Civil Service Statistics data browser (2023)

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

Status Year Sex Sexual_orientation Profession_of_post Region_london Headcount FTE Mean_salary Median_salary
In post 2023 Female Heterosexual / straight Commercial London 570 555 56030 53120
In post 2023 Female Heterosexual / straight Commercial Outside London 2435 2310 42480 38470
In post 2023 Female Heterosexual / straight Commercial Overseas 10 10 [c] [c]
In post 2023 Female Heterosexual / straight Commercial Unknown [c] [c] [c] [c]
In post 2023 Female Heterosexual / straight Communications London 770 740 49610 46450
In post 2023 Female Heterosexual / straight Communications Outside London 965 900 38870 37590
In post 2023 Female Heterosexual / straight Communications Overseas [c] [c] [c] [c]
In post 2023 Female Heterosexual / straight Communications Unknown [c] [c] [c] [c]
In post 2023 Female Heterosexual / straight Corporate Finance London 15 15 [c] [c]
In post 2023 Female Heterosexual / straight Corporate Finance Outside London 20 15 [c] [c]
In post 2023 Female Heterosexual / straight Counter Fraud London 675 625 35230 32520
In post 2023 Female Heterosexual / straight Counter Fraud Outside London 3090 2770 29580 28120
In post 2023 Female Heterosexual / straight Counter Fraud Unknown [c] [c] [c] [c]
In post 2023 Female Heterosexual / straight Digital, Data and Technology London 1235 1195 51540 49170
In post 2023 Female Heterosexual / straight Digital, Data and Technology Outside London 4320 4095 41380 38470
In post 2023 Female Heterosexual / straight Digital, Data and Technology Overseas [c] [c] [c] [c]
In post 2023 Female Heterosexual / straight Digital, Data and Technology Unknown 10 10 [c] [c]
In post 2023 Female Heterosexual / straight Economics London 405 390 52860 55020
In post 2023 Female Heterosexual / straight Economics Outside London 150 145 42750 38070
In post 2023 Female Heterosexual / straight Economics Overseas [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 2023-07-26, 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".
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.
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).