Strengthening National Evidence‑Informed Policymaking Ecosystems

Annex B. Examples of best practices from other European and OECD countries identified in the context of the project

This complementary annex presents best practices from other European and OECD countries that were identified during the EIPM project, particularly as part of the needs and gaps assessment, and to help identify best practices to inspire the seven participating countries. For clarity, they are presented separately.

Box A ‎B.1. Pairing schemes and other policy engagement opportunities in Europe and beyond

Pairing schemes are programmes where researchers and policymakers (MPs, parliamentary staff, diplomats, or civil servants) spend time together to build personal relationships and raise awareness about each other’s worlds. Some schemes are also accompanied by introductory workshops and training in use of science for policy. These schemes can aid researchers in better understanding how policymaking operates, how evidence can play a role, and how they can interact and engage with the policy process. On the policy side, they can help policymakers gain access to scientific knowledge, increase their network with the scientific world, and increase their likelihood of actively considering evidence in decision-making processes. Schemes can vary in terms of length, number and profile of participants, and type of organisation managing the programme (Parliamentary Office, learned society, university, embassy, etc.).

Popular examples are the Royal Society Pairing Scheme in the United Kingdom, the Oficina C Programa de emparejamiento in Spain, the JRC’s Science meets regions pairing schemes, the Leibniz im Bundestag and the Mercator Science-policy Fellowship Programme in Germany. Additional policy engagement opportunities can take the form of open doors programmes, run by many public organisations (ministries, embassies, international organisations); and the JRC’s Science meets Regions innovation camps and participatory events.

Source: (AAAS, 2017[1]) (Lacunza et al., 2021[2]) (Hill, 2023[3]) (European Commission, n.d.[4])

Box A ‎B.2. Examples of Policy Analysis tracks and expert professions in the civil service

The United Kingdom Framework of Digital Professionals

In 2015, the United Kingdom’s Government Digital Services (GDS) started conducting a broad mapping of digital skills in the government to evaluate the capacities and needs of the British government, to in turn promote a modern and agile digitally driven civil service. This mapping looked at digital professionals as well as product manager, user researcher and delivery manager roles – all of which are indispensable for well-functioning digital services. This mapping exercise has shown that employees with such digital skills had different job titles, functions and salaries within the British public sector. Based on this mapping, the GDS developed the “Digital, Data and Technology Capability Framework” that includes 37 jobs and identifies the skills needed for each of them, as well as the competences needed to advance to a higher-level title within each job. This framework has helped the UK civil service address the issue of digital professionals’ recruitment and career advancement, identify capacity gaps to design training and facilitated the creation of community of practice.

The Irish Government Economic Evaluation Service

In Ireland, the Irish Government Economic and Evaluation Service (IGEES) has a role as an economic and analytical resource co-ordinator across government. The IGEES manages a network of analytical staff who are hired centrally and later posted in line departments. The IGEES staff conduct economic analysis and evaluations, and more generally contribute to better policymaking in the line departments. IGEES was launched in 2012 in the aftermath of the Global financial crisis, initially aimed at ensuring the quality-for-money of public policies in response to budgetary pressures (OECD, 2020[5]). On average, 20 recent graduates are hired through this scheme every year, which brings the total number of analysts hired by IGEES to over 150 across the government. The IGEES also supports network building and knowledge sharing by providing its staff with incentives for mobility: after an initial 2-year period, staff will move either within the department or to another department. A learning and development framework has also been established whereby IGEES staff receive training in the following areas: policy analysis and evaluation methods, appraisal methods, data and advanced quantitative methods, and applied economics (OECD, 2020[5]).

Statistician Economists in France

In France, the National Institute of Statistics and Economic Studies (INSEE) has an inbuilt tertiary educational system, which trains a set of specialists in economic, statistics and econometric analysis through the ENSAE school, and statisticians and data scientists at the ENSAI school. Part of the graduates from these schools are to be enrolled in the civil service and receive a stipend during their studies in exchange for working in the civil service for a minimum period of 8 years. Within the civil service, graduates from the ENSAE/ENSAI serve in the analytical offices in each ministry, as well as a variety of public institutions such as France Stratégie or the Central Bank. At entry level, this pool of graduates is co-ordinated centrally by INSEE, thus creating a shared marketplace for analytical and statistical skills across the public sector. INSEE also has an important role in fostering and developing analytical competencies across government, by providing professional training aimed at all civil servants, organising seminars to foster knowledge sharing and encouraging mobility of analytical staff between line ministries. The scheme, which has been operating since the inception of INSEE in 1946, was part of a set of key reforms aimed at modernising the civil service in the after-war recovery period to ensure that the French public administration would be equipped to deal with modern challenges.

Source: (OECD, 2021[6]) (OECD, 2020[5])

Box A ‎B.3. Chief Scientific Advisers in the United Kingdom

Most government departments in the United Kingdom have a chief scientific adviser (CSA). It is the CSAs role to put mechanisms in place to ensure that policymaking is underpinned by science, and that this science is of high quality. These advisers tend to be recruited at the senior level (usually either Director or Director General), and have a history as a scientist or engineer with high standing in their field. They provide advice to ministers, discuss and facilitate implementation of policy in science and technology-related areas, and identify and share any good practices. They also facilitate communication on issues relating to science and technology-related policy. Furthermore, they are responsible for developing an R&D strategy for their department, helping to direct their scientific evidence needs.

These departmental CSAs work under the leadership of the Government Chief Scientific Adviser to support each other and resolve issues that do not fall strictly under one department’s jurisdiction. This is predominantly done through the CSA network, a forum with weekly meetings chaired by the Government Chief Scientific Adviser.

Source: (Government Office for Science, 2020[7])

Box A ‎B.4. United Kingdom Statistical Authority structure

Powers within the United Kingdom are devolved to the different nations – for example, Scotland, Wales and Northern Ireland all have government responsibility for policy decisions around agriculture, education, health, and housing, among others. The United Kingdom statistical system reflects this, in that statistics on UK-wide policy matters are produced by the country’s national statistics institute, the ONS, while statistics for devolved policy matters are produced by the nation in question.

In 2007, the Statistics and Registration Service Act created a Statistics Board with the authority to promote and safeguard production of all United Kingdom statistics, ensuring they serve the public good. The board monitors the work of the Government Statistical Service, including the work by statisticians for the devolved responsibilities. To do this, it established the Code of Practice for Official Statistics. This code has three key pillars:

• Trustworthiness: This includes requirements that statistics are truthful, impartial and independent, that they are released in an orderly and transparent manner, and that organisations look after people’s information securely.

• Quality: This includes requirements that statistics are based on the most appropriate data, with any data limitations minimised and explained, and that statistics fit their intended uses.

• Value: This includes requirements that statistics should be relevant users, accessible, and able to provide meaningful insight, as well as be published in forms that enable their reuse.

The Code also has three cross-cutting themes: collaboration, coherence and transparency. If official statistics are to be approved as national statistics – both for centralised and devolved policy areas – they must be approved as compliant with all 74 statements within the Code. Since the implementation of this code, several surveys have noted an improvement in public perception of United Kingdom official statistics.

Source: (Statistics Canada, 2016[8]) (UK Statistics Authority, 2024[9])

Box A ‎B.5. French Secure Data Access System

France’s national statistics institute INSEE created the Secure Data Access System (CASD) in 2010, with the stated aim of enabling the secure processing of sensitive data for researchers and data scientists. The system provides access to data from France’s national statistics institute, as well as from the Ministries of Agriculture, Education, Finance, Health and Justice. It also provides external access to private companies’ data for collaboration with researchers, start-ups and consultants. Today, it has secured about 350 data sources and shared more than 200 publications.

In order to ensure data remained anonymised, the CASD team designed a computer box, known as the SD-Box, which allows a user to have secure remote access to confidential data. No data can escape from this bubble without a control procedure, and no user can access it without authentication, carried out using a smart card. This ensures that data is contained and traceable, with minimal impact on the ability of the researcher to gain access to the data they need.

Source: (INSEE, 2019[10])

Box A ‎B.6. Capacities for evidence informed policymaking and strategic foresight in Finland

Finland has one of the most sophisticated foresight systems in the world. Foresight capacities exist across government, at both national and regional levels, as well as within civil society, academia and the private sector. Many of these capacities combine within the Finnish National Foresight Network, forming a complex foresight ecosystem with a high degree of inclusiveness. The Finnish National Foresight Network operates under the authority of the Prime Minister’s Office and foresight capacities exist in all ministries.

Beside government, SITRA, Finland’s independent innovation fund, is tasked with carrying out foresight analysis and promoting economic growth. SITRA is accountable only to the parliament, and its independence from the executive is ensured by its autonomous funding - the returns of its invested capital. SITRA has a mandate to “ensure the future wellbeing of Finland” and to “support and challenge” government, often by raising issues that are not always a priority for those in power. More concretely, in the 2021-2024 SITRA’s work focuses on three key challenges: finding solutions to the ecological sustainability crisis, promoting a fair data economy and strengthening democracy and participation. Underpinning all its operations, however, is SITRA’s strategic goal of supporting a renewal of the economy by aiming at sustainability and competitiveness. In this respect, SITRA also plays an important foresight function, conducting studies and issuing publications.

Source: (OECD, 2022[11]; Sitra, n.d.[12])

References

[1] AAAS (2017), “Connecting Scientists to Policy Around the World”, https://www.aaas.org/resources/connecting-scientists-policy-around-world (accessed on 31 March 2025).

[4] European Commission (n.d.), “Science meets regions pairing schemes”, https://joint-research-centre.ec.europa.eu/science-meets-regions/pairing-schemes_en (accessed on 31 March 2025).

[7] Government Office for Science (2020), “Guidance for government Chief Scientific Advisers and their Officials”.

[3] Hill, C. (2023), “GeoPolicy: Science-Policy Pairing Schemes in Europe – a regularly updated list”, https://blogs.egu.eu/geolog/2023/12/22/geopolicy-science-policy-pairing-schemes-in-europe-a-regularly-updated-list/ (accessed on 31 March 2025).

[10] INSEE (2019), “Le Centre d’accès sécurisé aux données (CASD), un service pour la data science et la recherche scientifique”, https://www.insee.fr/fr/information/4254227?sommaire=4254170 (accessed on 18 January 2024).

[2] Lacunza, I. et al. (2021), “How to set up a knowledge exchange experience in policy and/or diplomacy for researchers. The S4DC4 Open Doors Experience”, https://www.s4d4c.eu/wp-content/uploads/2021/04/S4D4C_D5.9_open-doors-report_revised.pdf (accessed on 31 March 2025).

[11] OECD (2022), Foresight and Anticipatory Governance in Practice: Lessons in Effective Foresight Institutionalisation, Strategic Foresight Unit, Office of the Secretary-General, https://www.oecd.org/content/dam/oecd/en/about/programmes/strategic-foresight/foresight-and-anticipatory-governance-2021.pdf.

[6] OECD (2021), “The OECD Framework for digital talent and skills in the public sector”, OECD Working Papers on Public Governance, No. 45, OECD Publishing, Paris, https://doi.org/10.1787/4e7c3f58-en.

[5] OECD (2020), The Irish Government Economic and Evaluation Services: Using Evidence-Informed Policy Making to Improve Performance, OECD Publishing, Paris, https://doi.org/10.1787/cdda3cb0-en.

[12] Sitra (n.d.), Sitra Publications website, The Finnish Innovation Fund Sitra, https://www.sitra.fi/en/publications/ (accessed on 15 June 2025).

[8] Statistics Canada (2016), “Compendium of Management Practices for Statistical Organizations from Statistics Canada’s International Statistical Fellowship Program”, https://www150.statcan.gc.ca/n1/pub/11-634-x/11-634-x2016001-eng.htm (accessed on 19 January 2024).

[9] UK Statistics Authority (2024), “Code of Practice for Statistics”, https://code.statisticsauthority.gov.uk/the-code/ (accessed on 19 January 2024).