Civil Service Statistics data browser (2023)

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

Status Year Sex Region_ITL1 Region_london Ethnicity Headcount FTE Mean_salary Median_salary
In post 2023 Female East Midlands (England) Outside London Asian 1175 1030 29360 27890
In post 2023 Female East Midlands (England) Outside London Black 400 370 28770 27890
In post 2023 Female East Midlands (England) Outside London Mixed 275 250 29850 28080
In post 2023 Female East Midlands (England) Outside London Other ethnicity 45 40 31880 28120
In post 2023 Female East Midlands (England) Outside London Undeclared 380 340 31270 28120
In post 2023 Female East Midlands (England) Outside London Unknown 1650 1520 28790 27650
In post 2023 Female East Midlands (England) Outside London White 9560 8640 32030 28120
In post 2023 Female East of England Outside London Asian 745 655 31280 28120
In post 2023 Female East of England Outside London Black 385 360 31480 29570
In post 2023 Female East of England Outside London Mixed 260 245 32270 30810
In post 2023 Female East of England Outside London Other ethnicity 65 60 31730 30850
In post 2023 Female East of England Outside London Undeclared 385 340 31750 29730
In post 2023 Female East of England Outside London Unknown 1200 1085 29960 26900
In post 2023 Female East of England Outside London White 9205 8305 31970 28620
In post 2023 Female London London Asian 8970 8315 39500 34770
In post 2023 Female London London Black 6905 6585 36860 32520
In post 2023 Female London London Mixed 2175 2075 42930 38680
In post 2023 Female London London Other ethnicity 800 760 42130 36380
In post 2023 Female London London Undeclared 2015 1870 41780 36180
In post 2023 Female London London Unknown 8585 8280 42810 37350
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".
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.
Sex Self reported sex.
"Unknown" accounts for employees who were recorded with an unknown sex.
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).