Civil Service Statistics data browser (2023)

Data preview: All civil servants / Ethnicity / Parent_department / Region_london / Organisation

Status Year Ethnicity Parent_department Region_london Organisation Headcount FTE Mean_salary Median_salary
In post 2023 Asian Attorney General’s Departments London Attorney General’s Office [c] [c] [c] [c]
In post 2023 Asian Attorney General’s Departments London Crown Prosecution Service 385 360 41490 33130
In post 2023 Asian Attorney General’s Departments London Government Legal Department 315 300 49960 52020
In post 2023 Asian Attorney General’s Departments London HM Crown Prosecution Service Inspectorate [c] [c] [c] [c]
In post 2023 Asian Attorney General’s Departments London Serious Fraud Office 50 50 46290 42110
In post 2023 Asian Attorney General’s Departments Outside London Crown Prosecution Service 455 425 38700 35000
In post 2023 Asian Attorney General’s Departments Outside London Government Legal Department 20 20 [c] [c]
In post 2023 Asian Attorney General’s Departments Outside London HM Crown Prosecution Service Inspectorate [c] [c] [c] [c]
In post 2023 Asian Attorney General’s Departments Overseas Crown Prosecution Service [c] [c] [c] [c]
In post 2023 Asian Cabinet Office London Cabinet Office (excl. agencies) 340 335 47990 43090
In post 2023 Asian Cabinet Office London Central Civil Service Fast Stream 140 140 30690 30130
In post 2023 Asian Cabinet Office London Crown Commercial Service 10 10 [c] [c]
In post 2023 Asian Cabinet Office London Government Commercial Organisation 50 50 73270 66270
In post 2023 Asian Cabinet Office London Government Property Agency 10 10 [c] [c]
In post 2023 Asian Cabinet Office Outside London Cabinet Office (excl. agencies) 80 75 38690 33020
In post 2023 Asian Cabinet Office Outside London Central Civil Service Fast Stream 45 45 31120 30130
In post 2023 Asian Cabinet Office Outside London Crown Commercial Service 20 20 [c] [c]
In post 2023 Asian Cabinet Office Outside London Government Commercial Organisation 25 25 [c] [c]
In post 2023 Asian Cabinet Office Outside London Government Property Agency 30 30 37750 33970
In post 2023 Asian Cabinet Office Unknown Cabinet Office (excl. agencies) 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 2023-07-27, 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).
Parent_department Government Department, total figures for both Ministerial and Non-Ministerial Departments include all of their Executive Agencies.
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".
Ethnicity Self reported ethnicity. "Undeclared" accounts for employees who have actively declared that they do not want to disclose their ethnicity and "Unknown" accounts for employees who have not made an active declaration about their ethnicity.
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).