Data Viz Done Right

June 4, 2018

Makeover Monday: The UK Gender Pay Gap Across Salary Bands

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This week's data comes from the UK government and more specifically the Valuation Office Agency. I was alerted of this data set by Aisling Roberts, who had written a great article on LinkedIn that questions whether people will actually take any actions based on the data.

Let's start with this viz from the official report:


What works well?

  • The symbols make it clear this about females and males.
  • The BAN in the middle tells us what the bonus pay gap is.

What could be improved?

  • Both icons are filled to the same level, making it look like there is no bonus pay gap. These should be filled to the actual values for each gender.
  • The icons don't add much value.
  • The title could tell us a whole lot more.
  • There's no source listed nor no timeframe.
  • The gridlines aren't evenly spaced between 0% and 50%.

I must admit, this is a tough data set. Hopefully the explanations I wrote on data.world provide sufficient context. I found it most useful to look at a specific company and look those values up in the data provided to ensure I understood what it means. Given that I found the data overwhelming, I decided to focus on the pay bands since that's what Aisling focused on in her article. 

From there, I started to build lots of charts, but found the number of companies overwhelming. Therefore, I decide to limit the data to those companies located in the City of London (i.e., those with a postcode that starts with EC). I also knew I need to do some data prep so that I could compare females and males in each pay band more easily. I turned to Tableau Prep for this.

The flow works like this:

  1. Remove columns that aren't needed
  2. Splitting the data up into two streams, one for the female columns and one for the male columns.
  3. Pivot the data so that the pay bands are listed down instead of across
  4. Add a column for the gender
  5. Union the data back together
  6. Export to an extract

Pretty straightforward and this short amount spent prepping the data made the gender comparison significantly easier. I first wanted to understand how the median proportion of females and males in each pay band by the size of the company with a City of London total (NOTE: the total only represents companies that reported).

Click on the image for the interactive version.


This simple view makes it incredibly evident that the proportion of females declines as the pay band increases. Males would be the inverse. It's particularly stark in the largest organizations. In the City of London, there are only three employers in that range (British Telecom, Royal Mail, and Sainsbury's Supermarket).

The heat map helped give me an overview of the data and felt ready to create something more detailed. This time I wanted to look at all companies together by gender by pay band compared to the overall median for each gender. I also wanted to provide the user with the option to choose a specific company. When they do, that company gets highlighted.

Click on the image for the interactive version.

What first struck me in this view is the clear, overwhelming patterns down and to the right for women. This gave me a great impression for how big the gender pay gap problem is.

The gender pay gap is not a myth. These are facts, facts that show women are underrepresented at higher salary levels. Don't let this discussion get lost. Check out your own company. How are they performing? Ask them to share the data within your organization. Transparency is a key to fixing this discrepancy.

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