Civil Service Statistics data browser (2023)

Data preview: All civil servants / Sex / Disability / Parent_department / Profession_of_post

Status	Year	Sex	Disability	Parent_department	Profession_of_post	Headcount	FTE	Mean_salary	Median_salary
In post	2023	Female	Declared disabled	Attorney General’s Departments	Commercial	[c]	[c]	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Communications	[c]	[c]	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Corporate Finance	[c]	[c]	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Counter Fraud	10	10	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Digital, Data and Technology	10	10	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Finance	20	20	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Human Resources	25	25	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Intelligence Analysis	[c]	[c]	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Internal Audit	[c]	[c]	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Knowledge and Information Management	5	5	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Legal	380	345	56840	56450
In post	2023	Female	Declared disabled	Attorney General’s Departments	Operational Delivery	320	290	28390	26900
In post	2023	Female	Declared disabled	Attorney General’s Departments	Other	[c]	[c]	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Policy	20	15	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Project Delivery	5	5	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Property	[c]	[c]	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Security	[c]	[c]	[c]	[c]
In post	2023	Female	Declared disabled	Attorney General’s Departments	Statistics	[c]	[c]	[c]	[c]
In post	2023	Female	Declared disabled	Cabinet Office	Commercial	115	110	57660	56000
In post	2023	Female	Declared disabled	Cabinet Office	Communications	10	10	[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 2023-07-29, 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.
Profession_of_post	Professions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
	Of the 20 bodies under the Scottish Government, 16 did not report any professions information for their employees.
Sex	Self reported sex.
	"Unknown" accounts for employees who were recorded with an unknown sex.
Disability	Self reported disability.
	"Undeclared" accounts for employees who have actively declared that they do not want to disclose their disability status and "Unknown" accounts for employees who have not made an active declaration about their disability status.
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).