Civil Service Statistics data browser (2023)

Data preview: All civil servants / Function_of_post / Region_london / Sex / Organisation

Status Year Function_of_post Region_london Sex Organisation Headcount FTE Mean_salary Median_salary
In post 2023 Analysis London Female Active Travel England [c] [c] [c] [c]
In post 2023 Analysis London Female Advisory, Conciliation and Arbitration Service [c] [c] [c] [c]
In post 2023 Analysis London Female Attorney General’s Office [c] [c] [c] [c]
In post 2023 Analysis London Female Building Digital UK 5 5 [c] [c]
In post 2023 Analysis London Female Cabinet Office (excl. agencies) [c] [c] [c] [c]
In post 2023 Analysis London Female Central Civil Service Fast Stream 35 35 30910 30130
In post 2023 Analysis London Female Charity Commission [c] [c] [c] [c]
In post 2023 Analysis London Female Companies House [c] [c] [c] [c]
In post 2023 Analysis London Female Competition and Markets Authority 40 40 66500 58050
In post 2023 Analysis London Female Department for Business, Energy and Industrial Strategy (excl. agencies) 75 75 44040 36230
In post 2023 Analysis London Female Department for Digital, Culture, Media and Sport (excl. agencies) 45 45 52210 56760
In post 2023 Analysis London Female Department for Education (excl. agencies) 130 120 49660 46600
In post 2023 Analysis London Female Department for International Trade 100 95 47180 41750
In post 2023 Analysis London Female Department for Levelling Up, Housing and Communities (excl. agencies) 85 85 48360 54630
In post 2023 Analysis London Female Department for Transport (excl. agencies) 140 135 52020 55740
In post 2023 Analysis London Female Department for Work and Pensions (excl. agencies) 115 105 49080 43760
In post 2023 Analysis London Female Department of Health and Social Care (excl. agencies) 40 35 55980 54690
In post 2023 Analysis London Female Driver and Vehicle Standards Agency [c] [c] [c] [c]
In post 2023 Analysis London Female Education and Skills Funding Agency [c] [c] [c] [c]
In post 2023 Analysis London Female Food Standards Agency 10 10 [c] [c]
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 2023-07-28, 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).
Organisation Executive Agencies, Ministerial and Non-Ministerial Departments, Crown Non-departmental Public Bodies.
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".
Function_of_post Functions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
Welsh Government and Royal Fleet Auxiliary did not report any functions information for their employees.
Of the 20 bodies under the Scottish Government, 16 did not report any functions information for their employees.
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).