Methodology

We set out below our methodology behind various pieces of analysis that have contributed to this year’s Whitehall Monitor. For questions on the below, or regarding any of our findings, please get in touch via email at enquiries@instituteforgovernment.org.uk

Throughout this methodology, we refer to charts by the figure numbers they have in the PDF version of this report.

Publication of data 

Our charts draw principally on publicly available government data, which in most cases we have further processed and analysed. We have collated the final data inputs for each of our charts and published them on our website alongside this report. If you have any questions about the analysis of this data, please get in touch via email at the address given above. 

Throughout the report 

Much of the analysis in this report draws on the Cabinet Office’s annual Civil Service Statistics publication. This dataset rounds numbers to the nearest 5, and reports numbers lower than 5 as ‘[c]’. In our analysis, we replace all figures reported as ‘[c]’ with ‘3’. Unless otherwise stated, all figures for numbers of civil servants throughout this report are FTE rather than headcount figures. 

Defining civil servants 

We define ‘civil servants’ as politically impartial, appointed officials of the UK Home Civil Service, which supports the work of the UK’s central government departments. This includes agencies that employ civil servants such as executive agencies, non-ministerial departments and some non-departmental public bodies. 

Our definition includes staff of the three Whitehall-based territorial offices that manage the UK’s relationships with Scotland, Wales and Northern Ireland though for simplicity we do not include them in much of our analysis which compares different departments. It also includes the civil servants that the devolved governments of Wales and Scotland employ, but not the staff of the Northern Ireland Civil Service, which is administratively distinct. 

In this way, civil servants are defined more narrowly than public sector workers – police officers, teachers, NHS staff, members of the armed forces and local government officers are not counted as civil servants. Nor do we include the UK’s diplomatic service in our analysis since it too is administratively separate from the UK Home Civil Service. 

Defining the senior civil service 

There are two definitions of the senior civil service. The annual Civil Service Statistics publication (the source of much of the data in this report) contains information on ‘SCS level’ employees. This measure includes “a number of health professionals, military personnel, and senior diplomats that are not part of the Senior Civil Service”. ²² Cabinet Office, ‘Quality and Methodology Information for Civil Service Statistics 2024’, 20 August 2024, https://www.gov.uk/government/statistics/civil-service-statistics-2024/quality-and-methodologyinformation- for-civil-service-statistics-2024

By contrast, the Cabinet Office collects data on ‘the senior civil service’ in the SCS database. Because this is not publicly available, by necessity we use the data in the annual Civil Service Statistics publication. These two measures give different figures for the size of the senior civil service. The 2024 release of Civil Service Statistics recorded 7,535 individuals at ‘senior civil service level’ (7,295 FTE). While the SCS database is not publicly available, the government’s evidence to the Senior Salaries Review Body on SCS pay (published in December 2024) put the size of the senior civil service at 6,740 (6,565 FTE). ²³ Civil Service / Senior Salaries Review Body, ‘Government evidence to the Senior Salaries Review Body on the pay of the Senior Civil Service’, 10 December 2024, www.gov.uk/government/publications/government-evidence- to-the-senior-salaries-review-body-on-the-pay-of-the-senior-civil-service

Defining departments 

Where possible, we categorise bodies into ‘departmental groups’ according to where ministerial responsibility lies, even when these are reported under a separate departmental heading in government data. For example, we group Ofsted with the Department for Education (DfE) departmental group, and not as a separate department, as it is reported in the original Office for National Statistics (ONS) Public Sector Employment data. 

In such cases where source data reports organisations as independent from core departments, we have identified the departmental group to which those organisations belong by using the ‘sponsor department’ identified in the most recent public bodies report (for 2022/23) published by the Cabinet Office, ²⁴ Cabinet Office, Public Bodies 2023, 2024, www.gov.uk/government/publications/public-bodies-2023  or by government statements – such as on machinery of government changes – to parliament. 

Unless otherwise indicated in the notes for a chart, the figures used throughout the report are for departmental groups, and therefore include the civil servants who work in the core departments as well as the agencies and non-ministerial departments they oversee. 

A table listing the departments and their associated organisations is presented below. We have not included organisations that no longer exist – for example, because they have been merged with other bodies or renamed. However, historic organisations are counted in our figures for change over time, and details of those used in our analysis are available upon request. 

List of departments and associated organisations

Machinery of government changes 

Much of the analysis in this report covers a timeframe in which multiple departments merged or changed names. Wherever possible, we use a department’s current name throughout – including for time points at which it had a different name. This applies, for example, to the Ministry of Housing, Communities and Local Government (MHCLG) – which was called the Department for Levelling Up, Housing and Communities (DLUHC) until 8 July 2024 – even though the latest data used for much of this report refers to the department as DLUHC. 

Where departments have undergone simple mergers, for example the Foreign and Commonwealth Office (FCO) and the Department for International Development (DfID) merging to form the Foreign, Commonwealth and Development Office (FCDO), we use the sum (for example, of staff numbers or spending on consultancy services) of the predecessor departments for the period preceding the merger. 

This is not possible for all departments. For example, while the Department for Business, Energy and Industrial Strategy (BEIS) was formed through a simple merger of the Department for Business, Innovation and Skills (BIS) and the Department of Energy and Climate Change (DECC), the more complex way in which the department was split up means that the current Department for Science, Innovation and Technology (DSIT), Department for Business and Trade (DBT) and Department for Energy Security and Net Zero (DESNZ) are excluded from some charts showing longer time series. 

Inflation/real-terms figures 

For government spending information that spans multiple years, we use the gross domestic product (GDP) deflator to present numbers in consistent prices. The GDP deflator is a measure of economy-wide inflation and so is appropriate for considering changes in government spending. We use the GDP deflator published alongside Autumn Budget 2024. ²⁵ HM Treasury, Autumn Budget 2024, 2024, www.gov.uk/government/publications/autumn-budget-2024  This is used in Figures 2.41–2.47 and 2.49. 

For pay figures, we use the Consumer Price Index (CPI) to present numbers in consistent prices as this is the relevant measure to understand how much pay packets are worth to households. We use CPI figures published in April 2024, as they are being used to adjust data from April in each year. This is used in Figures 1.4, 2.19, 2.20 and 2.21.

Specific sections 

The size of the civil service 

To analyse civil service staff numbers, we use Table 9 from the ONS’s quarterly Public Sector Employment series, which contains staff numbers (headcount and full-time equivalent [FTE]) in all public organisations that employ civil servants. Unless stated otherwise, we use FTE figures, which count part-time staff according to the time they work (for example, a person working two days a week as 0.4 FTE); this is more meaningful than headcount, which does not distinguish between full-time and parttime employees. 

As with the Cabinet Office’s Civil Service Statistics publication , the ONS public sector employment data rounds numbers to the nearest 5, and reports numbers less than 5 as ‘..’. In our analysis we replace these suppressed figures with ‘3’. 

Our figures exclude temporary Census Field staff. Staff from Central Government Security (formerly Security and Intelligence Services) have also been excluded from civil service statistics published since Q2 2016. We adjust for this by manually excluding Central Government Security staff from our datasets before this date, too. 

As stated in the text, in this edition of Whitehall Monitor we have altered our methodology for assessing how individual departments have changed in size over time. In previous editions of Whitehall Monitor and other Institute for Government analysis, we corrected for reclassifications of staff that were the result of machinery of government changes. For example, this meant that where several thousand staff were transferred from one department to another, we would not include that figure in our calculation of either department’s changing size over time. This was done to restrict our analysis to showing the ‘organic’ change in the size of departments. But this year, given the high number of significant machinery of government changes, we have decided to include staffing transfers to give a more accurate picture of how they have affected the sizes of different departments. 

Turnover and leaving route

Data on civil service staff turnover is derived from the annual Cabinet Office Civil Service Statistics dataset (Tables 20, 42 and 43). We use headcount rather than FTE for all staff turnover calculations. Figures relate to the core department and do not include agencies within departmental groups. 

External staff turnover is calculated as the number of civil servants who left the civil service entirely over the course of a given year, as a percentage of the average civil service headcount during that period. Average civil service headcount is calculated as the mean of civil service headcount at the beginning and end of the interval (for instance, headcount in March 2021 and March 2022 for the period 2021–22). We use average headcount to account for the fact that the number of civil servants changes over the course of the year. 

Internal staff turnover is calculated as the number of civil servants who transferred to another department over the course of a given year, as a percentage of the average civil service headcount during that period. 

Total staff turnover is calculated as the number of civil servants who either left the civil service entirely or transferred to another department over the course of a given year, as a percentage of the average civil service headcount during that period. This is an underestimate of real internal turnover in the civil service because it does not include civil servants who transferred to another role within the same department. Unfortunately, data on staff transfers within departments is not publicly available. 

Data on civil servants’ ‘leaving route’ comes from Table 42 of the Civil Service Statistics dataset. For simplicity, we have categorised the various kinds of leaving cause reported in the source data (referred to as ‘routes’ in this report) as such: 

• Resignation
• Retirement
• ‘End of appointment’ (which the dataset records as ‘End of Casual, Period, Conditional Or Provisional Appointment’)
• Dismissal 
• 'Voluntary exit/redundancy’, which combines the following leaving causes reported in the source data: ‘Voluntary Exit Scheme: With Payment’; ‘Voluntary Exit Scheme: With An Unreduced Pension’; ‘Voluntary Exit Scheme: Terms Not Recorded’; ‘Voluntary Redundancy Scheme: With Payment’; ‘Voluntary Redundancy Scheme: With An Unreduced Pension’; ‘Voluntary Redundancy Scheme: Terms Not Recorded’.
• ‘Other’, which combines the following leaving causes reported in the source data: ‘Compulsory Redundancy Scheme’; ‘Death in service’; ‘Transfer Of Function To Private Sector’; ‘Secondment To Organisation External To Civil Service’; ‘Other Leaving Cause’. 

Grade structure and pay 

Paybill calculations 

For Figure 2.20, we calculated estimates for the actual current civil service paybill and for two hypothetical scenarios. 

To estimate the actual current civil service paybill we combined statistics on the number of civil servants at each grade (FTE) and the mean salary for each grade. 

In the first hypothetical scenario, where the civil service in 2024 has the same grade composition as in 2010, we estimated the number of civil servants at each grade by multiplying (i) the proportion of civil servants at each respective grade in 2010 and (ii) total numbers (FTE) in 2024. We then estimated the paybill for this scenario by multiplying these estimates for numbers (FTE) by grade with the mean salary by grade in 2024. 

In the second hypothetical scenario, the civil service in 2024 again has the same grade composition as in 2010 but wages rise in line with those in the private sector. Mean civil service salary by grade is grown in line with wage growth in the whole private sector from 2010 (specifically, the private sector gross annual earnings measure in ONS, Annual Survey of Hours and Earnings, 2010–24). Again, we estimated the paybill by multiplying these estimates with actual numbers (FTE) by grade for 2024. 

Those with unreported grades were excluded from all calculations due to limited data availability, meaning that the estimated total paybill is a slight underestimate in each scenario. 

Comparison of private sector and civil service salaries 

For calculations of where civil service salaries at different grades compare to similar private sector jobs, we compare median salaries in each grade category to the distribution of pay in the ‘business research and administrative professionals’ ONS occupation category. This category includes accountants, consultants, analysts, economists, statisticians and other administrative professionals. It will include some public sector workers in these professions, as well as private sector workers. We compare annual salaries for full-time workers in the Annual Survey of Hours and Earnings to civil service statistics. We also compare senior civil servants to the ‘chief executives and senior officials’ occupation category. This category was redefined in 2020, so we only present comparisons up to 2019. 

Diversity 

Unless otherwise specified, the representation of a demographic characteristic in the civil service is calculated as a share of the number of staff for which that characteristic is known - i.e. excluding those for whom it is ‘not declared’ or ‘not reported’. 

Population benchmarks 

For the proportion of female staff in the civil service, the population benchmark is calculated from the ONS’s Labour Force Survey (Table A02). To render it as closely comparable as possible to the Civil Service Statistics data (which captures the state of the civil service annually on 31 March), the number of economically active women aged 16–64 in the February–April quarter of every year is divided by the whole economically active population in the same quarter. 

The population benchmark for minority ethnic individuals is also calculated from the ONS’s Labour Force Survey (Table A09), using non-seasonally adjusted figures. The number of economically active people belonging to ‘all other ethnic groups combined’ (i.e. not white) aged 16–64 in the January–March quarter of every year is divided by the number of economically active people whose ethnicity is known (‘all other ethnic groups combined’ and ‘white’ combined) in that same quarter. The same calculation is performed on the figures for the April–June quarter of the same year. The two resulting figures are then averaged, to obtain a benchmark figure that best covers the 31 March date which is captured by the Civil Service Statistics data. 

The population benchmark for disabled individuals is also calculated from the ONS’s Labour Force Survey (Table A08), using non-seasonally adjusted figures. The number of economically active people who meet the Harmonised Standard Definition of Disability in the January–March quarter of every year is divided by the number of economically active people whose disability status is known (‘Harmonised Standard Definition of Disability’ and ‘people who do not meet the Harmonised Standard Definition of Disability’ combined) in the same quarter. The same calculation is performed on the figures for the April–June quarter of the same year. The two resulting figures are then averaged, to obtain a benchmark figure that best covers the 31 March date which is captured by the Civil Service Statistics data. 

For Figure 2.30, the population benchmark is calculated using the ONS’s Sexual Orientation dataset. The number of people identifying ‘Gay or lesbian’, ‘Bisexual’ or ‘Other’ aged between 16 and 64 is divided by the number of people aged 16 and 64 whose sexual orientation is known (‘Gay or lesbian’, ‘Bisexual’, ‘Other’ and ‘Heterosexual or straight’ combined). The latest figures available are for 2022. 

The same methodologies are used to calculate the benchmarks in the arm’s-length bodies chapter (Figure 2.52). In that case, however, we have opted for the static version of each benchmark, using only the figures for 2024.

Socio-economic background 

In the absence of robust workforce statistics, our analysis of civil servants’ socioeconomic background uses the annual Civil Service People Survey. The Cabinet Office publishes the results of the people survey by socio-economic background. This data breaks down responses by officials in the national statistics socio-economic classification categories ‘never worked’, ‘routine’, ‘intermediate’ and ‘high’, based on questions about the main income earner in their household when they were 14 years old. Under each of these categories, the data states the number of survey responses received from officials in each grade. We have combined the number of survey responses received under the ‘never worked’ and ‘routine’ categories into the ‘low’ socio-economic background category, in line with the terms that the Social Mobility Commission employs, and used the resulting data to estimate the socio-economic background of officials in each grade.

Relocation 

The Institute’s view is that headcount (rather than FTE) is a better measure for assessing progress in relocating officials, as relocation requires moving individual staff members, regardless of their working pattern. To that end, we have used headcount data in the Relocation chapter, aside from where it is specifically stated that FTE is used. 

Civil servants working for the Scottish or Welsh government are excluded from our analysis, because the UK government has no control over where they work. 

Civil servants based overseas are excluded from our analysis, as they are usually in roles in which there is no or limited choice over where they are located.

Professions and functions 

Our analysis of the civil service professions uses Table 8A in the Cabinet Office’s annual Civil Service Statistics. The professions in the civil service have changed over time. 

As outlined in the text, while the civil service groups the professions into ‘operational delivery’, ‘policy’, ‘functional professions’ and ‘specialist professions’, we take a different approach to grouping them, as listed below. Our groupings are explained in the text, although we define a ‘departmental’ profession as one where at least 50% of its membership is in one department. 

In two cases, we combine very similar professions. We combine ‘planning inspectors’ and the ‘planning’ profession, and ‘corporate finance’ and the ‘finance’ profession. 

1. Operational delivery 

2. Cross-departmental professions

• Commercial 
• Communications
• Digital, data and technology
• Economics
• Finance (including corporate finance)
• Human resources 
• Intelligence analysis
• Knowledge and information management 
• Operational research 
• Policy 
• Project delivery 
• Property 
• Social research 
• Statistics 

3. Departmental professions 

• Counter fraud 
• Geography 
• Inspector of education and training
• Internal audit
• International trade
• Legal 
• Medicine 
• Planning (including planning inspectors) 
• Psychology 
• Science and engineering 
• Security 
• Tax 
• Veterinarian 

This list of professions – according to successive releases of the Cabinet Office’s annual Civil Service Statistics release – does not tally with the list of professions on GOV.UK. The latter includes other professions such as ‘actuary’ and ‘risk management’, which are not included in our analysis.

In Figure 2.40, eight departments are shown. These are the eight departments that saw the highest growth in staff numbers (FTE) in absolute terms between Q2 2016 and Q1 2024. We have used this date range to investigate how departments have grown since the civil service overall began growing again after the EU referendum. The range ends in Q1 2024 because the latest professions data is for that quarter. Different datasets are used to identify the departments to include in this chart (the ONS’s quarterly Public Sector Employment data) and to analyse the change in professions over time (the Cabinet Office’s Civil Service Statistics). These two government datasets give slightly different numbers for the total number of civil servants in a department at any given time. 

For each department, the five professions shown are those that experienced the greatest growth in absolute numbers over the period. We also show the number of officials whose profession was not reported, and group all other professions into an ‘all other professions’ category. In the case of the Ministry of Justice (MoJ), we have analysed the five professions with the greatest growth between 2017 (rather than 2016) and 2024, because the department did not report the professions of most of its staff in 2016. 

Professions data has historically been inconsistently reported. We have avoided correcting for this, except for in one instance. The Department for Work and Pensions (DWP) did not report the professions of over 95% of its staff in 2018, 2020 and 2021. Given the size of the department, this would significantly skew the trend data, particularly for the operational delivery profession. For this reason, we interpolated DWP’s professions numbers for these years based on its reported numbers in 2017, 2019 and 2022. 

Throughout our analysis, we combine the figures stated in the source data under ‘not reported’ and ‘other’. It should be noted that the civil service relies on civil servants self-reporting their profession for this data.

Consultancy and temporary staff spending

In this section, we are primarily interested in consultancy and temporary staff spending by core departments, rather than departmental groups. This is because they offer a better insight into civil service (rather than public sector) capability, by excluding the spending of bodies such as NHS England. The primary source of data on consultancy and temporary staff spending used in this report is departments’ annual reports and accounts. DBT had not released its 2023/24 annual report and accounts at the time of writing. We have also not analysed territorial offices. Wherever both restated and original values are available for a given financial year, we used the former. 

Some data points are unavailable because departments have not reported consultancy or temporary labour spending in their annual reports and accounts. BEIS did not report temporary labour spending for any of the years between 2018/19 and 2022/23. For years before the merger of FCO and DfID, FCDO’s spending is plotted as the sum of DfID’s and FCO’s. In some years, some departments did not report core departmental spending separately, and instead reported core department and executive agency spending. These departments include the Cabinet Office, the MoJ and HMT. In these cases we have by necessity used figures for core department and executive agency spending. 

Precise figures on consultancy spending in particular are difficult to obtain. Although the government’s ‘common areas of spend’ (CAS) guidance provides some terms of reference for classifying services as ‘consultancy’, especially for procurement purposes, ²⁶ Cabinet Office, ‘Common areas for spend: data definitions’, last updated 2021, retrieved 10 December 2024, www.gov.uk/government/publications/common-areas-of-spend-data-definitions  the National Audit Office (NAO) has noted that the boundaries between the ‘consultancy’ and ‘professional services’ spending categories are unclear and that the distinction is applied inconsistently across departments. ²⁷ Comptroller and Auditor General, Use of Consultants and Temporary Staff, Session 2015–16, HC 603, National Audit Office, 2016, www.nao.org.uk/wp-content/uploads/2016/01/Use-of-consultants-and-temporary-labour.pdf  This limits the utility of annual reports and accounts in determining accurate figures for consultancy spend – but they are the only source of such figures that the government publishes consistently. 

As outlined in the text, consultancy spending can also be estimated by analysing invoices for payments to suppliers that provide consultancy services, which departments publish. This was the method the Cabinet Office used to produce consultancy spending estimates while the now-abolished consultancy and professional services spend control that the coalition government introduced was in force. Suppliers can be identified as providing consultancy services by their Standard Industrial Classification (SIC) code. This is the method that Tussell, a provider of public procurement data, used in previous Institute for Government research. ²⁸ Paxton B and Davies N, Improving Accountability in Government Procurement, Institute for Government, 2024, www.instituteforgovernment.org.uk/publication/accountability-government-procurement  While SIC codes can be used to determine departmental spending with suppliers that provide consultancy services, they do not indicate the reason for the spending on each individual invoice. For example, a department could pay a company that provides consultancy services as per its SIC code, but for another service that is not consultancy related, and this would still count

Departmental spending 

Throughout the departmental spending chapter, we focus on departmental expenditure limits. And in all charts except Figure 2.46, we focus on resource departmental expenditure limits (RDEL – day-to-day departmental spending). 

To calculate how spending has changed in different departments since 2010/11 (Figures 2.43 and 2.45), we use successive Public Expenditure Statistical Analyses. Departmental boundaries and classifications change over time, but they are consistent within each annual publication, which covers the five previous years. To calculate changes over time for each department, we therefore start with the most recent data (in the 2024 publication, covering back to 2018/19). For every previous year, we calculate spending in that year based on the percentage change between that year and the year after in the relevant publication. So, for example, spending in 2017/18 is calculated as the 2018/19 value in the 2024 publication multiplied by the change between 2017/18 and 2018/19 in the 2023 publication. For this analysis, we only include departments that have existed in broadly their current form since 2010. The exception is FCDO, where we calculate the FCDO budget before the merger as the sum of FCO and DfID budgets. In Figure 2.45 we interpolate the 2020/21 and 2021/22 budgets for departments, because several departments saw very large temporary increases related to Covid spending, which would distort the axis on the chart and make the figure less clear. 

We calculate changes in planned spending (Figures 2.46 and 2.47) using successive Public Expenditure Statistical Analyses, which present plans at the start of the year and the final outturn each year. When ranking changes in budgets over time, we exclude those departments with small budgets (below £1.5 billion in 2024/25 prices), and increases in 2019/20, 2020/21 and 2021/22, which were due to Covid-related spending that was inherently difficult to plan for. We include all departments that overspent their original budget by 13% or more.

Arm’s-length bodies 

Throughout this report we use the term ‘arm’s-length bodies’ (ALBs), which is a narrower subset of ‘public bodies’. The category of ALB encompasses non-departmental public bodies, executive agencies and non-ministerial departments. The wider term ‘public bodies’ includes public corporations, unclassified bodies and parliamentary bodies, which are not included in the Cabinet Office data we rely on in several charts. 

The Cabinet Office provided figures for the number of ALBs in 2021/22 and 2022/23 (Figure 2.48). To calculate the number of ALBs in 2023/24, we used information provided directly to the Institute on the number of ALBs up to March 2023 and bodies opened and closed since then, and adjusted for public announcements on the establishment or abolition of bodies according to GOV.UK or each body’s own website. 

The Cabinet Office provided figures on the number of bodies that have been reviewed as part of the public body review programme (Figure 2.51), and these are accurate as of November 2024. 

For details on how population benchmarks for women, minority ethnic individuals and individuals with a disability (Figure 2.52) are calculated, see the ‘Diversity’ subsection above. To calculate the population benchmark of individuals of working age (aged 16–64) living outside London and the South East, we used the mid-2022 edition of the ONS dataset ‘Estimates of the Population for the UK, England, Wales, Scotland, and Northern Ireland’.