UK Ministry of Housing, Communities and Local Government (MHCLG) 
Exploring and prototyping a common service pattern for online housing repairs
From our discovery, we identified council tenants’ and leaseholders’ user needs and barriers for going online to report and book a repair and that a common service pattern for online repairs is possible.
For the alpha phase, we want to explore and test:
- Whether the ideal user journey and wireframes for the resident facing online service will allow tenants and leaseholders to easily report and book a repair and hence want to use the online service instead of calling
- What is the most effective way the common service pattern can be implemented and integrated with existing housing repair systems.
To test the above, we want to implement and test an end-to-end Minimum Viable Product (MVP) based on our common service pattern for two repair types which will allow council tenants and leaseholders to report, book and amend an appointment, and receive appointment reminders and alerts. We will integrate with the existing housing repair systems of the partner authorities and explore how the common service pattern can be implemented while doing so.
We want to focus on heating and damp/mould issues, as the repair types for alpha. Our key reasons for the scope of the MVP are:
- The report, book an appointment, amend appointments and receive reminders and alerts functionality include areas that were considered important for meeting user needs.
- Heating and damp and mould issues are high volume repairs and have a high first time fix percentage. Focusing on two repair types instead of all repair types reduces complexity and will allow for end-to-end testing within the time and budget restrictions of the fund. Both repair types will still deliver benefits for participating authorities and generate useful insights and learnings from the MVP.
- Integration with existing housing repair systems will allow the end-to-end repair process, reporting, scheduling and management to be tested.
We will build on the discovery user research and carry out further user research to better understand the users’ needs of our identified personas, including their support and access requirements. We will use interviews and visits to deepen our understanding of relevant aspects of our users’ lives and work, and test out design concepts and prototypes. We will feedback on how well our designs work for users and what we have learnt about usability issues related to layout, functionality and content.
We will know the Alpha phase is successful if:
- The common service pattern and ideal user journey can be applied and implemented by the partner authorities regardless of the different repair systems and business rules
- 90% of users can complete raising and scheduling a repair during user testing
- A repair can be reported online in less than 3 minutes.
Councils are responsible for providing repairs to socially rented properties. Most users access the service by phone and it is typically the service with highest volumes. The service is attractive to provide digitally, however when an acceptable telephone channel exists take-up is often low. The national cost of repairs call handling is estimated at over £30m per year. It is estimated that only about 50% of calls are for new repairs, implying significant levels of failure demand. Our discovery aims were to identify:
- Barriers to adoption of digital repairs services
- Elements best suited to automation/self-service
- Optimal uses of technology to improve user satisfaction and reduce costs
- If a common service pattern for end-to-end delivery of repairs is possible
- How the service pattern can be mapped to the Housing Associations’ Charitable Trust (HACT) repairs data standard.
Our discovery findings found:
- Top barriers to using current digital repairs service included forcing a login to report a repair; mobile versions are not responsive, accessible or user friendly; online reporting of a repair does not result in an appointment; no way to view or amend an existing booking; and current phone services are much better than the online service.
- Although the 3 discovery partner authorities were different in terms of number of socially rented properties, population size and demographics, and housing systems used, we had a lot in common when delivering a repairs service and hence made identifying a common service pattern based on the HACT data standard possible.
- We identified common user personas, their needs and frustrations, and used the user research to design an ideal user journey and wireframes for the resident facing online service which we want to test in an alpha phase.
Our discovery user research identified the following priority needs for a resident:
- As a resident (tenant & leaseholder) I want to find out what I am responsible for so that I know whether to report the repair or fix it myself
- As a resident (tenant & leaseholder) I want to report a repair online
- As a tenant I want to be able to book an appointment for the repair to be fixed
- As a tenant I want to add my contact details so you can confirm my appointment and send me reminders and alerts
- As a tenant I want to add contact details of the person who will be home during the appointment so that you can contact them directly if you will be late or have issues locating the property
- As a tenant I want confirmation of my reported issue and appointment time
- As a tenant I want to be able to cancel my appointment
- As a tenant I want to reschedule my appointment
We believe that through implementing and testing an MVP of the ideal user journey and wireframes for the resident facing online service which includes reporting, diagnosing, scheduling, amending repairs and sends reminders and alerts, we will improve the experience for tenants and leaseholders when using a repairs online service.
Our discovery identified a broad range of financial benefits for local authorities as a result of implementing the ideal customer journey. The quantifiable benefits identified include reduction in the volume of calls to a council’s contact centre enabling resourcing levels to be reduced, reduction in missed appointments, more accurate diagnosis which increases first time fixes and reduction in physical inspections. The full list of benefits and calculations can be found in our discovery report.
We have been conservative in how we calculated cashable benefits. The maximum achievable benefit for each of the quantifiable benefits are reduced by 46% to reflect the proportion of tenants that our research has indicated are likely to use online services and then further profiled over 3 years taking into account what is realistically achievable for digital take up:
- 33% of the digitally achievable benefit being realised in Yr1 (19/20)
- 66% in Yr2 (20/21)
- 100% in Yrs 3-12 (21/22 to 30/31)
The table below shows the estimated benefits profile for 10 years from 2019/20 to 2030/31 for the lead authority, Southwark:
Measure Financial year
19/20 20/21 21/22 22/23 23/24 24/25 to
30/31
Total
Gross
benefit
(£’000)
189 378 573 573 573 4,013 6,299
Net
benefit
adjusted
for
189 366 535 517 500 2,974 5,080
The total net benefit (adjusted for inflation) realisable by the lead local authority for 10 years between 2019/20 and 2030/31 is estimated at £5.08m and £3.95m in total for the other 3 discovery partner authorities.
We also calculated the benefits case for the average local authority in England. There are 161 local authorities across England managing council stock (excluding the 4 local authorities in the discovery). Each has an average of 9,452 general needs/sheltered properties.
The maximum, expected realisable benefit for each has been calculated by working out the maximum quantifiable benefit for the 4 local authorities participating in the discovery project, per property, and then calculating this for the average local Authority in England.
A high case and low case was calculated:
- high case; 62%, based on the upper quartile proportion of tenants from our discovery research that are likely to use online services
- low case; 52%, based on the median proportion of tenants from our discovery research that are likely to use online services.
The total net benefit (adjusted for inflation) realisable by the average local authority in England from 2019/20 and 2030/31 are:
- high case: £1.53m
- low case: £1.28m.
Indicative future cost is difficult to estimate at this point in time however Hackney Council has spent approximately £540k so far developing repairs and work is not complete. We anticipate that the cost will be closer to £700-800k however more research is required to understand integration/migration cost for legacy repairs systems and rollout costs. As such we are unable to give an estimated return on investment.
We will use the same collaborative and iterative approach that worked well in our discovery.
For key sessions such as initiation/kick-off we have found face to face workshops effective and representatives from each partner have been fine with travelling if given enough warning so we will continue with the same approach.
The project will be run in two week sprints with daily stand ups. The stand ups with partner representatives and successful alpha supplier are carried out over video conferencing and allows for work prioritisation and problems resolution to happen on a daily basis. Insights will be delivered and shared at the end of each 2 week sprint with partner councils in show and tells to draw out feedback. We will also hold fortnightly sprint planning to inform priorities for the next sprint.
We will be looking to use tools such as Google’s G Suite, Trello, week notes, video conferencing and Slack to collaborate, share findings and progress on the project.
We have found guidance and support on reviewing our user research and regular progress check-ins from the Local Digital Collaboration Unit helpful during discovery and would appreciate the same support in our alpha.
We provided feedback from when we took GDS’ Agile for Teams so we are hoping a revised and local government focused version of the course will be available to our new partner authorities. User research training would be helpful as well.