They have the data already. It's what they used to prepare the report.
So they need to look at that and analyse it.
I'd do a bubble graph for each band showing the distribution of pay of white employees and ethnic minority employees.
That will show 2 things
The number of different employees - you'd just use 2 colours
The spread of data. You'd probably see the employees distributed randomly across the pay band
This is an example although clearly it's not pay
Imagine orange is female and blue is male
You can see there are far more females than males.
A lot of women earn $80m
The rest earn $65m
As for the men, most earn $40m
There's some poor men who earn $25m
And a similar amount who earn $50m
Clearly there's something going on here.
Are the men being discriminated against?
Are the women just better at their job?
Are they doing different jobs so the women just happen to be doing a role that pays more?
I work in data analysis. It's so easy to get all these variables so you can then dice and slice to see what's going on,
I'd collect
Name (but that should be anonymised and given a number so only HR knows who it is)
Gender (that's going to annoy people)
Sex (assigned at birth)
Age
Employed since
Time at that level
Pay level
Last pay rise
Bonuses
Manager
Last assessment
Last promotion
Competency grading
Department
Job Role
Ethnicity
Disabled
LGBT
Working Class background
Most of those things will already be available on the HR systems so you just link the 2 systems
Then you can ask
How do the departments compare in pay levels?
Do any departments seem to be under or over represented with particular groups?
In a department, are managers doing assessments and are they being fair with awarding pay rises and bonuses?
eg Does Bob in car sales only employ males and then just gives bonuses to his mates?
Is there any issues you can see in pay distribution?
Is anyone just coasting along without wanting promotion?
Is anyone being looked over? eg At the company for years but has only had a few pay rises?
Is Senior management top heavy with Straight white middle class males ?
That's what a good data analyst can do.
Make sure the data is collected well, there's no gaps in the data (many people refuse to say their sexuality or gender identification), clean the data up and then analyse it.
If you did the Seniior Leadership LGBT pay at the BBC, I bet you'd just see a few LGBT people in there and can identify their pay.
How it's presented is entirely up to the agenda of the company.
I didn't get a job as a school data manager because they asked me to analyse the SEN performance in a class and they only had 3 pupils, I said that's too small a sample size to draw any conclusions.
Simple numbers and simple averages don't tell you anything and can really deceive you. I hate using them
When I first started my role, we were surveying clients. The Senior Staff got very excited with an 80% satisfaction rating and were desperate to share it on social media. I had to tell them that it meant nothing as we only interviewed 20 people. I said we should wait till the end of the year to get enough people or do a rolling 12 month mean. What I did show them was the bubble graph so we could see we had a good amount of people who were very satisfied and about 20% who were extremely dissatisfied. We then looked at those people to see what we were doing poorly
I changed their attitude to data analysis