Civil Service Statistics data browser (2023)

Data preview: All civil servants / Region_ITL1 / Region_ITL3 / Ethnicity / Region_ITL2

Status Year Region_ITL1 Region_ITL3 Ethnicity Region_ITL2 Headcount FTE Mean_salary Median_salary
In post 2023 East Midlands (England) Derby Asian Derbyshire and Nottinghamshire 130 115 27080 28120
In post 2023 East Midlands (England) Derby Black Derbyshire and Nottinghamshire 40 35 27960 28120
In post 2023 East Midlands (England) Derby Mixed Derbyshire and Nottinghamshire 30 30 27020 24570
In post 2023 East Midlands (England) Derby Other ethnicity Derbyshire and Nottinghamshire [c] [c] [c] [c]
In post 2023 East Midlands (England) Derby Undeclared Derbyshire and Nottinghamshire 50 45 29400 22700
In post 2023 East Midlands (England) Derby Unknown Derbyshire and Nottinghamshire 120 110 28510 28120
In post 2023 East Midlands (England) Derby White Derbyshire and Nottinghamshire 760 675 28770 26840
In post 2023 East Midlands (England) East Derbyshire Asian Derbyshire and Nottinghamshire 5 5 [c] [c]
In post 2023 East Midlands (England) East Derbyshire Black Derbyshire and Nottinghamshire [c] [c] [c] [c]
In post 2023 East Midlands (England) East Derbyshire Mixed Derbyshire and Nottinghamshire [c] [c] [c] [c]
In post 2023 East Midlands (England) East Derbyshire Other ethnicity Derbyshire and Nottinghamshire [c] [c] [c] [c]
In post 2023 East Midlands (England) East Derbyshire Undeclared Derbyshire and Nottinghamshire 15 15 [c] [c]
In post 2023 East Midlands (England) East Derbyshire Unknown Derbyshire and Nottinghamshire 20 20 [c] [c]
In post 2023 East Midlands (England) East Derbyshire White Derbyshire and Nottinghamshire 335 295 29640 28120
In post 2023 East Midlands (England) Leicester Asian Leicestershire, Rutland and Northamptonshire 775 695 26610 24360
In post 2023 East Midlands (England) Leicester Black Leicestershire, Rutland and Northamptonshire 80 75 27830 25300
In post 2023 East Midlands (England) Leicester Mixed Leicestershire, Rutland and Northamptonshire 60 60 29060 25830
In post 2023 East Midlands (England) Leicester Other ethnicity Leicestershire, Rutland and Northamptonshire 15 15 [c] [c]
In post 2023 East Midlands (England) Leicester Undeclared Leicestershire, Rutland and Northamptonshire 100 90 28040 28080
In post 2023 East Midlands (England) Leicester Unknown Leicestershire, Rutland and Northamptonshire 225 205 27450 26480
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_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.
Region_ITL2 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 2 divides into Northern Ireland, counties in England (most grouped), groups of districts in Greater London, groups of unitary authorities in Wales, groups of council areas in Scotland.
Region_ITL3 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 3 divides into counties, unitary authorities, or districts in England (some grouped), groups of unitary authorities in Wales, groups of council areas in Scotland, groups of districts in Northern Ireland.
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).