Civil Service Statistics data browser (2023)

Data preview: All civil servants / Ethnicity / Region_london / Region_ITL1 / Function_of_post

Status Year Ethnicity Region_london Region_ITL1 Function_of_post Headcount FTE Mean_salary Median_salary
In post 2023 Asian London London Analysis 555 545 45700 41770
In post 2023 Asian London London Commercial 235 235 51130 43750
In post 2023 Asian London London Communications 140 140 42590 39790
In post 2023 Asian London London Counter Fraud 650 610 35030 32520
In post 2023 Asian London London Debt 165 145 28120 26920
In post 2023 Asian London London Digital, Data & Technology 875 860 47820 43650
In post 2023 Asian London London Finance 610 595 45780 42970
In post 2023 Asian London London Grants Management 5 5 [c] [c]
In post 2023 Asian London London Human Resources 410 395 41690 38590
In post 2023 Asian London London Internal Audit 60 55 47590 46200
In post 2023 Asian London London Legal 785 740 47730 52020
In post 2023 Asian London London No function 9160 8585 37520 32520
In post 2023 Asian London London Project Delivery 735 715 47960 43210
In post 2023 Asian London London Property 190 185 39030 35670
In post 2023 Asian London London Security 230 225 38080 34860
In post 2023 Asian London London Unknown 245 240 38520 32960
In post 2023 Asian Outside London East Midlands (England) Analysis 10 10 [c] [c]
In post 2023 Asian Outside London East Midlands (England) Commercial 5 5 [c] [c]
In post 2023 Asian Outside London East Midlands (England) Communications [c] [c] [c] [c]
In post 2023 Asian Outside London East Midlands (England) Counter Fraud 90 85 32980 34170
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".
Region_ITL1 Workplace postcode data are used to derive geographical information using the International Territorial Level (ITL) classification standard.
Following the UK’s withdrawal from the EU, a new UK-managed international statistical geography - International Territorial Levels (ITL) - was introduced from 1st January 2021, replacing the former NUTS classification. They align with international standards, enabling comparability both over time and internationally. To ensure continued alignment, the ITLs mirror the NUTS system. They also follow a similar review timetable - every three years.
ITL 1 divides into Wales, Scotland, Northern Ireland, and the 9 statistical regions of England.
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.
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).