Civil Service Statistics data browser (2023)

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

Status Year Sex Parent_department Disability Ethnicity Headcount FTE Mean_salary Median_salary
In post 2023 Female Attorney General’s Departments Declared disabled Asian 90 80 42590 36530
In post 2023 Female Attorney General’s Departments Declared disabled Black 60 55 41090 35550
In post 2023 Female Attorney General’s Departments Declared disabled Mixed 30 25 [c] [c]
In post 2023 Female Attorney General’s Departments Declared disabled Other ethnicity 10 10 [c] [c]
In post 2023 Female Attorney General’s Departments Declared disabled Undeclared 15 15 [c] [c]
In post 2023 Female Attorney General’s Departments Declared disabled Unknown 30 30 40600 30870
In post 2023 Female Attorney General’s Departments Declared disabled White 585 535 43390 38860
In post 2023 Female Attorney General’s Departments Declared non-disabled Asian 615 565 42870 40800
In post 2023 Female Attorney General’s Departments Declared non-disabled Black 335 320 41440 34000
In post 2023 Female Attorney General’s Departments Declared non-disabled Mixed 160 145 45600 49050
In post 2023 Female Attorney General’s Departments Declared non-disabled Other ethnicity 40 35 44270 45390
In post 2023 Female Attorney General’s Departments Declared non-disabled Undeclared 70 65 47160 51270
In post 2023 Female Attorney General’s Departments Declared non-disabled Unknown 195 175 44410 40540
In post 2023 Female Attorney General’s Departments Declared non-disabled White 3370 3060 45550 49050
In post 2023 Female Attorney General’s Departments Undeclared Asian 15 15 [c] [c]
In post 2023 Female Attorney General’s Departments Undeclared Black 10 10 [c] [c]
In post 2023 Female Attorney General’s Departments Undeclared Mixed 5 5 [c] [c]
In post 2023 Female Attorney General’s Departments Undeclared Other ethnicity [c] [c] [c] [c]
In post 2023 Female Attorney General’s Departments Undeclared Undeclared 20 20 [c] [c]
In post 2023 Female Attorney General’s Departments Undeclared Unknown [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 2023-07-27, 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.
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.
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).