Civil Service Statistics data browser (2023)

Data preview: All civil servants / Sex / Disability / Region_ITL3

Explore further: Parent_department, Organisation, Responsibility_level_grouped, Responsibility_level_ungrouped, Region_london, Region_ITL1, Region_ITL2, Profession_of_post, Function_of_post, Ethnicity, Sexual_orientation, Age

Status Year Sex Disability Region_ITL3 Headcount FTE Mean_salary Median_salary
In post 2023 Female Declared disabled Aberdeen City and Aberdeenshire 90 85 32610 28120
In post 2023 Female Declared disabled Angus and Dundee City 230 210 27760 28120
In post 2023 Female Declared disabled Antrim and Newtownabbey 5 5 [c] [c]
In post 2023 Female Declared disabled Ards and North Down 10 5 [c] [c]
In post 2023 Female Declared disabled Armagh City, Banbridge and Craigavon [c] [c] [c] [c]
In post 2023 Female Declared disabled Barking & Dagenham and Havering 80 70 33170 32520
In post 2023 Female Declared disabled Barnet 80 75 35970 32520
In post 2023 Female Declared disabled Barnsley, Doncaster and Rotherham 330 280 28500 28120
In post 2023 Female Declared disabled Bath and North East Somerset, North Somerset and South Gloucestershire 735 675 36700 33310
In post 2023 Female Declared disabled Bedford 80 70 31860 28480
In post 2023 Female Declared disabled Belfast 175 155 33410 29730
In post 2023 Female Declared disabled Berkshire 205 185 33880 31280
In post 2023 Female Declared disabled Bexley and Greenwich 130 120 32680 32520
In post 2023 Female Declared disabled Birmingham 1050 935 31280 28120
In post 2023 Female Declared disabled Blackburn with Darwen 40 35 30360 28120
In post 2023 Female Declared disabled Blackpool 655 570 29470 28120
In post 2023 Female Declared disabled Bournemouth, Christchurch and Poole 95 80 27470 28120
In post 2023 Female Declared disabled Bradford 240 200 27090 25830
In post 2023 Female Declared disabled Breckland and South Norfolk 40 35 29190 28120
In post 2023 Female Declared disabled Brent 50 45 33460 32520
Note: Data has been truncated to 20 rows, please download the data to view the remaining rows

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About: The Civil Service Statistics data browser is a pilot project by Cabinet Office to provide access to more detailed data on the Civil Service workforce from the Annual Civil Service Employment Survey. We welcome feedback or comments on this project, which can be addressed to civilservicestatistics@cabinetoffice.gov.uk

Notes: Summary figures are suppressed when information relates to less than 5 civil servants for FTE or Headcount, and less than 10 civil servants for median and mean salary (shown as [c]). Zero responses and salaries for less than 30 civil servants have been suppressed for GPDR special category data. FTE figures are not shown for entrants or leavers due to data quality concerns for these groups. Figures are rounded to the nearest 5, or £10 as appropriate.

Data source: All figures are aggregated from the Cabinet Office Annual Civil Service Employment Survey collection.

Version: Generated on 2023-07-26, with GIT d545f65.

Data column Description
Status Employment status of the civil servants.
In post - includes staff that were in post on the reference date (31 March).
New entrant CS - includes new entrants to the Civil Service over the year (1 April to 31 March).
Leaver CS - includes leavers from the Civil Service over the year (1 April to 31 March). This includes employees who have an Unknown leaving cause.
Leaver Dept. - includes leavers from the department over the year (1 April to 31 March), who did not leave the Civil Service.
Four organisations do not report when their employees first entered the Civil Service and so entrants data for these organisations is not available . These are as follows: Foreign Commonwealth and Development Office (excl. agencies), Foreign Commonwealth and Development Office Services, Scottish Forestry and Forest and Land Scotland. A further three organisations also could not provide entrants data in 2021. These are as follows: Department for International Development, Foreign and Commonwealth Office (excl. agencies) and Royal Fleet Auxiliary.
Year Year of data collection (as at 31 March).
Region_ITL3 Workplace postcode data are used to derive geographical information using the International Territorial Level (ITL) classification standard.
Following the UK’s withdrawal from the EU, a new UK-managed international statistical geography - International Territorial Levels (ITL) - was introduced from 1st January 2021, replacing the former NUTS classification. They align with international standards, enabling comparability both over time and internationally. To ensure continued alignment, the ITLs mirror the NUTS system. They also follow a similar review timetable - every three years.
ITL 3 divides into counties, unitary authorities, or districts in England (some grouped), groups of unitary authorities in Wales, groups of council areas in Scotland, groups of districts in Northern Ireland.
Sex Self reported sex.
"Unknown" accounts for employees who were recorded with an unknown sex.
Disability Self reported disability.
"Undeclared" accounts for employees who have actively declared that they do not want to disclose their disability status and "Unknown" accounts for employees who have not made an active declaration about their disability status.
Headcount Total number of civil servants (rounded to nearest 5).
FTE Total full-time equivalent (FTE) employment numbers (rounded to nearest 5).
FTE figures are not shown for entrants or leavers due to data quality concerns for these groups.
Mean_salary Average salary (mean, rounded to nearest £10). For part-time employees, salaries represent the full-time equivalent earnings, while for full-time employees they are the actual annual gross salaries.
These figures should be interpreted with caution when the total number of employees in a group is small, as they will tend to show more variability than larger groups (i.e. may be much higher or lower than can be explained by the data shown).
Median_salary Median salary (rounded to nearest £10). For part-time employees, salaries represent the full-time equivalent earnings, while for full-time employees they are the actual annual gross salaries.
These figures should be interpreted with caution when the total number of employees in a group is small, as they will tend to show more variability than larger groups (i.e. may be much higher or lower than can be explained by the data shown).