Stage 2: Data, Research and Analysis for Policymaking

Data, research and analysis are central to national strategies on migration and developing effective and sustainable policies (see Developing migration policy). Sound evidence can create coherence between:

• policies and programmes
• policy sectors
• national and subnational levels of government
• national migration policies and international obligations and standards

Evidence is also important for:

• planning for future opportunities and challenges, including in the realm of foreign policy
• mobilizing resources for the development and implementation of policies

The United Nations has highlighted the importance of data and research on migration in recent high-level global initiatives:

• The 2030 Agenda for Sustainable Development Goal 17 Target 18 sets out the need to increase the availability of high-quality, timely and reliable data across development sectors that are disaggregated by migratory status, to monitor progress towards meeting targets. At least eleven of the seventeen Sustainable Development Goals (SDGs) contain targets and/or indicators directly relevant to migration that need improved data. In addition, several targets are either directly or indirectly relevant to migration, and either specialized migration data, or other data disaggregated by migratory status, will be required to monitor their progress.
• The Global Compact for Safe, Orderly and Regular Migration sets out in its first objective “improving and investing in the collection, analysis and dissemination of accurate, reliable, comparable data, disaggregated by sex, age and migration status and other characteristics relevant in national contexts”. The aim is to “ensure this evidence fosters research, guides well-informed and coherent policymaking and public discourse, and allows for effective monitoring of the implementation of commitments over time.” Objective 1 also recommends several ways to improve migration data, including developing a global programme to build national migration data capacities, supporting relevant databases (including the Global Migration Data Portal) and establishing regional centres for migration research and training. This objective is significant because it recognizes that evidence is central to migration governance and relevant for action under all other objectives.

While global momentum for improving migration data has never been stronger, this is a challenge that requires political and institutional commitment. It requires the allocation of sufficient resources: both human and technological resources, feasible and sustainable plans of action and ongoing capacity-building to create a “data aware” policy environment.

Timely and sound data: Without data of good quality, coverage and timeliness, it is not possible to develop informed migration-related policies or to plan programme activities that can be monitored effectively and transparently.

Comparable data: Different concepts and definitions related to migration data are often used across and even within countries (see Concepts and definitions and Frameworks, standards and guidelines on migration data in What is data for policyamking? this chapter). Comparability of migration data within and across countries and regions is vital for the development of effective policies and to support international cooperation on migration [IOM Global Migration Data Analysis Centre (GMDAC), 2018]. In order to compare migration data, though, standardized concepts and definitions are required.

Cross-sectoral data: Data gaps remain in many areas. Appropriate collection of data – especially if appropriately disaggregated – could shed light on the often “hidden” dimensions of migration as well as on migration-relevant aspects in public policy areas (such as health, education, housing and transport, access to legal services), allowing for policy to be crafted in these areas.

Data, research and analysis quality and credibility: In an era of rapid change, when increasingly influential digital technologies make it increasingly easy to produce and share information, quality and credibility of data, research and analysis pose additional challenges. Finding ways to evaluate, contextualize and effectively use this wealth of existing information is as important as ensuring that new sources of evidence produce good quality and credible information (see details on data innovation and new sources in Accessing relevant data for policymaking). Having irrelevant or low-quality evidence is as ineffective as having too little evidence.

Identifying, accessing, assessing and using relevant data, analysis and research: Identifying and using relevant evidence can be challenging, especially when policymakers need to respond to issues quickly (see McAuliffe, Bauloz and Kitimbo, 2020, for a discussion related to the challenges of doing real-time analysis in the context of the health pandemic triggered by COVID-19). Data, research and analysis on specific migration topics are sometimes missing or may not be accessible. Even when data are available, they may be unknown to government officials, may not be of good quality, and may be ultimately disregarded (see Accessing relevant research and analysis for policymaking).

Contrasts in how policy and research sectors operate: Research timelines can be lengthy while policymakers usually work with time pressures. While researchers would benefit from a better understanding of policy processes in order to better tailor research to inform policymaking, so too would policymakers benefit from a greater understanding of research development (IOM, 2017: 95–96).

People, power and politics: These elements should be understood when identifying evidence to be used for policymaking. Policymaking is not value neutral, and informing policies with unbiased empirical evidence is not straightforward. First, research designs and data collection instruments (such as survey questionnaires) can vary, and the answers provided by people surveyed can be biased. Second, migration takes place in the context of politics, and can often be a highly politicized topic. This impacts the ways in which migration data are interpreted, how the research and analysis are reflected back to the policymaker, and how the data and research are used in the policymaking process. Third, actors with power may be more interested in evidence that is closer to their political ideology and as a result some evidence may be marginalized.

Policymaking is multilevel and multi-actor. It extends across various levels of governance and involves both public and private actors. These factors impact the way data and research can be used in order to produce evidence-based policies.

Sound evidence is needed at the outset, in order to clearly establish the policy question at stake, and then to establish what additional evidence is needed to address it. It is important to seek evidence to inform potential policy options, and to avoid seeking evidence to simply justify policies already decided (Boswell, 2009).

While data, research and analysis constitute a specific stage of the policy cycle, they are also relevant to all stages. It is important that they be not seen as a stage that is “done” before moving on the next, but rather as requirements for informing each stage from issue identification, through policy formulation, implementation and evaluation.

Below is a table summarizing the different policy cycle stages and the role and type of evidence needed in each stage: