The WMREDI Data Lab provides data insights for the West Midlands and the UK.
The Birmingham Economic Review 2022
These dashboards provide data insights to accompany the Birmingham Economic Review 2022, an in-depth exploration of the economy of England’s 2nd city and a high-quality resource for informing research, policy and investment decisions.
Levelling Up and SDGs - coming soon!
This dashboard looks at how the levelling up missions contribute to sustainable development goals. To do this we match the missions to sustainable development goals comparing performance at a Local Authority level.
This data dashboard explores the impact and relationships of Higher Education providers and their place. Using various metrics and categories, HE providers and their local geographies are ranked and compared on how integral HE providers are to their area in the form of civic impact.
The MIT Regional Entrepreneurship Acceleration Program (MIT REAP) is a program of engagement with regions to verify innovation-driven entrepreneurship. This dashboard illustrates how innovative and entrepreneurial Birmingham/West Midlands is compared to the national average.
The City Index
This data dashboard compares and ranks 61 English cities according to various metrics and categories. Many publications and literature will often focus on an aspect of city ranking such as sustainability, but the City Index tool is a rounded measure that seeks to explore all major factors as to what makes a successful city.
Children in Trouble
This tool is a set of interactive dashboards which aims to spot Middle Layer Super Output Areas areas in the West Midlands where children may need support. The analysis estimates the number of children in trouble in each area with an aggregated metric which is constructed from four different datasets.
Homelessness in the West Midlands
The homelessness prediction tool is developed to foresee how homelessness rise will hit areas across West Midlands. The prediction tool relies on what has been known about likelihood of people to experience homelessness and is based on data from multiple data sources.