title and the current title more as a subtitle or description
  • The measure ‘job automation at potential high risk’ is a bit tricky to understand, because ‘high risk’ is defined as 70% or above, so what this measure shows (I think) is that, for example, at a total level, 30% of jobs are more than 70% likely to face automation. Percentage of percentage ain’t an easy way to describe something that you want everyone across the population to understand.

What did I do?

(Click the image to view the viz on Tableau Public)

  • my viz 2.pngGiven all the context available in the article, the PwC report and the video, my focus this week was on creating a story while keeping the mobile-friendly format
  • With the story came the need for some text boxes to provide commentary on the numbers and charts. I also wanted to bring in my own view to some extent and move away from the dramatic ‘30% of jobs could be lost’ approach by putting the numbers into perspective
  • Most of my time was taken up by formatting as I tried to figure out how to layout the story to produce a natural flow from top to bottom and show interesting information at the same time through a couple of charts
  • The vertical bar chart looks at the overall situation for the whole employment market, while the horizontal bar chart focuses on the industry-specific results, sorted by the impact on employment given each industry’s share of the overall employment market
  • For colours I chose an aubergine/purple/beige/grey palette. Aubergine and beige were used for the whole market, while purple plus a lighter shade depict the two most affected industries (>10% share of employment market) and grey with a lighter shade were used for the remaining industries (<10% share of employment market)
  • Near the end of my story I added a bit of my own opinion as well as a quote from the PwC report to further underline my statements
  • I also included a short hyperlink to the source and my Twitter account. (I explain how to do this in this article)

 

 

 

 

 

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