How to Use Data Science to Improve Social Housing

Posted 2017-11-20T Posted by Tom

Using data for social good is important and is one field that is developing at a rapid rate. Multiple charities and social schemes are looking for ways to improve their practices and increase their capabilities and funds by making the best use of the data that they hold. John Gardner, the former president of Carnegie Corporation explained that

“Wealth is not new. Neither is charity. But the idea of using private wealth imaginatively, constructively and systematically to attack the fundamental problems of mankind is new.”
Firms in a variety of industries across the globe are enhancing their practices through the adoption of sophisticated tools that enable improved use of the data that they hold. Palantir, one of ‘big data’s’ leading names has developed programs that nonprofit organisations can benefit from. One such organisation is Mercy Corps, who are using analytics to help predict refugee crises on a large scale. This will help Mercy Corps to prepare in advance and ensure that essential supplies are readily available and can be distributed urgently as needed.

Analytics have also been implemented to provide more thorough evaluations of the effectiveness of existing programs. One example of this is GiveWell, the nonprofit firm who seek out giving opportunities through in-depth analysis. GiveWell determines the level of social improvement and benefit that is achieved by every dollar spent on programs and publishes their findings online in order to assist donors in choosing the most appropriate and effective schemes to give to.

Socially Responsible Data Science

Closer to home, we have worked on a range of socially responsible projects, most recently with Hackney Council. In our work with the council, we aimed to employ data science tools to identify, intervene and help those at risk of falling into rent arrears. By preempting those most vulnerable to rent arrears from an early stage, the council would be able to monitor, advise and support tenants to prevent them from entering into difficult situations. The project was highly successful and the model could readily be applied to not just other housing services, but to financial institutions too.

Promoting philanthropy by nonprofit organisations to wider economic and social circles is a flourishing field. The relatively new “digital civil society,” as it has been referred to by the Stanford Center on Philanthropy and Civil Society, is set to revolutionise for-profit and nonprofit schemes across the globe. For example, the Bill & Melinda Gates Foundation has invested in for-profit pharmaceuticals, in the development of drugs that are then distributed through nonprofit organisations. This work will support and encourage the development of medications whilst maximising medicine availability to the poor. Likewise, data science investment by leading companies can rapidly impact nonprofit organisations, helping to minimise losses and increase available funds.

The profit and nonprofit benefits that can be seen from data science adoption were clear in our recent Hackney Council project. Rent arrears cause incredible difficulties across a  diverse spectrum - from emotionally stressed tenants to financially weakened landlords. An unstable economy and unreliable housing system can soon snowball into a mammoth cross-industry problem.

On Pivigo’s Science to Data Science (S2DS) programme, aspiring data scientists are presented with real-world problems to solve and Hackney Council was an ideal task to undertake. Using data science to predict which tenants are most at risk of falling into long-term arrears allows local housing associations and councils the opportunity to intervene before the problem occurs. Ensuring that vulnerable tenants have access and support from financial planning teams, councils such as Hackney are able to minimise the likelihood of rent arrears and maximise the potential for more financially secure tenants.

The team at S2DS analysed the data helped by the council and employed a range of data science techniques, such as decision trees, model building and clustering, to assess the likelihood of tenants falling into rent arrears. Their work and results will allow the council to set specific parameters such as predicted inflation rates and likely growth in wages to determine the impact on tenants in set scenarios.


Data science is more often recognised as the revolutionary force behind margin-boosting corporation developments - a technological evolution that can redefine a business to almost unrecognisable successes. However, data science can also be responsible for significant successes and securities within the nonprofit sector. Promoting civil good and securing social development and security is considerably more achievable through the adoption of data science techniques in not-for-profit organisations.

From social housing to pharmaceuticals, marrying tech advancements to benefit the poor and vulnerable is more rewarding than ever. The analysis of data ensures that algorithms are designed to maximise the efficiency of organisations, promote the availability of sources and ensure that those in need receive the most without compromising the wellbeing of the firm.

Solutions, like the one we created for Hackney council, have many applications, not just to other councils and housing agencies, but to credit agencies, financial services institutions and more. To find out how we can turn your data into socially responsible solutions, get in touch:

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