Blog Series: Part 4
Innovation in Anticipation for Migration: A Deep Dive into Methods, Tools, and Data Sources
Posted on 9th of November 2023 by Sara Marcucci, Stefaan Verhulst
In the ever-evolving landscape of anticipatory methods for migration policy, innovation is a dynamic force propelling the field forward. This seems to be happening in two main ways: first, as we mentioned in our previous blog, one of the significant shifts lies in the blurring of boundaries between quantitative forecasting and qualitative foresight, as emerging mixed-method approaches challenge traditional paradigms. This transformation opens up new pathways for understanding complex phenomena, particularly in the context of human migration flows.
Second, the innovation happening today is not necessarily rooted in the development of entirely new methodologies, but rather in how existing methods are adapted and enhanced. Indeed, innovation seems to extend to the utilization of diverse tools and data sources that bolster the effectiveness of existing methods, offering a more comprehensive and timely perspective on migration trends.
In the context of this blog series, methods refer to the various approaches and techniques used to anticipate and analyze migration trends, challenges, and opportunities. These methods are employed to make informed decisions and develop policies related to human migration. They can include a wide range of strategies to gather and interpret data and insights in the field of migration policy.
Tools, on the other hand, refer to the specific instruments or technologies used to support and enhance the effectiveness of these methods. They encompass a diverse set of resources and technologies that facilitate data collection, analysis, and decision-making in the context of migration policy. These tools can include both quantitative and qualitative data collection and analysis tools, as well as innovative data sources, software, and techniques that help enhance anticipatory methods.
This blog aims to deep dive into the main anticipatory methods adopted in the field of migration, as well as some of the tools and data sources employed to enhance and experiment with them. First, the blog will provide a list of methods considered; second, it will illustrate the main innovative tools employed, and finally it will provide a set of new, non-traditional data sources that are increasingly being used to feed anticipatory methods.
List of Methods and Criteria of Selection
As mentioned in the introduction to this blog, the prevailing innovation in the field of migration policy anticipatory methods seems mostly to lie in the adaptation and enhancement of existing methodologies, rather than the creation of entirely new ones. This transformative approach is further reinforced by the integration of diverse and innovative tools and data sources, significantly enriching the effectiveness of these methods. Therefore, the list of methods here illustrated prominently features traditional methodologies, as they form the bedrock upon which innovation is built through the use of innovative tools and data sources, enhancing their capacity to address the intricate challenges posed by human migration flows.
Simulation and Modeling
Science Fiction Narratives
Early Warning Systems
Participatory Action Research
System Dynamics Modeling
Weak Signal Analysis
Focus Group Discussions
Table 1: List of Selected Methods.
The selection criteria for the list of anticipatory methods for migration policy included:
Usage in Migration Policy: This criterion focused on the relevance and applicability of the method within the context of migration policy. Methods that have a history of being used in the field were prioritized.
Proven Efficacy: Methods with a demonstrated track record of effectively providing valuable insights and facilitating decision-making in migration policy were given preference.
Innovative Data Sources and Tools: A significant emphasis was placed on methods that displayed a propensity for integrating innovative data sources and advanced tools. This recognition of innovation was identified through the compilation of a repository of use cases where these methods had effectively leveraged modern resources to enhance their capabilities.
Interdisciplinary Applicability: Consideration was given to methods that possess the capacity to bridge different disciplines and fields of knowledge, acknowledging the multifaceted nature of migration issues and their intersection with various fields.
The criteria of selection for the list of methods were intentionally designed to encompass fairly broadly understood methods while excluding those that are similar or contained within the broader method already included. This selection approach serves the purpose of offering a comprehensive and diverse toolkit for practitioners in the field of migration policy. The rationale for this lies in the attempt to minimize redundancy, ensuring that practitioners have access to a wide range of approaches for addressing the multifaceted challenges of migration policy.
Indeed, excluding methods that are too specific or closely resemble broader methods already listed helps to avoid repetition. It ensures that each included method brings a unique perspective and approach to the table, enhancing the overall diversity of the list. For example, the list includes Trend Analysis but excludes Extrapolation, as Extrapolation is a specific kind of trend analysis. Similarly, it encompasses Participatory Action Research and Citizen Panels but excludes Appreciative Inquiry, which is a specific approach within those broader methods. Additionally, it includes the Delphi Method, Expert Panels, and Expert Interviews but excludes Argument-based forecast, which can be seen as a specific approach within the Delphi method.
By employing these criteria and conducting a comprehensive analysis of the methods through the repository of use cases, the list was constructed to reflect a balanced and forward-looking approach in the field of migration policy. These methods, with their adaptability to new data sources and tools, can empower stakeholders to address the complexity of human migration with a versatile and informed perspective. Find here our repository of methods, which includes methods definitions, relevant tools for each method, and specific uses and real-world examples in migration.
Below we illustrate the allocation of these methods within the three categories we have identified in the previous blog of this blog series, namely (1) Experience-based Methods, (2) Expertise-based Methods, and (3) Exploration-based Methods. The following section will illustrate the tools and data sources that can be used to enhance and augment these methods.
Figure 1: Allocation of methods.
Innovative Tools and Data Sources
As mentioned above, a lot of the innovation happening in the anticipation realm is related to the increasing amount and types of tools available to be used to innovate and augment anticipatory methods. Below, we identify ten main categories of tools and list a few per category. Please note that this list does not aim to be exhaustive, but only to give a sense of the tools available. Additionally, it is important to note that many of these tools are available in a variety of sectors which are not necessarily related to migration. However, it seems worth acknowledging their increasing availability and importance, as they hold potential for adoption in the realm of anticipatory methods for migration policy.
Quantitative Data Collection and Analysis
Qualitative Data Collection and Analysis
Expert and Stakeholder Engagement
Creative and Collaborative Techniques
Scenario Building and Planning
Environmental Scanning and Trend Analysis
Modeling and Simulation
Risk Assessment and Management
Futurist Tools and Methods
Early Warning and Counterfactual Analysis
Table 2: Categories of Tools for Anticipatory Methods in Migration.
Further, increasing levels of datafication and the rising adoption of digital systems to operate within the migration policy field have brought about a variety of new data sources. These are non-traditional data sources, which we have mentioned in our previous blog. The University of Manchester Global Development Institute’s “The Data-Powered Positive Deviance Handbook” defines Non-Traditional Data (NTD) as: “data that is digitally captured (e.g. mobile phone records and financial data), mediated (e.g. social media and online data), or observed (e.g. satellite imagery)”. In the context of anticipating migration, this can include, among others:
Social Media Posts
Social media platforms like Twitter, Facebook, and Instagram can serve as a source for monitoring discussions, sentiments, signals of migration intentions, and real-time events related to migration.
Weather and Climate Data
Weather data from sources like the National Oceanic and Atmospheric Administration (NOAA) can be used to assess the impact of extreme weather events on migration patterns.
Platforms like Ushahidi and FrontlineSMS allow the collection of real-time data from individuals and communities, which can include information on migration patterns, emergencies, and needs.
Remote Sensing Data
Data from remote sensing technologies, like drones and LiDAR, can offer information on border surveillance, environmental factors, and disaster response.
High-resolution satellite imagery, such as that provided by Planet Labs or DigitalGlobe, can be used to track border movements, refugee camp expansion, and natural disaster impact on migration.
Humanitarian Data Exchange (HDX)
HDX offers data on humanitarian responses and activities related to migration, including resource allocation and needs assessments.
Mobile Phone Data
Data from mobile network operators, including call records and location data, can help track the movements of internally and internationally mobile populations and provide insights into migration trends.
Health Records and Epidemiological Data
Data from community health workers, digital health apps, wastewater data for infection rates, telemedicine platforms, and epidemiological data collected from non-traditional sources.
In the context of migration policy analysis, non-traditional financial data can encompass various sources such as cryptocurrency-based transactions, mobile money transfers, cross-border financial flows, and informal remittance networks.
Digital Trace Data
Analysis of digital traces, such as Wi-Fi connections, can help track the movement of migrants in transit.
Online Forums and Communities
Online discussion forums, such as Reddit or specialized migration-related platforms, can provide qualitative insights into migrant experiences and concerns.
Flight and Travel Data
Airline flight data and travel booking information can provide insights into international travel patterns and destinations of migrants.
Table 3: Categories and Definitions of Non-Traditional Data Sources for Anticipatory Methods in Migration.
In our next blog, we will present a picture of the levels of maturity and time zones of prediction of anticipatory methods, so as to inform decision makers on how to employ each method based on the specific timescale and urgency inherent to various predictive tasks.
If you haven’t already, check out the previous blogs on the blog series webpage and stay tuned as we uncover innovative approaches to address the complexities of migration!
We would like to express our gratitude to members of the BD4M Alliance Anna Rosinka (JRC) and Alina Menocal Peters (IOM) for their valuable reviews of this piece before its publication.
The cover image of this blog was created using Perchance and was adapted to make it relevant to the content.