Civil Service Statistics data browser (2023)

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

Status Year Parent_department Profession_of_post Sex Region_london Headcount FTE Mean_salary Median_salary
In post 2023 Attorney General’s Departments Commercial Female London 5 5 [c] [c]
In post 2023 Attorney General’s Departments Commercial Female Outside London 15 15 [c] [c]
In post 2023 Attorney General’s Departments Commercial Male London 5 5 [c] [c]
In post 2023 Attorney General’s Departments Commercial Male Outside London 10 10 [c] [c]
In post 2023 Attorney General’s Departments Communications Female London 40 35 45040 40540
In post 2023 Attorney General’s Departments Communications Female Outside London 20 20 [c] [c]
In post 2023 Attorney General’s Departments Communications Male London 30 30 [c] [c]
In post 2023 Attorney General’s Departments Communications Male Outside London 10 10 [c] [c]
In post 2023 Attorney General’s Departments Corporate Finance Female London 5 5 [c] [c]
In post 2023 Attorney General’s Departments Corporate Finance Male London 5 5 [c] [c]
In post 2023 Attorney General’s Departments Counter Fraud Female London 95 95 43360 38480
In post 2023 Attorney General’s Departments Counter Fraud Male London 135 135 50430 43430
In post 2023 Attorney General’s Departments Digital, Data and Technology Female London 30 30 [c] [c]
In post 2023 Attorney General’s Departments Digital, Data and Technology Female Outside London 45 45 40310 35000
In post 2023 Attorney General’s Departments Digital, Data and Technology Male London 75 75 51980 46230
In post 2023 Attorney General’s Departments Digital, Data and Technology Male Outside London 55 55 41440 38940
In post 2023 Attorney General’s Departments Finance Female London 50 45 36920 31100
In post 2023 Attorney General’s Departments Finance Female Outside London 80 70 28270 26900
In post 2023 Attorney General’s Departments Finance Male London 45 45 42730 32890
In post 2023 Attorney General’s Departments Finance Male Outside London 60 60 32050 27440
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).
Parent_department Government Department, total figures for both Ministerial and Non-Ministerial Departments include all of their Executive Agencies.
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.
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).