Civil Service Statistics data browser (2023)

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

Status Year Sex Sexual_orientation Region_london Function_of_post Headcount FTE Mean_salary Median_salary
In post 2023 Female Heterosexual / straight London Analysis 1390 1325 50960 46600
In post 2023 Female Heterosexual / straight London Commercial 575 560 55930 54460
In post 2023 Female Heterosexual / straight London Communications 840 810 49560 45960
In post 2023 Female Heterosexual / straight London Counter Fraud 1150 1075 37830 32580
In post 2023 Female Heterosexual / straight London Debt 205 185 30190 26920
In post 2023 Female Heterosexual / straight London Digital, Data & Technology 1420 1375 49090 45150
In post 2023 Female Heterosexual / straight London Finance 1080 1035 49590 44250
In post 2023 Female Heterosexual / straight London Grants Management 25 25 [c] [c]
In post 2023 Female Heterosexual / straight London Human Resources 1590 1520 48890 43760
In post 2023 Female Heterosexual / straight London Internal Audit 65 60 51570 50810
In post 2023 Female Heterosexual / straight London Legal 2375 2210 52320 53390
In post 2023 Female Heterosexual / straight London No function 23715 22310 42510 36540
In post 2023 Female Heterosexual / straight London Project Delivery 2045 1950 53690 52760
In post 2023 Female Heterosexual / straight London Property 375 355 43360 39020
In post 2023 Female Heterosexual / straight London Security 460 440 44810 40250
In post 2023 Female Heterosexual / straight London Unknown 605 580 47140 41950
In post 2023 Female Heterosexual / straight Outside London Analysis 1850 1720 41040 39290
In post 2023 Female Heterosexual / straight Outside London Commercial 2215 2100 42510 39040
In post 2023 Female Heterosexual / straight Outside London Communications 880 820 38710 37300
In post 2023 Female Heterosexual / straight Outside London Counter Fraud 5030 4525 31890 28130
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).
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.
Sexual_orientation Self reported sexual orientation.
"Undeclared" accounts for employees who have actively declared that they do not want to disclose their sexual orientation and "Unknown" accounts for employees who have not made an active declaration about their sexual orientation.
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).