Civil Service Statistics data browser (2023)

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

Status Year Region_london Parent_department Ethnicity Profession_of_post Headcount FTE Mean_salary Median_salary
In post 2023 London Attorney General’s Departments Asian Commercial [c] [c] [c] [c]
In post 2023 London Attorney General’s Departments Asian Communications [c] [c] [c] [c]
In post 2023 London Attorney General’s Departments Asian Corporate Finance [c] [c] [c] [c]
In post 2023 London Attorney General’s Departments Asian Counter Fraud 15 15 [c] [c]
In post 2023 London Attorney General’s Departments Asian Digital, Data and Technology 20 20 [c] [c]
In post 2023 London Attorney General’s Departments Asian Finance 20 20 [c] [c]
In post 2023 London Attorney General’s Departments Asian Human Resources 15 15 [c] [c]
In post 2023 London Attorney General’s Departments Asian Intelligence Analysis [c] [c] [c] [c]
In post 2023 London Attorney General’s Departments Asian Internal Audit [c] [c] [c] [c]
In post 2023 London Attorney General’s Departments Asian Knowledge and Information Management 10 5 [c] [c]
In post 2023 London Attorney General’s Departments Asian Legal 390 365 56690 54230
In post 2023 London Attorney General’s Departments Asian Operational Delivery 235 220 28440 27760
In post 2023 London Attorney General’s Departments Asian Other 5 5 [c] [c]
In post 2023 London Attorney General’s Departments Asian Policy 15 15 [c] [c]
In post 2023 London Attorney General’s Departments Asian Project Delivery 15 15 [c] [c]
In post 2023 London Attorney General’s Departments Asian Property [c] [c] [c] [c]
In post 2023 London Attorney General’s Departments Asian Security [c] [c] [c] [c]
In post 2023 London Attorney General’s Departments Asian Statistics [c] [c] [c] [c]
In post 2023 London Attorney General’s Departments Black Commercial [c] [c] [c] [c]
In post 2023 London Attorney General’s Departments Black Communications 5 5 [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).
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.
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.
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).