Migration and Displacement (MDI) Predictive Displacement Project
Predictive Analytics to Better Support Vulnerable Populations When They Need It Most
Response Innovation Lab is working with Save the Children’s Migration and Displacement Initative (MDI) and their Predictive Displacement Project to host local convener events - in Iraq and Jordan - around the development of a predictive analytics tool that will anticipate the scale and duration of conflict-driven displacement crises. At present, the lack of good data on the eventual scale and duration of forced displacement crises make it difficult for humanitarian actors to efficiently and sustainably plan for early stages interventions. Lack of demographical data also limits the efficiency and effectiveness with which they can plan for the specific needs of vulnerable groups within displaced populations. MDI seeks to use historical and contemporary data and machine learning to predict these characteristics of displacement, enabling better responses.
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The use of predictive analytics in displacement work in the humanitarian sector has grown significantly amongst international organisations. There appears however to have been limited involvement or consultation with field-level stakeholders. The convening events held with the Response Innovation Lab in Iraq and Jordan focus on identifying and gathering the perspectives and input of other potential end-users of predictive analytics tools and other relevant actors, with Save the Children’s displacement model as an initial reference.
Credit: Gabriele Francois Casini/Save the Children
Particularly, the interest is in actors not well represented in typical discussions around predictive analytics in the humanitarian sector: national and sub-national level actors working on displacement issues, local and regional research and policy centers and commercial actors with a stake in predicting population movements.
Objectives
Identify and establish a network of relevant actors
Understand how those actors
i) make decisions about planning for displacement responses
ii) how predictive analytics in general and our model specifically could impact/support their work
iii) perceive associated risks and issues
The input of these actors will help shape our thinking for the third, external facing phase of our project, and be a network through which to carry out rollout of this and other predictive tools. Learning from the exercise will be shared with other humanitarian actors to similarly inform their work.