Civil Service Statistics data browser (2023)

Data preview: All civil servants / Region_london / Ethnicity / Region_ITL1 / Profession_of_post

Status Year Region_london Ethnicity Region_ITL1 Profession_of_post Headcount FTE Mean_salary Median_salary
In post 2023 London Asian London Commercial 210 205 50420 43750
In post 2023 London Asian London Communications 130 130 42010 39460
In post 2023 London Asian London Corporate Finance 15 15 [c] [c]
In post 2023 London Asian London Counter Fraud 390 360 32660 32520
In post 2023 London Asian London Digital, Data and Technology 850 840 49540 45170
In post 2023 London Asian London Economics 195 190 47290 42360
In post 2023 London Asian London Finance 525 510 46170 43210
In post 2023 London Asian London Human Resources 395 380 42110 38730
In post 2023 London Asian London Inspector of Education and Training 10 10 [c] [c]
In post 2023 London Asian London Intelligence Analysis 150 140 35200 30500
In post 2023 London Asian London Internal Audit 60 60 47390 45840
In post 2023 London Asian London International Trade 125 120 48100 41750
In post 2023 London Asian London Knowledge and Information Management 90 85 38840 35410
In post 2023 London Asian London Legal 605 565 54440 54100
In post 2023 London Asian London Medicine 60 55 79220 74840
In post 2023 London Asian London Operational Delivery 6415 5895 32820 31260
In post 2023 London Asian London Operational Research 50 50 49340 44180
In post 2023 London Asian London Other 375 360 37980 35410
In post 2023 London Asian London Planning 5 5 [c] [c]
In post 2023 London Asian London 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 2023-07-28, 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.
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.
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).