The housing sector is on the cusp of something big. For years, housing providers have been collecting data. Data on the structure of properties, the nature and frequency of repairs and data on rental payments, and although this data has been very useful, until now it has done little more than tell a housing provider what is happening on a day-to-day basis.
While this allows housing providers to react to complaints and deal efficiently with problems as they arise and review processes, it hasn’t enabled them to get ahead of the curve and predict what might happen tomorrow or next year.
But this is set to change. The latest developments mean data can be cross-referenced and analysed to spot trends and patterns to improve service to tenants and predict issues before they arise.
The potential is momentous, enabling housing providers to make earlier interventions which have the power to transform the social value they deliver. Here’s how housing providers can ensure they make the best use of these tools.
1. Overload on information
There is no such thing as too much information when it comes to business intelligence. The more quality information you have, the better you can predict what could happen in the future, allowing you to create strategies to address any potential issues.
What if you could predict that in four weeks’ time a tenant risks falling into arrears for a period of several months? Armed with that information, you could arrange an intervention to avoid court action, eviction and potential homelessness.
Business intelligence tools can predict with over 85 per cent accuracy a person’s likelihood of paying rent on time by bringing together data about historic payment patterns, demographics and where people live. You can then use those insights to provide targeted support such as putting a payment plan in place for those people identified as most at risk to get them back on track.
In the same way that data can be used to improve income management by predicting those more at risk of debt, it can now be harnessed to help housing providers discover and understand the root causes of damp and mould. This will enable them to adopt a more strategic response to this priority issue.
Combining tenant and property data into one platform will help housing providers to rank households more at risk of damp and mould. For example, is it the asset that is structurally failing or is the property over-occupied and not being ventilated sufficiently.
This 360-degree view will give both tenants and housing providers the insight and understanding they both need to tackle the issue together so pre-emptive action can be taken. One housing provider we work with was able to analyse their entire stock and predict properties with damp and mould at an accuracy of 75 per cent. Not quite at the click of a button, but almost.
2. Use tenant visits to expand your knowledge base
Most organisations will have other opportunities to expand their available data sets. I estimate that most housing providers visit 90 per cent of their stock each year for one reason or another – for a gas safety certificate, maybe a repair or a tenancy visit.
If you have every person that enters one of your properties to do an ‘eyes on’ survey, you could rapidly improve the information you have available on the repair state of each home or identify the potentially more vulnerable tenants who might need more support later. A quick checklist to run through each time to answer questions such as, “Is there damp and mould in the property, and if so, how far has it spread and does the elderly tenant live alone?” can rapidly expand housing providers’ knowledge to improve their support to tenants and manage their housing stock more efficiently.
And because business intelligence tools can now analyse unstructured data in notepads and reports, the system can be pre-programmed to detect key words such as ‘annoyed’, ‘fed-up’ or ‘health condition’ that a housing officer has entered. This can generate a report alerting which properties may need to be more urgently investigated.
3. Make use of IoT
We are moving from a world which relies on word of mouth or documents to gather data to obtaining that information direct. The ability to access real-time data from inside your properties such as temperature, humidity and carbon monoxide levels has been made possible with IoT sensors. These small pieces of hardware fitted inside homes to detect changes in the environment provide a gold mine of information.
Algorithms can be finely tuned to interpret the data correctly such as what is an acceptable level of humidity for a certain type of property. This information builds on the knowledge you already have about a property to see if these levels are appropriate or if they could signify damp and a potential mould risk.
Analytics can even take into account certain variations in the seasons or if humidity increases at mealtimes so that those peaks can be discounted. Reports are then produced on the system alerting which homes need urgent reviewing for damp concerns.
The current thinking is that one in five houses will have a damp and mould problem. When you consider some housing providers have over 50,000 units of stock, that’s a lot of properties to know what to maintain and when. The data from IoT sensors could make that a far easier process.
4. See data collection as an ongoing process
Data left in a system can become redundant very quickly. Given the nature of social housing, key factors can change very fast, such as whether a leaking roof has been fixed or if the tenancy has changed from a single person to a young family. Maintaining your dataset is fundamental to solving the current crisis regarding housing standards.
Ultimately, keeping on top of your data so that business intelligence and analytics are performing to the highest level will improve the services you can provide to your tenants.
And although it may seem a large task to gather all this data, work is underway to retrofit properties using the net-zero grant. This provides an opportunity to improve data sets by considering whether to fit an IoT sensor at the same time or to conduct an ‘eyes on’ survey to detect any other issues.
Providers can also buy in data from other sources such as utility companies. Energy consumption data when overlaid with internal data can make for a richer dataset and reveal a pattern of over- or underconsumption, signalling a potential cladding or boiler issue. Providers can then head off a problem before it develops. This will help build tenants’ trust and relationships will be further strengthened if they can see the value of working with their housing provider to help improve their homes. Gathering quality data and using business intelligence will only improve this further.
Trevor Hampton is the director of housing solutions at NEC Software Solutions UK.
