Civil Service Statistics data browser (2023)

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

Status Year Sex Region_ITL1 Age Region_london Headcount FTE Mean_salary Median_salary
In post 2023 Female East Midlands (England) 16-19 Outside London 40 40 24720 23230
In post 2023 Female East Midlands (England) 20-29 Outside London 2100 2035 27220 26900
In post 2023 Female East Midlands (England) 30-39 Outside London 2725 2480 31440 28480
In post 2023 Female East Midlands (England) 40-49 Outside London 3205 2870 33620 28480
In post 2023 Female East Midlands (England) 50-59 Outside London 4040 3665 32270 28120
In post 2023 Female East Midlands (England) 60-64 Outside London 1105 900 28590 27140
In post 2023 Female East Midlands (England) 65+ Outside London 275 200 28670 25340
In post 2023 Female East of England 16-19 Outside London 40 35 24030 23230
In post 2023 Female East of England 20-29 Outside London 1675 1625 28030 27000
In post 2023 Female East of England 30-39 Outside London 2305 2080 31720 29970
In post 2023 Female East of England 40-49 Outside London 2910 2580 34300 31280
In post 2023 Female East of England 50-59 Outside London 3795 3480 32280 28120
In post 2023 Female East of England 60-64 Outside London 1145 960 30270 28120
In post 2023 Female East of England 65+ Outside London 380 285 27670 25610
In post 2023 Female East of England Unknown Outside London [c] [c] [c] [c]
In post 2023 Female London 16-19 London 65 65 27030 26920
In post 2023 Female London 20-29 London 13095 13000 37980 35240
In post 2023 Female London 30-39 London 13620 13035 47700 44140
In post 2023 Female London 40-49 London 12385 11410 49550 43980
In post 2023 Female London 50-59 London 12665 11975 44680 38680
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.
Sex Self reported sex.
"Unknown" accounts for employees who were recorded with an unknown sex.
Age Age in 10 year bands. Age is calculated as at the reference date in each year (31st March), so entrants or leavers may have been up to one year younger at the date of exit or entry.
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).