Civil Service Statistics data browser (2023)

Data preview: All civil servants / Ethnicity / Region_london / Region_ITL3

Explore further: Parent_department, Organisation, Responsibility_level_grouped, Responsibility_level_ungrouped, Region_ITL1, Region_ITL2, Profession_of_post, Function_of_post, Sex, Disability, Sexual_orientation, Age

Status Year Ethnicity Region_london Region_ITL3 Headcount FTE Mean_salary Median_salary
In post 2023 Asian London Barking & Dagenham and Havering 170 155 32780 32520
In post 2023 Asian London Barnet 425 405 40530 33330
In post 2023 Asian London Bexley and Greenwich 110 100 32800 32520
In post 2023 Asian London Brent 135 120 32140 32520
In post 2023 Asian London Bromley 40 35 34370 32520
In post 2023 Asian London Camden and City of London 290 275 33850 29660
In post 2023 Asian London Croydon 1795 1685 37420 32580
In post 2023 Asian London Ealing 160 145 33130 32520
In post 2023 Asian London Enfield 55 50 32750 32520
In post 2023 Asian London Hackney and Newham 1490 1400 39070 34370
In post 2023 Asian London Haringey and Islington 185 170 31860 32520
In post 2023 Asian London Harrow and Hillingdon 1210 1100 32190 30200
In post 2023 Asian London Hounslow and Richmond upon Thames 620 570 32380 30280
In post 2023 Asian London Kensington & Chelsea and Hammersmith & Fulham 110 105 34270 33800
In post 2023 Asian London Lambeth 240 230 39090 34450
In post 2023 Asian London Lewisham and Southwark 95 90 35090 32520
In post 2023 Asian London Merton, Kingston upon Thames and Sutton 80 75 35100 32520
In post 2023 Asian London Redbridge and Waltham Forest 540 480 30090 30240
In post 2023 Asian London Tower Hamlets 1130 1090 43970 40000
In post 2023 Asian London Wandsworth 90 85 31140 30840
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_ITL3 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 3 divides into counties, unitary authorities, or districts in England (some grouped), groups of unitary authorities in Wales, groups of council areas in Scotland, groups of districts in Northern Ireland.
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).