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Get to know the Finalists in the Housing Open Data Challenge

The Housing Open Data Challenge is in its final stages - we’ve defined the question, created a data guide and user research, invited applications from teams, provided expert support to the shortlisted 10 teams at the Creation Weekend and now, selected 3 finalists to receive £5k + a tailored package of incubation support. If you’d like to find out more about their journey through the Creation Weekend, check out our Storify.

As we enter into the final ‘incubation’ phase, we’re pleased to introduce the three teams and the ideas that they have put forward (below). Now they have the chance to win the final £40,000 prize - so do get in touch with them directly if you think you could support them to fulfil our judging criteria - use of open data, innovation, sustainability and social impact.

  1. RentSquare (previously The Fair Rent)

Team Fair Rent: Lais de Almeida, Helena Trippe + digital Iban Benzal

Q: What is your product?

The Fair Rent is a web-based matchmaking service, helping generation rent calculate fair prices for specific properties and search for landlords who realise a return isn't just about charging the highest fee.

The service uses open data to calculate a fair rent index, bringing visibility to the issue, and combats inflated rent levels, extortionate fees and poor quality housing. The platform proposes an alternative model to connect both demand and supply, encouraging the market to regulate itself.

Q: Who is on your team? Tell us more about yourselves!

We are a multi-disciplinary team of service designers from different backgrounds, bringing together public service, housing, technology and design. Helena is a housing practitioner, specialising in service delivery, policy implementation and research. She is currently undertaking a PhD on public service innovation and the is in charge of design for The Fair Rent. Iban, a creative technologist, is an expert in fast prototyping, responsive design, developing ways of connecting user-centred design with new technologies and the internet of things. Laís is a service and social innovation designer, with expertise in co-design, co-production with stakeholders and user communities, and prototyping ideas to design out risk.

We know housing is a big and complex issue, especially for those who can’t afford it. It is sector very resistant to change as there are so many competing interests. Yet it is in serious need of disruptive thinking, serial innovation and generally a good shake-up! Since meeting at the RCA, we have keenly pursued our interests in social and public innovation, and the role of new technologies to facilitate social change. The Housing Open Data Challenge is a perfect opportunity to make something happen.

Q: How did you come up with the idea? When and what was the lightbulb moment?

The idea is a really culmination of three separate research and design projects we were involved in, looking at mobility in the affordable housing sector, inequality in cities and technology based tools for active citizen engagement and decision making.

The light bulb moment happened when we realised that open data is a powerful source for social innovation. We approached the challenge as a design problem, and by unpacking the brief of how people could get the maximum from renting, we realised two things. First, by combining different data sets, we can calculate a fair rent index and then design a service to create better relationships between landlords and tenants.

We believe passionately that affordability in housing is not only achieved by turning on a government tap of direct provision, subsidy or investment. We wanted The Fair Rent to introduce a model of affordable housing with a small ‘a’, driven by user needs and the market. We wanted to recognise landlords should not be penalised for generating profit from their investment, but design an alternative which is an equally attractive model to connect both demand and supply.   

Q: How will your project help the community get the best out of renting?

The Fair Rent is for those 1.1 million people who government is failing to support. It is for the millions of young people and families who can’t rely on the bank of ‘mum and dad’ and face a lifetime having to move every couple of years, knowing they are being overcharged and unprotected.

The value proposition serves two customer groups - tenants and landlords - providing a service proposition designed to reliably and through transparency of information minimise costs for both.

We don’t want to be another property advertising site. The Fair Rent perhaps sets out to achieve the unthinkable... it is a demand driven tool that helps regulate the private rental market by making profit levels explicit and encouraging more socially responsible practice by landlords in the rents they charge and tenants by how they look after where they live. The Fair Rent’s vision: greater equality in cities.  

Q: What open data are you using and how does it form an essential part of your proposition?

The Fair Rent is only possible because of Open Data. It allows us to calculate how much a landlord is paid and is paying for a home, then compares it with social and market rents to give a fair rent price for tenants but also ensure a good return for landlords.

Price Paid Data

House Price Index

Private Rental Market Statistics

Keep up with The Fair Rent by tweeting them @theRentSquare!


  1. MoveMaker (previously Housing Tinder)

Creation Weekend attendees John Upton and Dipesh Amin with Team Housing Tinder: Alice Granville, Isabelle Champion, Ed Wallace + Jo Salter

Q: What is your product?

Housing Tinder is an app that makes it easier for social housing customers wanting to swap their rented property to find more suitable accommodation in areas they want to live. The app will give customers the option to search for suitable properties and get in touch with people about potential moves, all through a few taps on their mobile phone.

We want Housing Tinder to have these key features:

  • A simple sign up process

  • An easy to use search function

  • The ability for users to register their interest in as many properties as they want to

  • Notifications for any property matches

  • A messaging function which allows users to contact each other.

Q: Who is on your team? Tell us more about yourselves!

Our team consists of Ed Wallace, Alice Granville, Izy Champion and Jo Salter. We work for Viridian Housing and are members of the Research and Innovation team. The team was created 2 years ago to help Viridian rethink its approach to service delivery. Our work initially focused on developing Viridian’s social impact agenda, but increasingly we are looking at how we can help to transform some of our core services.

Our successes to date have focused on issues such as welfare reform, financial or digital inclusion or service improvement in areas such as domestic abuse and shared ownership. Through Housing Tinder and our other work, we want to demonstrate to our customers and the wider social housing sector, that it is possible to provide a better service through innovative, elegantly designed solutions.

Q: How did you come up with the idea? When and what was the lightbulb moment?

We've been running a Housing Options pilot over the last 12 months to support customers wanting to move into more suitable accommodation. This has been driven by the fact that benefit changes mean customers affected by the Bedroom Tax might be accumulating significant arrears, while at the same time we know we have a large number of overcrowded households.

The aim of the pilot has been to help customers move into more appropriate accommodation. There has been significant interest: over 300 customers have registered for a move, we've had 39 successful moves and reduced waiting times to around 2 months compared to nearly 2 years on our wider waiting list. Although we've achieved some notable successes, the process has been very resource intensive and staff have had to spend a lot of time creating matches. Customers have also told us they do not have as much choice and control over the moving process as they would like, and their feedback on existing services aimed at facilitating moves has been less than positive.

Our 'lightbulb' moment has grown out of this combination of factors. We feel there is a massive opportunity for digital innovation in this area and believe Housing Tinder will not only offer a delightful and intuitive experience, but also dramatically increase the amount of control social tenants have over the moving process.

Q: How will your project help the community get the best out of renting?

We want to create something that is beautifully designed, easy to use and intuitive. Housing Tinder differs from existing websites as it:

  • Only allows messaging between users who have a mutual interest in each other’s homes. We found that customers often have negative feedback about existing sites; they report spending considerable time messaging other social tenants without getting any responses. This often led them to becoming disheartened and giving up their property search.

  • Uses open data to give information about key services. We know that customers often have very strong ties to an area so do not want to move far, and when they will move they have very specific requirements about the property and area. Our app will use open data to help users find a home in the right area. We want to include data from schools, GPs and information about the job market so that it’s easy for users to prioritise areas.

  • Aims to be more accessible and intuitive to use. We’ve found that a lot of tenants find existing websites confusing and hard to use. About a third of housing association tenants do not have internet access, meaning they have to travel to access existing websites. We’ve found that customers are more likely to have smartphones than they are to have a computer with the internet at home. Our app will be mobile based so it can be used by anyone with a smartphone or tablet.

Q: What open data are you using and how does it form an essential part of your proposition?

These are the open data sources that we plan to use:

Location of schools

Location of GPs

Access to food stores (we plan to simplify how these appear in the app. E.g. “very good access for this area”.

Job density data

Jobs vacancies

Rent data (Table 704 and table 705)

We are also looking at the possibility of using data from other publicly available sources, for example the number of advertised jobs on recruitment websites.

Want to get in touch? They are around on Twitter @MoveMakerApp!


  1. OpenJamJar

OpenJamJar's Tim Drye

Q: What is your product?

We build assurance for private landlords that let to tenants receiving Local Housing Allowance. This is done by promoting and facilitating the use of JamJar accounts by Tenants within Credit Unions.

By participating in the OpenJamJar, tenants would benefit from a regular Credit Union savings cashback, the opportunity to build their Credit Score and exposure to trustworthy relevant advice at points of financial stress.

We will only deliver services that can be executed via SMS, to ensure no clients are excluded from access due to their lack of appropriate technology.

Q: Who is on your team? Tell us more about yourselves!

The team is lead by Tim Drye, a statistician by trade and a long term private Landlord to Housing Benefit Tenants by accident, with Seb Bennett: an innovative and enthusiastic A-level student, who is a resourceful researcher and analyst. Debbie Townsend is the essential administrator who makes sure things happen on time and each of us are in the right place. Additionally we have Tim Brooks, a technology strategist and social activist, who has wide experience of both coding and implementation of dispersed IT infrastructure between multiple partners.

Q: How did you come up with the idea? When and what was the lightbulb moment?

As a private Landlord, Tim, like many others worried about the uncertainty engendered by the ongoing changes in the distribution of benefits. As a result of no longer receiving payments directly from the local authority, he considered refusing tenants on benefits. However a current tenant, eager to occupy a property, proposed the use of a Credit Union account, so that Housing payments went directly from the authority to the Landlord without entering the Tenant’s general income. This has worked very successfully, giving Tim his ‘lightbulb’ moment. The team now want to do this at scale.

Q: How will your project help the community get the best out of renting?

The most obvious help is to maintain and eventually increase the number of houses available for private rent by this target group; those receiving Local Housing Allowance, and a net lower rent once the Credit Union, savings “cashback” is accounted for. This is by building assurance for the Landlords to provide access to this segment of the population.

Building on this the tenants can build their credit scores so that they gain access to cheaper forms of financial services and so ease their financial stress making them more stable tenants with less chaotic financial management. In addition, timing trustworthy communication at times of financial stress provides good guidance and allows both Tenant and Landlord to better handle the vagaries of life. Further establishing a broad base of members of Credit Unions would also help develop more of a savings culture and a better awareness of products.

Q: What open data are you using and how does it form an essential part of your proposition?

Open data is essential to deliver this project at each stage. Initially we have to identify where private tenants receiving housing allowance are using 2011 Census Data and the distribution of housing allowance.

Secondly we need to facilitate the setup of OpenJamJar accounts through using and opening up information from the Financial Conduct Authority.

Third, we use DWP benefit data and Census Information to help select appropriate messages within the 140 characters available for communication and provide generate a benchmark of rents in similar localities.

Fourth, we will use open data to link together Local Authorities as controls to our Pilot localities, and then use available and updated FOI requests to demonstrate improved measures of social impact where we have implemented the service.

The links overlap but broadly fall into the following areas:

Segment Identification & Location:

Process Facilitation: "Claimant Count"

Communication Segmentation: "DWP Benefits" "2011 Census"

Social Impact Assessment:

Collate requests about levels of emergency housing by authorities

If you would like to find out more about OpenJamJar, you can so so by tweeting @OpenJamJar and @timothydrye.


Photo Credit: Bella Zanesco of