Civil Service Statistics data browser (2023)

Data preview: All civil servants / Ethnicity / Disability / Region_london / Function_of_post

Status Year Ethnicity Disability Region_london Function_of_post Headcount FTE Mean_salary Median_salary
In post 2023 Asian Declared disabled London Analysis 45 45 44950 37850
In post 2023 Asian Declared disabled London Commercial 25 25 [c] [c]
In post 2023 Asian Declared disabled London Communications 15 15 [c] [c]
In post 2023 Asian Declared disabled London Counter Fraud 70 65 36120 32540
In post 2023 Asian Declared disabled London Debt 10 10 [c] [c]
In post 2023 Asian Declared disabled London Digital, Data & Technology 75 75 44290 41030
In post 2023 Asian Declared disabled London Finance 55 50 43140 43650
In post 2023 Asian Declared disabled London Grants Management [c] [c] [c] [c]
In post 2023 Asian Declared disabled London Human Resources 70 65 41500 39150
In post 2023 Asian Declared disabled London Internal Audit 5 5 [c] [c]
In post 2023 Asian Declared disabled London Legal 65 60 49420 52790
In post 2023 Asian Declared disabled London No function 965 885 35550 32520
In post 2023 Asian Declared disabled London Project Delivery 70 70 44620 42060
In post 2023 Asian Declared disabled London Property 20 20 [c] [c]
In post 2023 Asian Declared disabled London Security 25 25 [c] [c]
In post 2023 Asian Declared disabled London Unknown 40 40 36910 32960
In post 2023 Asian Declared disabled Outside London Analysis 10 10 [c] [c]
In post 2023 Asian Declared disabled Outside London Commercial 20 20 [c] [c]
In post 2023 Asian Declared disabled Outside London Communications [c] [c] [c] [c]
In post 2023 Asian Declared disabled Outside London Counter Fraud 80 75 29060 28120
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.
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).