Using Data for Resource Allocation
Tech Deep Dives are best suited to our more technically advanced members. This session will look at 'Using Data Science to Allocate State Resources' and will be delivered by our member organisation, Pobal.
Summary: In this session, Pobal's Principal Data Scientist, Dr Patrick Collins, will demonstrate how data science is used to underpin the allocation of hundreds of millions of euros in state funds. The presentation will cover relative national supply/demand models, the operationalising of census data, and the creation and implementation of policy-specific Resource Allocation Models (RAMs). This technical deep dive will provide an overview of the practical application of data to directing state resources, with a specific focus on geographic data analysis techniques that support defensible and objective decision-making.
Learning Outcomes:
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Understand the role of data science in state fund allocation.
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Learn about national supply/demand models and their applications.
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Explore how census data can be operationalized for resource allocation.
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Mathematics of resource variable manipulation and Mixed modelling
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Gain insights into creating and implementing policy-specific resource allocation models.
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Develop knowledge of geographic data analysis techniques for objective decision-making.
Target Audience: This session is ideal for data scientists and analysts working in, or thinking about working in the public sector, as well as anyone involved in using analytics to optimise budget planning and fund allocation processes. Participants will benefit most if they are familiar with R Studio and ArcGIS.
This masterclass is part of our ‘Technical Deep Dive Masterclass’ series delivered by our member organisations on a monthly basis. If you or your organisation would like to run your own masterclass for the benefit of our community, please get in touch.
