Civil Service Statistics data browser (2025)

Data preview: All civil servants / Ethnicity / Disability / Region_ITL1

Explore further: Parent_department, Organisation, Responsibility_level_grouped, Responsibility_level_ungrouped, Region_london, Region_ITL2, Region_ITL3, Profession_of_post, Function_of_post, Sex, Sexual_orientation, Age

Status Year Ethnicity Disability Region_ITL1 Headcount FTE Mean_salary Median_salary
In post 2025 Asian Declared disabled East (England) 185 165 35260 33780
In post 2025 Asian Declared disabled East Midlands (England) 340 305 31670 30980
In post 2025 Asian Declared disabled London 1925 1790 42840 36680
In post 2025 Asian Declared disabled North East (England) 90 80 31310 30980
In post 2025 Asian Declared disabled North West (England) 535 495 33690 30980
In post 2025 Asian Declared disabled Northern Ireland [c] [c] [c] [c]
In post 2025 Asian Declared disabled Overseas 10 10 [c] [c]
In post 2025 Asian Declared disabled Scotland 110 110 39040 35200
In post 2025 Asian Declared disabled South East (England) 185 170 36370 34330
In post 2025 Asian Declared disabled South West (England) 95 85 38510 33890
In post 2025 Asian Declared disabled Unknown [c] [c] [c] [c]
In post 2025 Asian Declared disabled Wales 55 55 37410 30980
In post 2025 Asian Declared disabled West Midlands (England) 820 750 33430 30980
In post 2025 Asian Declared disabled Yorkshire and The Humber 470 430 33660 30980
In post 2025 Asian Declared non-disabled East (England) 1140 1045 35660 31500
In post 2025 Asian Declared non-disabled East Midlands (England) 1980 1825 33100 30980
In post 2025 Asian Declared non-disabled London 11830 11220 44860 39950
In post 2025 Asian Declared non-disabled North East (England) 705 665 35640 30980
In post 2025 Asian Declared non-disabled North West (England) 3555 3345 34100 30980
In post 2025 Asian Declared non-disabled Northern Ireland 20 20 [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 2025-07-16

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.
Five 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, United Kingdom Statistics Authority, Scottish Forestry and Forest and Land Scotland.
Year Year of data collection (as at 31 March).
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.
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).