Civil Service Statistics data browser (2023)

Data preview: All civil servants / Sexual_orientation / Region_london / Ethnicity / Profession_of_post

Status Year Sexual_orientation Region_london Ethnicity Profession_of_post Headcount FTE Mean_salary Median_salary
In post 2023 Heterosexual / straight London Asian Commercial 165 160 49410 43650
In post 2023 Heterosexual / straight London Asian Communications 115 115 41730 39000
In post 2023 Heterosexual / straight London Asian Corporate Finance 15 15 [c] [c]
In post 2023 Heterosexual / straight London Asian Counter Fraud 315 295 33070 32520
In post 2023 Heterosexual / straight London Asian Digital, Data and Technology 710 700 50210 45920
In post 2023 Heterosexual / straight London Asian Economics 165 160 47770 43760
In post 2023 Heterosexual / straight London Asian Finance 460 450 46090 43210
In post 2023 Heterosexual / straight London Asian Human Resources 355 340 42150 39010
In post 2023 Heterosexual / straight London Asian Inspector of Education and Training 10 10 [c] [c]
In post 2023 Heterosexual / straight London Asian Intelligence Analysis 130 125 35590 30680
In post 2023 Heterosexual / straight London Asian Internal Audit 45 45 48470 46340
In post 2023 Heterosexual / straight London Asian International Trade 105 105 47570 41750
In post 2023 Heterosexual / straight London Asian Knowledge and Information Management 75 70 39030 35410
In post 2023 Heterosexual / straight London Asian Legal 505 480 54120 54100
In post 2023 Heterosexual / straight London Asian Medicine 45 40 72310 67160
In post 2023 Heterosexual / straight London Asian Operational Delivery 5345 4955 33040 31350
In post 2023 Heterosexual / straight London Asian Operational Research 45 45 49140 43650
In post 2023 Heterosexual / straight London Asian Other 325 310 38330 36000
In post 2023 Heterosexual / straight London Asian Planning 5 5 [c] [c]
In post 2023 Heterosexual / straight London Asian Planning Inspectors [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 2023-07-26, 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".
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.
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.
Sexual_orientation Self reported sexual orientation.
"Undeclared" accounts for employees who have actively declared that they do not want to disclose their sexual orientation and "Unknown" accounts for employees who have not made an active declaration about their sexual orientation.
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).