| Status | Year | Sex | Region_london | Region_ITL1 | Organisation | Headcount | FTE | Mean_salary | Median_salary |
|---|---|---|---|---|---|---|---|---|---|
| In post | 2022 | Female | London | London | Advisory, Conciliation and Arbitration Service | 105 | 95 | 41120 | 38670 |
| In post | 2022 | Female | London | London | Animal and Plant Health Agency | 50 | 50 | 35890 | 31800 |
| In post | 2022 | Female | London | London | Attorney General’s Office | 30 | 25 | [c] | [c] |
| In post | 2022 | Female | London | London | Cabinet Office (excl. agencies) | 3410 | 3345 | 47450 | 40600 |
| In post | 2022 | Female | London | London | Charity Commission | 55 | 50 | 43990 | 37910 |
| In post | 2022 | Female | London | London | Companies House | [c] | [c] | [c] | [c] |
| In post | 2022 | Female | London | London | Competition and Markets Authority | 395 | 375 | 58500 | 55860 |
| In post | 2022 | Female | London | London | Crown Commercial Service | 35 | 35 | 52380 | 43130 |
| In post | 2022 | Female | London | London | Crown Prosecution Service | 1175 | 1090 | 43220 | 39750 |
| In post | 2022 | Female | London | London | Defence Equipment and Support | 40 | 40 | 27260 | 23010 |
| In post | 2022 | Female | London | London | Defence Science and Technology Laboratory | [c] | [c] | [c] | [c] |
| In post | 2022 | Female | London | London | Department for Business, Energy and Industrial Strategy (excl. agencies) | 2590 | 2510 | 48700 | 46190 |
| In post | 2022 | Female | London | London | Department for Digital, Culture, Media and Sport | 985 | 960 | 47130 | 51730 |
| In post | 2022 | Female | London | London | Department for Education (excl. agencies) | 1335 | 1265 | 49600 | 53420 |
| In post | 2022 | Female | London | London | Department for Environment, Food and Rural Affairs (excl. agencies) | 1520 | 1455 | 44310 | 38900 |
| In post | 2022 | Female | London | London | Department for International Trade | 1230 | 1215 | 45220 | 39840 |
| In post | 2022 | Female | London | London | Department for Levelling Up, Housing and Communities (excl. agencies) | 1115 | 1085 | 48450 | 53130 |
| In post | 2022 | Female | London | London | Department for Transport (excl. agencies) | 1330 | 1290 | 48570 | 43670 |
| In post | 2022 | Female | London | London | Department for Work and Pensions (excl. agencies) | 6360 | 5790 | 33190 | 31060 |
| In post | 2022 | Female | London | London | Department of Health and Social Care (excl. agencies) | 1765 | 1700 | 47800 | 41920 |
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). |
| Organisation | Executive Agencies, Ministerial and Non-Ministerial Departments, Crown Non-departmental Public Bodies. |
| On 30 September 2021, the Ministry for Housing, Communities and Local Government changed it’s name to the Department for Levelling Up, Housing and Communities. | |
| On 1 October 2021, Public Health England was dissolved and its staff were transferred into either the newly created UK Health Security Agency, the NHS or the Department for Health and Social Care (excl. agencies). In addition to this the DHSC have been offboarding Test and Trace staff as well as onboarding the former PHE staff onto their system and so caution should be advised when interpretting data at DHSC as they are currently undertaking data cleansing exercises. PHE only includes entrants and leavers up to 30 September 2021 and UKHSA only inlcudes entrants and leavers from 1 October to 31 March 2022. | |
| Region_london | Workplace postcode data are used to derive geographical information using the International Territorial Level (ITL) classification standard. |
| Region_london groups the ITL classifications into “London”, “Outside London”: all UK regions excluding London, “Overseas”, and “Unknown”. | |
| 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. | |
| 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). |