A researcher at the University of Essex in the UK is working on a project that is looking at the potential of big data to prevent homelessness.
Professor Vania Sena believes that the vast swathes of data held by local authorities can be mined to predict when people need help.
Professor Sena is currently working with Suffolk and Essex County Councils to analyze large sets of citizen data and use algorithms to predict households that might require extra support.
Big Data Benefits
The aim is to discover those who are in dire need and help them before they end up on the streets. The benefits of such a big data approach are not only for individuals but also for the councils.
By the time somebody becomes homeless and they are sleeping rough, the cost to the public purse of helping them is even greater. According to Crisis, the UK national charity for homeless people it can cost £20,128 (approx. USD $26,000) to help someone who has been sleeping rough for one year or more. The costs of interventions are far less at £1,426 per person. Preventing 40,000 people from becoming homeless could save £370 million per year.
By using predictive analytics councils could also create hotspots of communities that are most under pressure.
“The council can then work with the community on a comprehensive set of interventions, to try to reduce the risk that each individual could face,” Prof. Sena told the Big Issue, a street newspaper sold by homeless people.
If big data starts to make a positive impact on the number of people on the streets in Essex other councils elsewhere in the country may adopt similar approaches.