Civil Service Statistics data browser (2022)

Data preview: All civil servants / Region_london / Ethnicity / Sex / Function_of_post

Status Year Region_london Ethnicity Sex Function_of_post Headcount FTE Mean_salary Median_salary
In post 2022 London Asian Female Analysis 215 205 45430 40930
In post 2022 London Asian Female Commercial 85 85 45040 40600
In post 2022 London Asian Female Communications 95 90 43380 40000
In post 2022 London Asian Female Counter Fraud 375 330 31330 31020
In post 2022 London Asian Female Debt 80 65 27300 26400
In post 2022 London Asian Female Digital, Data & Technology 265 260 44890 40730
In post 2022 London Asian Female Finance 260 250 42970 39960
In post 2022 London Asian Female Grants Management [c] [c] [c] [c]
In post 2022 London Asian Female Human Resources 255 250 40780 36650
In post 2022 London Asian Female Internal Audit 25 25 [c] [c]
In post 2022 London Asian Female Legal 490 450 46170 50500
In post 2022 London Asian Female No function 4155 3850 36530 31880
In post 2022 London Asian Female Project Delivery 335 315 45470 41740
In post 2022 London Asian Female Property 125 115 36900 32560
In post 2022 London Asian Female Security 75 75 37830 34710
In post 2022 London Asian Female Unknown 1985 1820 34550 29510
In post 2022 London Asian Male Analysis 230 225 45890 42260
In post 2022 London Asian Male Commercial 75 75 49900 44080
In post 2022 London Asian Male Communications 55 55 43420 40530
In post 2022 London Asian Male Counter Fraud 270 260 34340 31060
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 2023-02-15, with GIT 71a76ea.

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.
Five 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, Defence Electronics and Components Agency, 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.
Organisation specific notes on status: In late June 2021 around 7,000 employees from Community Rehabilitation Companies were transferred in from the private sector to HM Prison and Probation Service, counting as entrants. HM Land Registry do not record where their departing employees transfer to and so are unable to identify those that transfer to another Civil Service department.
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”.
Function_of_post Functions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
Home Office, Welsh Government and Royal Fleet Auxiliary did not report any functions information for their employees.
Of the 20 bodies under the Scottish Government, 16 did not report any functions information for their employees.
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.
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).