Civil Service Statistics data browser (2023)

Data preview: All civil servants / Parent_department / Region_london / Age / Organisation

Status Year Parent_department Region_london Age Organisation Headcount FTE Mean_salary Median_salary
In post 2023 Attorney General’s Departments London 16-19 Attorney General’s Office [c] [c] [c] [c]
In post 2023 Attorney General’s Departments London 16-19 Crown Prosecution Service 5 5 [c] [c]
In post 2023 Attorney General’s Departments London 16-19 Government Legal Department [c] [c] [c] [c]
In post 2023 Attorney General’s Departments London 16-19 Serious Fraud Office [c] [c] [c] [c]
In post 2023 Attorney General’s Departments London 20-29 Attorney General’s Office 15 15 37600 32890
In post 2023 Attorney General’s Departments London 20-29 Crown Prosecution Service 320 320 29440 28200
In post 2023 Attorney General’s Departments London 20-29 Government Legal Department 350 350 37440 32710
In post 2023 Attorney General’s Departments London 20-29 HM Crown Prosecution Service Inspectorate [c] [c] [c] [c]
In post 2023 Attorney General’s Departments London 20-29 Serious Fraud Office 75 75 34120 34500
In post 2023 Attorney General’s Departments London 30-39 Attorney General’s Office 20 20 50990 52020
In post 2023 Attorney General’s Departments London 30-39 Crown Prosecution Service 330 320 44650 44750
In post 2023 Attorney General’s Departments London 30-39 Government Legal Department 720 690 52770 52790
In post 2023 Attorney General’s Departments London 30-39 HM Crown Prosecution Service Inspectorate [c] [c] [c] [c]
In post 2023 Attorney General’s Departments London 30-39 Serious Fraud Office 105 105 48710 51840
In post 2023 Attorney General’s Departments London 40-49 Attorney General’s Office 10 10 66220 55750
In post 2023 Attorney General’s Departments London 40-49 Crown Prosecution Service 470 440 49380 54100
In post 2023 Attorney General’s Departments London 40-49 Government Legal Department 705 635 61630 65650
In post 2023 Attorney General’s Departments London 40-49 HM Crown Prosecution Service Inspectorate [c] [c] [c] [c]
In post 2023 Attorney General’s Departments London 40-49 Serious Fraud Office 105 105 51410 54230
In post 2023 Attorney General’s Departments London 50-59 Attorney General’s Office [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 2023-07-29, 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).
Parent_department Government Department, total figures for both Ministerial and Non-Ministerial Departments include all of their Executive Agencies.
Organisation Executive Agencies, Ministerial and Non-Ministerial Departments, Crown Non-departmental Public Bodies.
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".
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).