The housing sector is heavily regulated, with housing providers required to support and improve the lives of tenants while meeting a number of regulatory requirements. It’s therefore vital to keep on top of areas such as finance, maintenance and repairs, tenancies and voids, contractors and partner agencies and much more.
Many housing providers cite difficulties in not only reporting this information but also analysing it and addressing any problems. What’s more, because of the inflexible nature of many systems, reports become out of date very quickly. This can have serious consequences: for some, it results in a lack of visibility around arrears and the inability to collect debt effectively; for others, it’s a lack of understanding around why certain properties remain empty for so long, equating to lost revenues.
Data chaos, whereby your data is siloed and therefore unmanageable, is a common concern for housing providers. Part of this problems stems from the fact that there is no single big provider of housing-specific technology which covers all of a housing provider’s needs, hence the application spaghetti of most housing providers.
The difficulty is that these disparate and/or bespoke systems don’t fit all of their requirements, or they might have done when first implemented, but then things change, technology progresses and then they’re outdated.
Housing providers require specialist systems for many different purposes, such as property management, overseeing external contractors and internal staff systems for HR and payroll. That’s a lot of data to manage, understand and analyse.
There might be a recurring problem that your organisation is experiencing regularly. For example, you might have a lot of empty properties; is it because there’s a performance issue in your team or is it because no one wants two-bedroom properties in a certain area? These are the questions you need to answer.
Using analytics tools will help you identify and resolve these issues. You probably have a lot of different systems with all of this information in separately, and it’s hard to get an overview. Analytics can help housing providers with a number of common issues including void properties, repairs and rent arrears.
Quite often, housing providers will implement analytics as a solution to a specific problem; perhaps they’re haemorrhaging money, a vital repair was ignored or a crucial problem with a property was missed. At the same time, some housing providers do proactively adopt analytics to gain a competitive edge and get the answers they need faster.
We therefore recommend implementing data analytics as a way to futureproof your business, improve your tenant experience and make better evidence-based decisions.
Addressing and preventing arrears
Not reconciling rent and utilities arrears equates to money down the drain. In 2020, arrears hit a five-year high in the social housing sector, while rent collection was at its lowest level since 2013. It’s very difficult recovering owed money once someone moves out, and you certainly want to avoid writing off debt because it’s easier than chasing.
With leading analytics platforms, you can do things such as profiling tenants, allowing you to see who is likely to fall into arrears. Of course, this has to be done accurately and in a non-biased manner. You feed the system all your data and it will identify the key factors, whether that’s geographic or demographic, that make someone a high-risk case.
Filling your voids
Like uncollected rent arrears, you’re losing money when you have empty properties. With coronavirus restrictions, overall social housing voids increased in 2020. You need to understand why a property is void and what you can do about it. By using analytics, you can identify common themes across empty properties, including their location, the level of furnishing and the number of bedrooms.
Combining this with your repairs service means that you can also ensure the property is fit for purpose before renting again. In fact, a lack of repairs might be the reason it’s sitting empty. Analytics can help tie these systems together so you can gain an understanding of what repairs and maintenance needs to be done and when.
Repairs are a necessary but costly part of property management. The most recent data from the Regulator of Social Housing shows that maintenance costs £4,120 per property, rising by 7 per cent from previous analysis in 2017.
Repairs require a lot of attention and generally fit into three categories: responsive, planned and cyclical work. Using data analytics, you can predict and plan when these works will take place and view important information including completed repairs, overdue repairs, repairs in progress, scheduled repairs, first-time fix rates and a visualisation of repair locations. And if you work with many subcontractors for repairs, you can give them the relevant information on their jobs by providing secured access to your dashboard.
Many housing providers struggle with exactly the same issues when it comes to repairs, arrears, voids and more. The fact that there are no software solutions that take care of all aspects of housing management adds to the problem because housing providers therefore have to rely on multiple systems.
Implementing a data analytics solution will not only allow you to bring all your data together into a single source, but also drill down into it to identify and resolve a number of issues. Your business holds and produces mountains of valuable data; it’s time to make it work for you and let you to make smarter decisions.
Lisa Donoghue is the data and analytics account director at Perfect Image.