 It's great to all be here, thank you for coming to this session. I'm going to talk about something that affects all of us which is housing and specifically reframing housing using open data now, barely a day goes by in the UK without some discussion in the national media about how to use the housing crisis. Most people recognize that there is a crisis but there's less clarity about what to do about it Before the general election, the National Housing Federation created the Homes for Britain campaign designed to bring awareness to this issue. It championed the idea of ending the housing crisis within a generation by building more homes. So what is actually happening on the ground? Why is this housing crisis even here? We must, I think, ask the question, what is our approach to housing fit for purpose in this century and what with digital technology can be done for it? It might be surprising to hear that the data tells us our urban landscapes only account for little more than 10% of the available land mass in England and less than half that in the rest of the UK. So technically, space isn't the issue. Added to the question of space, there is one of affordability. On Friday, what is called affordable housing was re-listed as part of the public sector by the Office of National Statistics. It consists of approximately £400 billion worth of assets against £60 billion worth of debt and that's actually pretty healthy as a debt to asset ratio. Most people would be able to get a mortgage against that kind of ratio. Yet the need for innovative thinking to tackle the housing crisis is apparently strong with headlines calling for radical new ideas cropping up regularly and it's urgent. The deaths of two recently homeless babies show that for vulnerable families this housing crisis is a matter of life and death. Now, there's no doubt that housing management is complicated. It's so complicated it's missing as one of the indices in the open data barometer. That's why I think it makes sense to examine the business model behind how housing is managed to ask if it's a broken model and that data can fix it. If so, what can we do about it? I think we can look particularly at the gains that digital business can create as a way of managing all the variables, bringing together information. At the moment, quite a lot of the available data is housed in closed spaces or across different departments and organisations. It doesn't necessarily join up together to create a better housing system and an open data infrastructure can change that, but there is confusion. There are a whole range of issues and challenges that housing organisations are grappling with. These are some of them as expressed by housing organisations that between them represent about 2.4 million homes that comes from our last years connected housing report. Meanwhile, average monthly rents are skyrocketing because of disjointed availability and how we manage stock. For tenants seeking affordable housing, the options are getting narrower, with many being reported as going from exclusion to real poverty. Basically, the lifestyles that many hope for with a safe roof over their head that they can afford is becoming no longer an option. I think open data in housing can do two things. Firstly, it can close the dissonance gap between performance data and real life perceptions. Secondly, it can help improve the bigger picture by lowering costs and improving outcomes. This is a map of the national housing ecosystem that I made. It shows 9,811 different relationships that exist between local authorities and housing associations across the UK. Just one housing association can have more than 159 local authority relationships. It manages across its housing stock, as for example Riverside Housing does. So how can we manage such complexity? Well, if we look at the examples of some early infrastructure, we can perhaps see other ways that we can do this. This map, which some of you may have seen before, is the organisational structure of the US Railroad when it was first built in the mid 1800s, that suggests that we can design a vastly improved national housing infrastructure using data. The good news today is that land registry data, SRD data, core data, lettings data and more is becoming open. So, let's take, for example, match the city's catchment as an idea of what could happen. We can see through the data what's going on regarding, for example, stock to population ratios, average house prices, the percentage of homes that are affordable, how much stock on average per housing association is under management in the area, and the rent paid as a percentage of the medium weekly wage in the area. Now, that's quite a lot of information with which we can draw on some ideas about how to manage housing for better results and how in detail. Basically, we can reframe housing substantially by joining up and connecting this kind of data and creating a framework for it. National data exists on house prices, jobs and the amount of money people have either as income or benefits. Added to that, we can now look at how housing organisations are delivering on their core functions that are essentially building homes, managing homes, collecting rent and providing services. The Connected Housing Study that I do in fact looks at this and how it is being handled digitally and assesses which organisations are best placed in terms of digital performance. Through the studies over the years, we know that this kind of information accelerates performance. This chart, which showed the breakdown of online functions available in 2012 for the top 100 housing organisations, had a marked effect in accelerating how online customer services were handled by organisations. This chart from the 2013 study also highlighted the level to which housing organisations were using digital service management to streamline costs in key areas such as providing information on benefit changes or information about local skills training. We can look at the relationship between overheads, outcomes and online engagement. The Connected Housing Study is doing this too. So, to reframe housing using open data, we want to connect the dots and have a conversation about three things. Firstly, we want to talk about stock. We want to help pull together the open inventory about housing stock, about the volume, cost of stock, land registry data and more, for example, and this is already happening. Secondly, we want to connect that to needs. We want to link data and understand it better so that we can meet people's needs, including their levels of deprivation and digital inclusion so that we don't have to be dealing with these threshold challenges all the time. Thirdly, we want to better understand costs and use digital business modelling to develop increasingly effective ways of doing things. We want to harness open data so that we can make processes work more efficiently, both in terms of service delivery and costs. These three things, connected together through data, give us a powerful way to help create much better outcomes in terms of how we manage housing. It can happen in the way housing organisations use the data they generate and they can be pivotal in creating it. Through this, we can create a powerful national intelligence about how to solve the housing crisis. We can see interdependencies, for example, between housing stock managed by providers and neighbourhood management and create more viable communities. We can see the interrelationship between management efficiency per unit and how many residents are active online. Between the average price per square foot and how many people are locally employed. Between priorities in terms of stock management and repairs costs as actually reported. Between building costs and affordability. And we can do this area by area. There are already great initiatives happening in housing using open data. This one by the Trafford Innovation and Intelligence Lab is looking at the changing face of deprivation in the local area and helping to move towards more predictive analysis. This one by Sovereign Housing seeks to understand affordability gaps in the local area so housing can indeed help people to feel able, either as tenants or owners, to afford their own home. This by the Leeds Data Mill is looking at empty home trends in Leeds. And this by Midland Heart provides a great sight line on housing data looking at stock levels by provider, types of stock and rent levels. Indeed these data examples are not going away. They're just the start. We're moving towards the age of quantified organisation and quantified infrastructure in which joined up data is our biggest intelligence asset. That's why it's important that our national infrastructure owns the data and that housing organisations do not lose their ability to make data an asset by outsourcing digital capabilities in a way that fragments data, that reduces the chance of them either having ownership of their own data or being able to contribute to a joined up picture using data. With Connected Housing 2015 we're making a call for more open data in housing. This initiative is on between now and the middle of December for organisations in housing to participate in. And I'm pleased to say that several housing organisations are already joining this initiative with more every day so that we can begin to build a dynamic intelligence about how to solve the housing crisis. So, to go back to the question, can data logic solve the housing crisis? I would say yes. I would say that reframing housing using open data is the best way possible that we can create both social and capital value. I hope that more organisations will join this initiative because if not us, who? And if not now, when? That's what I have on reframing housing. Thank you. Do we have any questions? I'm sure there must be some. Got a question down here at the front? Hi. Social. Sorry. You talked about housing associations, social housing. What about other providers of housing in the private sector in open data? Have you looked into that? What are your thoughts on that side of the stuff? I've focused on housing associations for the study for two reasons. One, because they've got an aggregate amount of stock that they manage, which is easier to look at than the fragmented private sector. And also because part of their remit and having a social purpose is to join up services. And I think one of the key things that's really critical within housing, but is sometimes overlooked, is how the roof over our heads is a junction point for so many services that we can really get an understanding about by having a joined up approach to data. If we're in the business of people owning their own homes, they've got that security. But we have, with devolution, which is being talked about now, I think we have a real risk that we lose this opportunity to have a joined up picture about our national intelligence about housing. And given it's the thing that crops up over and over again, I think that's kind of worth going for. More questions. I think... Sorry, a question here at the third row back. Hello. Really interesting. You've been doing some great work on this subject. If you could just actually, I should have said this before, but if you could say your name as well and why you're working. Paul McMullan, I work for Shelter. So we're coming up to our 50th anniversary trying to alleviate homelessness and housing issues. I just wonder where you think from the work that you will be doing, what you could do if we, because I'm trying to help us open up our data, and what would your thoughts be on how you could work with kind of the data we have on people's problems and the advice we've given over the years and the intelligence that we have? Well, the one thing actually, I'm really glad you're here, and I'm really glad you've asked the question, because in the study it does include some charities which offer units, so Centre Point, for example, some mongos and so forth. And time and time again what we see in the study for the last four years is that the charitable sector has a far, far greater traction with people on the street or the general public. They are far more connected to the not-for-profit sector than they are to the housing sector. So I think the very nature of the relationship you have with supporters, for example, could teach the housing sector a lot. Their engagement rates are less than 5% of the average charitable rate, but also in terms of your data, which is really at the heart of the question, to be able to connect the needs with the stock, with the costs is I think really at the heart of it, and you've got a really good sight line on needs. It's only now within housing that there is an appetite to even hear what people's real-life stories are. You know, you are very good at bringing those to people's minds and sharing them in a way that people can understand. So I'd love to be able to get the qualitative insights that comes from the kind of work you're doing, plus the data to connect with things like stock and efficiency and business management, a much, much better system out of it.