Lately, housing providers in the UK are under immense pressure to perform stock condition surveys of their entire portfolio due to increased pressure from regulators. This week, it became clear that housing associations face ‘very real risk’ of exclusion from grant programmes if they fail on disrepair. However, a complete audit of their housing stock might take much longer than expected due to time consuming traditional methods most housing providers still employ.
That’s why housing providers are now exploring an updated version of stock condition surveys, by using established digital technology. Spotr, the European market leader in digital stock condition surveys is officially expanding into the UK to help housing providers reduce site visits, get all reliable data of their housing stock in one place and encourage data driven decision making.
Since 2021, Spotr has been cooperating with the Disruptive Innovators Network, a community for social housing organisations investing in innovation in the UK, to test if Spotr's technology could undertake building stock measurements and surveys digitally, instead of using costly traditional methods. Nine housing providers, among whom Loreburn Housing Group, Halton Housing and Clarion, joined the project to test this innovative alternative to traditional stock condition surveys.
Jenny Danson, Proptech Innovation Network Director says: “We’ve been really excited to work with Spotr to test virtual stock condition surveys through our DINLab process. Like all good innovation, the solution has learnt and grown following the input and feedback from the DINLab participants.
This solution has the capability to disrupt the way we do condition surveys as a sector and move from a silo approach where the information is stored in locked PDF files into a solution that benefits the whole organisation and allowing for a risk based approach to condition surveys rather than the sheep dip approach now. “
What do housing providers have to say?
"What got us interested in virtual stock condition surveys is how to understand the condition of our stock quicker and easier", Gary Alison from Loreburn Housing Group says. "Since we operate in a large rural area, it's much more cost-effective to have all images of all our properties available to our colleagues and maintenance partners in one place. This saves them repeat visits. For the rental team it's great as well; they can now show properties to future tenants without having to drive there."
"The pilot with Spotr was beyond anyone was expecting", Lee Reevell from Halton Housing adds. “It's so intuitive to work with a visual map and much easier to proactively send out the right people to the right properties."
The company, based in The Hague, initially created the tool in cooperation with Dutch housing associations. Dirk Huibers, co-founder and CEO of Spotr, explains: “We’ve been building up experience over the last few years how to best help housing associations maintain their housing stock. Creating a visual twin of the entire portfolio is a necessary first step and we’re delighted to be setting this up for our first customers in the UK.”
Spotr is an AI-powered property insights platform, helping housing providers to digitally inspect buildings at scale to reduce on-site visits and improve data-driven decision making.
It's never been more complex to be a housing provider due to more compliance, higher costs and an ageing labor force. Housing providers need to get more done with less resources, but the lack of reliable data is holding them back. Currently, the only way to get reliable data is by driving out on site and manually gather data. However, this is unscalable, expensive and often data is incomplete due to inaccessible parts of the building like the roof, back façade or interior.
Spotr creates a complete visual twin of every property in a portfolio, including roof, façade, context ánd interior images. Powered by computer vision, Spotr provides additional data like condition, measurements and specific risks associated with the properties. With Spotr Analytics, housing providers can prioritize properties based on specific risks or opportunities.