Civil Service Statistics data browser (2022)

Data preview: All civil servants / Region_ITL3 / Sex / Region_ITL1 / Region_ITL2

Status Year Region_ITL3 Sex Region_ITL1 Region_ITL2 Headcount FTE Mean_salary Median_salary
In post 2022 Aberdeen City and Aberdeenshire Female Scotland North Eastern Scotland 970 885 32990 27940
In post 2022 Aberdeen City and Aberdeenshire Male Scotland North Eastern Scotland 965 935 40580 35000
In post 2022 Angus and Dundee City Female Scotland Eastern Scotland 1280 1170 27460 26110
In post 2022 Angus and Dundee City Male Scotland Eastern Scotland 805 780 27090 23230
In post 2022 Antrim and Newtownabbey Female Northern Ireland Northern Ireland 65 60 29400 22500
In post 2022 Antrim and Newtownabbey Male Northern Ireland Northern Ireland 140 140 24730 20560
In post 2022 Ards and North Down Female Northern Ireland Northern Ireland 65 60 30480 25790
In post 2022 Ards and North Down Male Northern Ireland Northern Ireland 175 175 25950 21060
In post 2022 Armagh City, Banbridge and Craigavon Female Northern Ireland Northern Ireland 15 15 [c] [c]
In post 2022 Armagh City, Banbridge and Craigavon Male Northern Ireland Northern Ireland 5 5 [c] [c]
In post 2022 Barking & Dagenham and Havering Female London Outer London - East and North East 440 390 31330 31060
In post 2022 Barking & Dagenham and Havering Male London Outer London - East and North East 255 245 32180 31060
In post 2022 Barnet Female London Outer London - West and North West 1135 1045 38240 32330
In post 2022 Barnet Male London Outer London - West and North West 660 640 42050 36820
In post 2022 Barnsley, Doncaster and Rotherham Female Yorkshire and The Humber South Yorkshire 1930 1670 26760 26610
In post 2022 Barnsley, Doncaster and Rotherham Male Yorkshire and The Humber South Yorkshire 1195 1135 29430 27570
In post 2022 Bath and North East Somerset, North Somerset and South Gloucestershire Female South West (England) Gloucestershire, Wiltshire and Bath/Bristol area 5575 5165 35140 32990
In post 2022 Bath and North East Somerset, North Somerset and South Gloucestershire Male South West (England) Gloucestershire, Wiltshire and Bath/Bristol area 8170 8010 40080 38150
In post 2022 Bedford Female East of England Bedfordshire and Hertfordshire 485 435 29730 27570
In post 2022 Bedford Male East of England Bedfordshire and Hertfordshire 375 370 31880 28820
Note: Data has been truncated to 20 rows, please download the data to view the remaining rows

Download the data

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 2023-02-15, with GIT 71a76ea.

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.
Five 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, Defence Electronics and Components Agency, 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.
Organisation specific notes on status: In late June 2021 around 7,000 employees from Community Rehabilitation Companies were transferred in from the private sector to HM Prison and Probation Service, counting as entrants. HM Land Registry do not record where their departing employees transfer to and so are unable to identify those that transfer to another Civil Service department.
Year Year of data collection (as at 31 March).
Region_ITL1 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 1 divides into Wales, Scotland, Northern Ireland, and the 9 statistical regions of England.
Region_ITL2 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 2 divides into Northern Ireland, counties in England (most grouped), groups of districts in Greater London, groups of unitary authorities in Wales, groups of council areas in Scotland.
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.
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).