Civil Service Statistics data browser (2023)

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

Status	Year	Sex	Parent_department	Ethnicity	Organisation	Headcount	FTE	Mean_salary	Median_salary
In post	2023	Female	Attorney General’s Departments	Asian	Attorney General’s Office	[c]	[c]	[c]	[c]
In post	2023	Female	Attorney General’s Departments	Asian	Crown Prosecution Service	595	545	39450	32660
In post	2023	Female	Attorney General’s Departments	Asian	Government Legal Department	230	210	50670	52020
In post	2023	Female	Attorney General’s Departments	Asian	HM Crown Prosecution Service Inspectorate	[c]	[c]	[c]	[c]
In post	2023	Female	Attorney General’s Departments	Asian	Serious Fraud Office	30	30	45430	42110
In post	2023	Female	Attorney General’s Departments	Black	Attorney General’s Office	[c]	[c]	[c]	[c]
In post	2023	Female	Attorney General’s Departments	Black	Crown Prosecution Service	305	290	39810	30560
In post	2023	Female	Attorney General’s Departments	Black	Government Legal Department	140	135	43480	38860
In post	2023	Female	Attorney General’s Departments	Black	HM Crown Prosecution Service Inspectorate	[c]	[c]	[c]	[c]
In post	2023	Female	Attorney General’s Departments	Black	Serious Fraud Office	20	15	[c]	[c]
In post	2023	Female	Attorney General’s Departments	Mixed	Attorney General’s Office	[c]	[c]	[c]	[c]
In post	2023	Female	Attorney General’s Departments	Mixed	Crown Prosecution Service	155	140	40140	32980
In post	2023	Female	Attorney General’s Departments	Mixed	Government Legal Department	60	60	57510	52790
In post	2023	Female	Attorney General’s Departments	Mixed	HM Crown Prosecution Service Inspectorate	[c]	[c]	[c]	[c]
In post	2023	Female	Attorney General’s Departments	Mixed	Serious Fraud Office	10	10	[c]	[c]
In post	2023	Female	Attorney General’s Departments	Other ethnicity	Attorney General’s Office	[c]	[c]	[c]	[c]
In post	2023	Female	Attorney General’s Departments	Other ethnicity	Crown Prosecution Service	40	35	38590	35550
In post	2023	Female	Attorney General’s Departments	Other ethnicity	Government Legal Department	30	25	[c]	[c]
In post	2023	Female	Attorney General’s Departments	Other ethnicity	HM Crown Prosecution Service Inspectorate	[c]	[c]	[c]	[c]
In post	2023	Female	Attorney General’s Departments	Other ethnicity	Serious Fraud Office	[c]	[c]	[c]	[c]

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 2023-07-28, 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).
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.
Sex	Self reported sex.
	"Unknown" accounts for employees who were recorded with an unknown sex.
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).