Civil Service Statistics data browser (2023)

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

Status Year Disability Ethnicity Sex Region_ITL1 Headcount FTE Mean_salary Median_salary
In post 2023 Declared disabled Asian Female East Midlands (England) 150 130 27890 28100
In post 2023 Declared disabled Asian Female East of England 90 80 30720 29620
In post 2023 Declared disabled Asian Female London 965 880 37800 32520
In post 2023 Declared disabled Asian Female North East (England) 35 30 26800 28120
In post 2023 Declared disabled Asian Female North West (England) 180 155 29060 28120
In post 2023 Declared disabled Asian Female Northern Ireland [c] [c] [c] [c]
In post 2023 Declared disabled Asian Female Overseas [c] [c] [c] [c]
In post 2023 Declared disabled Asian Female Scotland 30 30 31800 28120
In post 2023 Declared disabled Asian Female South East (England) 90 80 30970 29360
In post 2023 Declared disabled Asian Female South West (England) 40 35 33240 28120
In post 2023 Declared disabled Asian Female Unknown [c] [c] [c] [c]
In post 2023 Declared disabled Asian Female Wales 20 20 [c] [c]
In post 2023 Declared disabled Asian Female West Midlands (England) 355 315 29340 28120
In post 2023 Declared disabled Asian Female Yorkshire and The Humber 150 130 28300 28120
In post 2023 Declared disabled Asian Male East Midlands (England) 110 100 28290 28120
In post 2023 Declared disabled Asian Male East of England 55 50 32880 28480
In post 2023 Declared disabled Asian Male London 590 570 38630 34390
In post 2023 Declared disabled Asian Male North East (England) 30 30 30070 28120
In post 2023 Declared disabled Asian Male North West (England) 185 175 30020 28120
In post 2023 Declared disabled Asian Male Northern Ireland [c] [c] [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 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_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.
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).