Using Data to Save Costs: Digital Adoption in the Social Housing Sector

Data is leading a quiet revolution in the social housing sector, positively impacting real decision making

Data is leading a quiet revolution in the social housing sector, positively impacting real decision making

As of 2019, around one in three councils have adopted algorithmic software to assist in making decisions regarding Universal Credit, housing allocation and other services. That number is only set to rise. The current climate has shown that having trusted cloud-based systems in place can assist all landlords and tenants to provide and access the services they need, from wherever they are.  

It Is predicted that the next quarter century will usher in the Fourth Industrial Revolution, whereby analytics, machine learning, AI and robotics will overhaul every industry at an exponential rate.  Some jobs will be deemed obsolete, taken on by intelligent robotics, whilst other roles will be created in order to analyse these machines and apply the results in the human environment.

Back in the present, in the delivery of social housing, healthcare and government services there is a quieter revolution taking place. In the face of mounting challenges, good software delivering collated data in near real-time is allowing human decision-making to become more focused and efficient. Although adoption to digitise operations in the social sector has been well underway for some time, 75% of housing associations asked by Phoenix Software in 2018 didn’t think their organisation capable of effectively using the information it stores.

It is imperative for local authorities (LAs) and housing associations (HAs) to embrace these services, as any savings made through utilisation of data and the streamlining of processes can be fed directly into building more homes, improving existing homes and plugging the ever-growing housing funding gap. According to the Chartered Institute of Housing, in the year 2016/17 LAs and HAs invested £4.7billion of funds raised by rents into new and existing stock, which outstripped central government spending ten-fold. With more citizens potentially becoming affected by a deeper housing crisis in the near future, capital can be sourced by social housing providers and directed to customer sustainability and welfare.

“Good use of data can be hugely beneficial in helping councils make services more targeted and effective … But it is important to note that data is only ever used to inform decisions and not make decisions for councils.”

A spokesperson for the Local Government Association

What are the benefits of harnessing organisational data?

Computers are more capable and much faster at establishing sequences of behaviour, such as patterns of financial capability, than any human ever will be. Data collation and visualisation software puts these results into the hands of those who can investigate further and enact support using evidence paired with empathy.

Nesta reported that councils engaging data and analytics across services, found some of the key benefits to be; more productive staff, more effective services, the reduction of environmentally harmful activities and – importantly – financial savings, which could then be reinvested within the council. Croydon Council has reported that their ‘Gateway’ system has been utilised to reduce homelessness. In Bristol, officials can download any individual’s ‘vulnerability profile’, which tracks the issues that may affect vulnerable families.

What are the risks?

Automating services with the sole aim of cutting costs and personnel will never achieve the results that can provide organisational transformations. Staff and tenants need to be on board and well trained in order to achieve the best results with harnessed data. The Guardian has been tracking the “trend among cash-strapped local authorities to embrace algorithmic technology to analyse their citizens. It holds out the hope of reducing fraud or preventing costly social problems, but the systems are often opaque.”

One council in The North of England had to cut ties with a private software company whose service was intended to flag vulnerable or problematic tenancies in terms of benefit claims; council tax wrongly identified low-risk cases as high risk, leading to councils embarking on the wrong measures with the wrong people.

“It is not replacing professional judgement; it is not making any decisions on its own. What it does is give us information that has been sunk in organisations’ memories.”

Gary Davies, the head of early intervention and targeted services for children and families, Bristol City Council

Case Study: Camden Residents’ Index, London Borough of Camden

Camden Council brought together the data from 16 council IT systems and services. This uber-collation aimed to eliminate the margin for repeated work across council silos. Through the process, Camden targeted fraud such as blue badge, housing and school applications. Solely through the identification of illegal subletting, they have managed to save £800k as of 2016. The bringing together of 123 fields of primary demographic information aims to improve back office processes and service delivery to meet a £70million funding gap

“There is too much hype and mystery surrounding machine learning and algorithms. I feel that councils should demand trustworthy and transparent explanations of how any system works, why it comes to specific conclusions about individuals, whether it is fair, and whether it will actually help in practice.”

David Spiegelhalter, a former President of the Royal Statistical Society

Case Study: TAIM InSight, Metropolitan Thames Valley

It was in 2017 that we started working with Metropolitan Housing to implement our InSight solution to help support them with challenges, such as identifying and supporting tenants at risk from the rollout of Universal Credit, assessing and managing tenancy sustainability, tracing former tenant debt and securing income by growing the sign up of Direct Debit payments.

Throughout the financial year from 2018-2019, Metropolitan increasingly used InSight to identify tenancy fraud within their housing stock, which resulted in them discovering 54 proven cases of fraud. The public purse saving from these 54 cases alone is estimated at £693,000.

In recent months, Metropolitan have merged with Thames Valley Housing Association to form Metropolitan Thames Valley Homes. In Spring 2019 we started working with Metropolitan Thames Valley to implement InSight for their Thames Valley stock, concentrating primarily on tenancy fraud.

Since April 2019, Metropolitan Thames Valley Housing have had continued success with using InSight to identify tenancy fraud. During the period from April – February 2020, there have been 50 additional proven cases of fraud. The total saving to the public purse from 2018-2020 is £1,071,000.

“The InSight solution has proved invaluable for the Income team. In 18 months of using the product, InSight has supported the recovery of 104 homes, which we have been able to reallocate to those most in need.”

Tim Millns, Director of Income & Leasehold Services, Metropolitan Thames Valley Housing

Multi-cloud structures are where most organisations in almost all sectors are moving towards. Those who had already embraced cloud technologies for their operations have been at an advantage at this particular time, when remote working and remote customers are becoming the norm. When housing associations have the ability to streamline and analyse their data, it becomes easier to understand the customer base and spot changes on the horizon, pre-empting crises before they occur and stalling, or at times, preventing the need for a wealth of resources to fix them.

Housing Partners build a number of solutions for the social housing sector including TAIM. If you would like to know more about what we do, please drop an email to