"Housing Associations have got a huge amount of data," says Matt Leach, CEO of the Housing Action Charitable Trust (HACT), a think-tank for the social housing sector that has become increasingly active in providing services. What is more, adds Leach, they are becoming more and more interested in putting that data to good use.
Speaking at the Cloud World Forum this month, he continued: "They have data on the people that live in their homes; they have data on their homes; they have data on rent payment records; data around anti-social behaviour in their local areas. They have got a bunch of open data, a lot of which is provided by HACT on a service basis. And there's an emerging interest in data analytics right across the sector."
However, while housing associations may account for approximately one-in-eight households in England, and have a collective income of about £12bn every year, individually they are not necessarily so weighty. "The social housing sector has around 200 providers of scale and they may have anywhere between 5,000 and 80,000 homes between them," said Leach.
Putting that into perspective, the average housing association has the turnover of a medium-sized branch of Asda and don't necessarily have the resources to strike out on big data projects on their own. "So the challenge for HACT was how can we move to an environment where we could give housing associations the same sorts of capabilities as the best organisations had in the private sector?" said Leach.
Basic aggregated cost and performance analytics capabilities have been tried within the housing association sector for a number of years, in which one provider can crudely compare or benchmark its performance against another.
"But they haven't been able to get much further. In part, because of the complexity of the data, not because the data is inherently complex – rent records, housing records – but because every housing provider, although they collect the same data, call it different things, store it in different ways, give it different labels, and there's been an unwillingness to try and unpick that," said Leach. Not least, he adds, due to fears over data protection.
However, the advent of cloud computing, said Leach, has enabled HACT to provide housing associations with the common platform to develop their big data strategies.
Working on the Microsoft Azure platform, HACT has put together secure "data vaults" for housing associations on which they can host shared data. And, over the past year, HACT has attracted 20 social housing landlords comprising some 450,000 households between them to its big data platform.
Together, says Leach, they have created a single repository for nearly all of the transactional data they have in relation to their homes, but held in an encrypted, G-Cloud certified environment with associated analytic tools, such as HDInsight, Microsoft's Hadoop-based service.
"So, housing associations are putting nearly all of their data into the cloud, associating it with a bunch of other data sources, both commercial and open. Then starting to see whether we can drive insights around predicative factors such as arrears, whether people will pay their rent, for maintenance, for voids - are there common factors that might lead people to abandon their homes prematurely?" said Leach.
The cost so far - partly by only buying capacity when it is needed - has been around £40,000-£50,000, he adds. "We are hoping to get some real insight into the ways in which data about housing can drive repairs. Housing associations spend some £10bn a year keeping their stock in good order.
"We are also hoping to be able to start to manage and predict arrears and voids," said Leach. This will help them better manage their cash flow and, hence, improve their ability to borrow and build new stock. That is one of the key focuses of HACT this summer, as well as fraud - finding the key factors that might indicate that a home is being sub-let illegally.
Then, it will start to feed in tenant satisfaction and other survey data.
In total, HACT has spent around a year building the infrastructure in Azure, including smoothing over the data protection concerns and migrating the data from the first housing associations into the cloud. "We have now started working with a bunch of data scientists from Royal Holloway University to start generating results," said Leach.
In future, Leach foresees Housing Associations taking data from their homes, particularly elements such as boilers that are prone to failure, in order to schedule preventative maintenance and, ultimately, to analyse how people live in, and use, their homes. "We have been working with UCL post-graduate students enabling us to capture 45 million data points per home, per year, across half-a-million homes.
"The idea is that you can capture data on heat, light and motion in rooms; capture data on boiler performance and, perhaps, capture data on how often a particular room in the house is used.
"If we can understand how people use their homes, we can start to think about the way in which we design them. It will enable people to target investment more effectively," says Leach. Data on room use, for example, could be fed into refurbishment projects, stretching the refresh cycle in homes where kitchens and bathrooms have been less well-used.
So-called "intelligent" or "smart homes" are most commonly associated with initiatives such as Nest, now owned by Google, and the kind of high-tech executive houses frequently showcased by technology companies, where money would appear to be no object. Yet maybe they will have more use in the rented sector - especially in social housing.
Sometimes, the power of the mainframe is the most cost effective answer. Computing's Peter Gothard puts Computing's readers' questions on the future of the mainframe to IBM's Z13 expert Steven Dickens.
This Dummies white paper will help you better understand business process management (BPM)