Key Data Challenges for Social Housing
We have recently explored some of the key use case challenges impacting the Real Estate industry and the importance of data in helping to manage these challenges.
Whilst these use cases are equally relevant for the Social Housing sector, there are a number of other macro as well as micro factors that are uniquely important for the sector.
In the first two Blogs of our three part series, we will discuss and explore some of these challenges in more detail. In our final Blog we will then look at some of the cutting edge tools and techniques that can help Housing Associations and other parties to respond to these challenges
One of the first challenges for Social Housing concerns the dynamic and continuously changing shape of the resident population as individual households adjust over their lifetimes.
For example, an individual may become resident in a Housing Association property as a young person. That same individual may then find a partner to live with and then have children before the children leave as they become young adults.
The household may change again as the individual splits from their partner before taking in an elderly relative to look after in old age for a period of time.
As this example shows, the property needs of this fictional individual changes significantly over the course of their lifetime.
Housing Associations, like all property firms make investments for the long-term, but not necessarily with residents’ changing circumstances in mind.
The key challenge for the Housing association is therefore how to capture these changes in a timely and sensitive manner to ensure the individual has a property to meet their requirements, whilst simultaneously optimising a finite property portfolio resource for the benefit of other residents.
In other words, how to make sure that all residents are ‘right-sized’ in a property that is neither too big or too small and also have all of the necessary provisions for a particular resident.
One of the ways that leading organisations are tackling this issue is through the extended use of client self-service portals (either in the form of webpages or specific apps) to allow changes in circumstance and other information to be input.
Once the data is captured, organisations then need to regularly optimise resident demands against portfolio supply on a basis that helps as many residents as possible have a home consistent with their needs, without causing unnecessary and continual disruption.
This optimisation needs to consider a number of additional data points such as population, social trends and their property portfolio. That way Housing Associations can accurately predict what types of property they need to provision and so optimise their portfolio for the benefit of their residents.
Capturing, storing and then using the data to automate this optimisation process not only provides operational efficiency savings, but also helps to make more informed investment decisions.
In addition, organisations need to consider the data demands required in order to adequately extrapolate and predict changing resident profiles and demands.
This is likely to be non-trivial and should be included within the scope of the organisations data strategy and execution plans. Once finalised, partial or full automation of the optimisation process may reduce resourcing costs and also allow the process to be run more frequently.
Another challenge for Housing Associations is how to best manage building maintenance and improvement. Traditionally, regular checks on the state on the housing stock has been used in order to ascertain when roofs, boilers and other items would need to be replaced so that this work can be planned, cost provisioned, and appropriate staff /contractors lined up to complete the work.
With the advent of improved technologies, new buildings can be equipped with ‘SMART’ capabilities that allows additional information to be captured, allowing a more proactive approach to maintenance. By leveraging the ‘Internet of Things’ (IoT) in this way, repairs can be made before additional damage is caused, therefore reducing long term maintenance costs.
‘SMART’ technology may also be used to help to provide more tailored care for vulnerable residents. For example, ‘SMART’ kettles or televisions allow non-intrusive visibility to the carer that the resident is up and about and has not fallen over and hurt themselves.
This removes the need to take more intrusive activity such as daily checking or worse still, forceful entry had they failed to answer their phone to a worried carer.
Data captured in this way allows the Housing Association to create a profile of habits (for example the kettle is usually turned on four times a day) that allows an early warning that something may be amiss.
Enhancing this with additional data points (related to weather or other seasonal factors like holidays and festive celebrations), can also help to enrich predictability and provide Associations with greater insight into their residents in order to provide better care.
In the next blog, we will explore more of these Social Housing challenges including resident feedback and the impact of Covid-19. By analysing the latest industry scenarios, we will look at how organisations can best respond to these challenges using innovative data management techniques from DTSQUARED.
Read our White Paper ‘ A Practical Guide to Data Management‘ here.