Housing Associations in the UK are continuously striving to deliver a good quality of life to their tenants by providing them with safe and good quality homes, whilst overcoming challenges such as repairs and rent arrears.
To manage and improve social housing services, it is hugely beneficial for housing authorities to understand their business in terms of data. This blog will explore ways that data science applications built on the Azure cloud platform, can help address the current challenges that housing associations are experiencing, in transparent and cost-effective ways.
Recovering arrears and retaining Tenants more effectively
In the current climate, housing authorities are striving to protect tenants that are struggling with rent arrears to avoid eviction and homelessness, but the recovery of rent arrears remains an important business concern for many housing authorities
To aid recovery of arrears, the ideal software triages arrears cases and provides a dashboard of relevant information for each case to housing officers. This can be highly effective in recovering arrears by contacting the tenant and using timely follow-ups if the debt isn’t paid. Power BI can be used to create informative dashboards, integrating tenant information from various source systems, as well as using the results of machine learning models and statistical analyses. It can indicate the severity of arrears cases and the likely best course of action.
Similarly, data science and analytics methods can be used to understand the socioeconomic factors involved in tenant retention, allowing the organisation to prioritise tenants at risk of eviction and intervene optimally. Integration of these data science methods with existing CRM systems is also possible using Microsoft technologies such as Power Apps, in a bespoke manner which best fits the needs of the business.
Understanding repair and damage risk factors
Repairs are a major concern for housing authorities and tenants alike. For example, it is well known that fuel poverty in social housing can lead to condensation and black mould which, if unaddressed, can lead to more costly repairs for the social housing provider, as well as health problems for the tenant [1]. However, using a housing authority’s data, we can intervene earlier (and in a more targeted and effective manner) by finding geographic and demographic correlates of condensation risk. This would save money on repairs and improve the quality of life of tenants – a win-win situation.
Similar approaches can also be used to identify risks factors for anti-social behaviour and fires, allowing your organisation to take steps to mitigate these hazards. Sensor technologies that enable predictive maintenance, and the Internet of Things, have already had a cost-saving impact in the manufacturing sector and have huge potential to save housing authorities money too. These technologies generate large amounts of data which Microsoft Azure is designed to manage in a cost-effective and scalable manner.
Benefits of Keeping Data In-House with Microsoft Azure
Using housing authority data for these data science applications in-house with an organisational Azure tenant has various benefits. One of these is the ability to ease the integration of any data science solution with source systems and downstream CRM systems. Proprietary software aimed at providers of social housing are typically expensive compared to in-house solutions created in Azure and cannot be as easily tailor made to the needs of the organisation This is particularly true if they are used to assist in the recovery of arrears or management of repairs.
Any machine learning models included in proprietary software will be black-box in nature, whereas models generated by the organisation in Azure are transparent, owned by the organisation and more readily tuned and extended to their requirements. Microsoft Azure offers a cost-effective way to develop and scale data science solutions, whilst building expertise in the organisation surrounding data analytics and cloud technologies.
Conclusions
Data science methods offer a number of opportunities to social housing providers in terms of optimising their business and improving quality of service for tenants. Simpson Associates offer data science consulting and managed data services to help your housing authority build and deploy these solutions in Azure and become a more efficient, data driven organisation.
Blog Author
Robert Constable, Senior Consultant, Simpson Associates
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