Today, we are excited to launch the Big Data For Migration Alliance (BD4M) Repository of Use Cases for Anticipating Migration Policy! The repository is a curated collection of real-world applications of anticipatory methods in migration policy. Here, policymakers, researchers, and practitioners can find a wealth of examples demonstrating how foresight, forecast and other anticipatory approaches are applied to anticipating migration for policy making. 

Migration policy is a multifaceted and constantly evolving field, shaped by a wide variety of factors such as economic conditions, geopolitical shifts or climate emergencies. Anticipatory methods are essential to help policymakers proactively respond to emerging trends and potential challenges. By using anticipatory tools, migration policy makers can draw from both quantitative and qualitative data to obtain valuable insights for their specific goals. The Big Data for Migration Alliance — a join effort of The GovLab, the International Organization for Migration and the European Union Joint Research Centre that seeks to improve the evidence base on migration and human mobility — recognizes the importance of the role of anticipatory tools and has worked on the creation of a repository of use cases that showcases the current use landscape of anticipatory tools in migration policy making around the world. This repository aims to provide policymakers, researchers and practitioners with applied examples that can inform their strategies and ultimately contribute to the improvement of migration policies around the world. 

As part of our work on exploring innovative anticipatory methods for migration policy, throughout the year we have published a Blog Series that delved into various aspects of the use of anticipatory methods, exploring their value and challenges, proposing a taxonomy, and exploring practical applications.

The value of mapping the complex landscape of uses of anticipatory methods for migration is to understand the applications of these methods to create policies that are relevant and responsive to migrant populations’ needs.  

The repository has three main filters:

• Policy Objectives: Considering the specific objectives and the broader context of the projects is important to decide on the type of anticipatory method that will be used for a project. Some methods may work better for specific objectives that fit the desired outcomes of the project or policy that has been implemented. To learn more about the uses of anticipatory methods for migration policy objectives, read this blog. 

• Typology of Method: We created a taxonomy of anticipatory methods, categorizing them into three distinct sub-categories: Experience-based, Expertise-based, and Exploration-based methods. The focus of the taxonomy is the practical applications of these methods, and how both traditional and non-traditional data sources play a pivotal role within each of these categories. To learn more about how the taxonomy was developed, read more on this blog. 

• Timeframe of Anticipation:  The timeframe of the anticipatory method is essential when considering what is an appropriate anticipatory method for each specific project. Anticipatory methods differ in the length of their time frames into the future and this temporal dimension is important for the relevance and applicability of the insights generated by its use. To learn more about timeframes, read more on this blog.

We encourage you to explore the repository and learn more about the work that has been done using anticipatory methods for migration policy-making. 

The repository will be constantly updated with new examples. If you lead or know of projects that use anticipatory methods for migration policy-making and are not included already in the repository, do not hesitate to reach out to us through the Contact Form on our website to include your project in the repository!

Back to the Blog