The pressures facing the social housing sector in meeting an ever-pressing decarbonisation agenda are huge.
It’s well known that homes are a major contributor to the climate crisis. Powering and heating buildings account for 40 per cent of the UK’s total energy use, with England’s homes alone emitting more carbon emissions every year than all the country’s cars, according to the National Housing Federation.
Plans to decarbonise the nation’s housing stock were laid out last January by the government in its Future Homes Standard consultation. It confirmed plans to ban gas boilers in new homes from 2025, while proposing tighter energy efficiency standards on existing properties, in a move it hopes will bring us closer to meeting our legally-binding ‘net zero’ 2050 target.
With 2.7 million of the country’s homes owned by housing providers and a further 1.6 million by local authorities, the challenges in delivering these targets will be felt acutely by social landlords, particularly when you consider many are still grappling with the complexities and costs associated with bringing their stock up to building safety standards against a backdrop of depleted resources and severely restricted budgets.
Harnessing the power of data
This is why now is the time for the sector to harness the power of their existing data to help tackle these challenges head-on without compromising their core values.
For over a decade, housing providers have been collecting data on their housing stock and tenants for reasons spanning tenant onboarding to compliance, asset management, maintenance, regulation and warranties, but until now many have yet to use and analyse this data effectively to work out how efficient their stock is and where they could save money.
Part of the problem is how that data is stored. It’s common for housing providers to use multiple systems as part of their housing management. For example, they might have one system for rental income and arrears, one for collecting information on maintenance and repairs, and another that covers compliance. For many ‘a system’ could be as basic as a spreadsheet, with data manually maintained by staff.
The challenge with this, aside from such high levels of manual administration being open to human error, is the data analysis that takes place in the sector today tends to be very static. Too often, housing providers will report on figures after they’ve happened, rather than actually being able to use the data for proactive, empirical analysis to support business decisions.
But by integrating this wide variety of information within a single housing management system, housing providers could make better investment decisions around decarbonising their stock while balancing the needs of their tenants.
For example, take the replacement of gas boilers with heat pumps. This has been put forward as one solution to reducing carbon emissions within existing properties, but that could do more harm than good in the short term without targeted data analytics.
A housing provider might want to install a heat pump in one of its 50-year-old properties to reduce the building’s emissions as a quick win to help decarbonise its stock. But only when you start to pull together information on the property does a different story emerge.
Its stock condition data, for example, might show the home hasn’t been properly insulated (a likely scenario in a property of this age) and its separate tenant records could show several months of rent arrears (an increasing possibility as a result of the economic impact of the pandemic). The poor insulation would mean the home would be likely to lose heat, something that can make heat pumps far less effective, in turn increasing the tenant’s utility bills. With their financial situation already stretched, this could force them into fuel poverty.
Simplicity in integration
It’s important to note that this isn’t about making processes for complicated; it’s about using the information that housing providers already have in a more joined-up manner.
That said, there are wider data sets beyond those collected by housing providers that could be applied to a single system, the applications for which are really exciting, particularly regarding decarbonisation.
For example, Capita runs the UK’s smart metering network. This gives us unique insights into energy performance data in over 20 million homes, which we can share with our customers for analysis.
For instance, we could use a tenant’s accurate energy consumption data, collected via their smart meter, to unveil important ‘unknowns’. This might show that a tenant is living in a house categorised as energy efficient, while also having high energy bills.
This flag would prompt a more thorough analysis. The housing provider could then look at some of the causes and analyse whether the property is being heated properly or whether this is causing dampness or poor living conditions, or even if it’s affecting the property’s infrastructure. Further areas could be tracked, such as what type of insulation or boiler was being used, right down to the light bulbs that were installed.
By looking at the building from an energy supply and demand perspective, we can assess the property’s condition and in turn the living conditions for the tenant. Any concerns can be automatically flagged, and this can again reduce the risks of things such as fuel poverty.
This same data analysis can also be used to help housing providers secure government funding to support its net-zero carbon agenda. Capita is working with a number of local authorities and housing providers in this area; in one recent example, we helped an organisation secure £6m to kick start its decarbonisation programme, supported through accurate and integrated data.
A reasonable concern for anyone considering using tenant data is compliance with GDPR. However, this isn’t a problem if the housing provider can make a compelling case about why it needs the information, such as ensuring improved tenant conditions.
Elsewhere, a wider benefit of using a single system is that it can automate data tracking where appropriate, minimising the need to disturb tenants. This can be done by assessing, say, 10 per cent of houses on an estate and then extrapolating those results to the whole estate.
By combining this process with aggregated housing-improvement data registered with the local authority (something required by law for any improvement such as window glazing or change of heating), data can be collected without the need for excessive surveying, consequently saving housing providers time and money.
Ultimately, the key here is to provide tenants with warmer, greener and cheaper homes, while delivering more tailored services. By using effective, efficient datasets, both can be done hand-in-hand with benefits for housing providers, the government and tenants alike.
Glenn Allan is the head of product (housing) at Capita One.