Imagine being told that there is a day in the year on which you stop being paid, while others still pick up a wage until New Year’s Eve. The gender pay gap map converted a percentage difference between male and female earnings into something instantly recognisable and so easy to understand people could point to it on a calendar.In addition, it showed the vast difference in earnings across the country, calculating the “equal pay day” where you work.The Annual Survey of Hours and Earnings, published by the Office for National Statistics, provided the percentage difference in male and female full time hourly earnings.To make this relevant and relatable, the BBC England Data Unit took that difference in median earnings for male and female workers in each local authority area then worked out the day on which it was equivalent to one or other gender no longer being relative to the other.This was then visualised on a map of the UK using Carto and a quick-to-understand key. It allowed the audience to personalise the content and see the scale of the difference relative to their own area. Handy tooltips gave them all the key figures in a quick and simple to understand format.Of course, the data alone was not the full story and the piece also brought in expert opinion and the case study of an ongoing equal pay battle between Asda and current and former workers.This vital context explained how the gap changed relating to different industries and the proportion of male and female workers at different levels of the pay scale.The piece occupied a front page slot on the BBC News website for most of the day and was shared on social media by people who were interacting with the data visualisation.
What makes this project innovative?
Many stories have addressed the issue of the gender pay gap, looking at the percentage difference in earnings between men and women.This project went beyond that in order to bring the issue home to a general audience.By converting the percentages for each area of the country into the number of days in a year (a number out of 365), we were able to work back to calculate the date on which women effectively stopped earning relative to men (or vice versa in a limited number of cases).This was an important step that engaged the audience with the story and furnished the audience with all the data they needed to see, not just a percentage difference but the pounds and pence figure that everyone would be able to understand and immediately grasp in terms of their own personal circumstances.By plotting these differences on a map we were able to show how people were affected in the area where they work and how people working in neighbouring areas measured up.It meant people did not need to know a postcode or another identifying aspect of their own circumstances in order to be able to travel the country and examine for themselves in easy to understand terms how big an issue gender pay inequality is.
What was the impact of your project? How did you measure it?
Using Chartbeat we were able to see people spent longer than normal in the story, while our own internal data gathering revealed almost half a million page views on the day.The map was shared widely on social media, which continued to bring visitors to the website for days afterwards, even after it was no longer visible on front pages and indexes on the BBC News website.
Source and methodology
The BBC England Data Unit used the Annual Survey of Hours and Earnings published by the Office for National Statistics and analysed the full time hourly median earnings, excluding overtime, for male and female workers in each local authority area to get the percentage gap between their earnings.We then calculated the dates on which the average female worker in each area effectively stops being paid, relative to male workers, because of the gap in their earnings.
The map was made using Carto. The heat mapping and colour palette were adapted using CSS.Data was uploaded in Excel along with KML shapefiles for local authority area boundaries, obtained from the Office for National Statistics.
Paul Bradshaw, Becca Meier, Daniel Dunford, Nassos Stylianou, Sue Bridge.