Civil Service Statistics data browser (2023)

Data preview: All civil servants / Sex / Region_london / Profession_of_post / Responsibility_level_grouped

Status Year Sex Region_london Profession_of_post Responsibility_level_grouped Headcount FTE Mean_salary Median_salary
In post 2023 Female London Commercial AA/AO 30 25 [c] [c]
In post 2023 Female London Commercial EO 60 60 30820 31200
In post 2023 Female London Commercial G6/G7 345 340 65790 65680
In post 2023 Female London Commercial SCS level 60 55 112490 103430
In post 2023 Female London Commercial SEO/HEO 345 340 39890 39780
In post 2023 Female London Commercial Unknown [c] [c] [c] [c]
In post 2023 Female London Communications AA/AO 15 15 [c] [c]
In post 2023 Female London Communications EO 105 100 30140 29660
In post 2023 Female London Communications G6/G7 435 420 61180 59510
In post 2023 Female London Communications SCS level 40 40 88370 83340
In post 2023 Female London Communications SEO/HEO 600 585 40990 41210
In post 2023 Female London Communications Unknown [c] [c] [c] [c]
In post 2023 Female London Corporate Finance EO [c] [c] [c] [c]
In post 2023 Female London Corporate Finance G6/G7 5 5 [c] [c]
In post 2023 Female London Corporate Finance SCS level [c] [c] [c] [c]
In post 2023 Female London Corporate Finance SEO/HEO 15 15 [c] [c]
In post 2023 Female London Counter Fraud AA/AO 220 180 25310 25610
In post 2023 Female London Counter Fraud EO 440 410 32190 32520
In post 2023 Female London Counter Fraud G6/G7 50 50 64120 64260
In post 2023 Female London Counter Fraud SCS level 5 5 [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 2023-07-26, 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).
Responsibility_level_grouped With the exception of the centrally managed Senior Civil Service, government departments have delegated pay and grading. For statistical purposes departments are asked to map their grades to a common framework by responsibility level.
This table shows staff in their substantive responsibility level unless on temporary promotion in which case staff are recorded at the higher responsibility level.
Responsibility_level_grouped combines the mapped grades into five broad responsibility levels. This is the headline measure for responsibility level for the Civil Service and is consistent with the published National Statistics.
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".
Profession_of_post Professions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
Of the 20 bodies under the Scottish Government, 16 did not report any professions information for their employees.
Sex Self reported sex.
"Unknown" accounts for employees who were recorded with an unknown sex.
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).