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Modelling and understanding the impact of right-to-buy and pay-to-stay

"We needed to quickly build a model to assess the impact of these policies on TVH and allow us to budget effectively. Without the Clearview tools we simply would not have been able to do this as efficiently and effectively as we did."

Thames Valley Housing (TVH) is a registered social landlord, based in Twickenham, South West London. They own, manage or administer loans for over 14,500 properties in London, Berkshire, Surrey, Hampshire, Oxfordshire, Buckinghamshire, Wiltshire and Sussex. They provide affordable rented homes, shared ownership, market rent, student and key worker accommodation, working with eight NHS Trusts.

Right-to-Buy-660x330.pngLike many in the social housing sector just now, TVH decided to set about understanding the financial impact of right-to-buy (RTB) and pay-to-stay (PTS) policies on their organisation by building a financial model.

Finding, cleansing and combining data

There are many challenges with a project like this, including a need to build a data store that contains data from a variety of different sources. This helps to ensure that TVH can assess individuals against all restrictions and eligibility criteria for RTB and PTS policies. The team decided to use the Clearview business intelligence and reporting suite as the tool for the job.

Christopher Roberts (002).jpgChris Roberts, Data analyst, TVH was part of the team tasked with producing the budget model.

"We chose to use Clearview because it is perfectly suited to the task we faced. We needed to combine and blend a number of data sets, identify where we had holes in our data, and then supplement the model with data to ensure we could effectively assess the impact of all aspects of the policies by fully considering all eligibility and restrictions imposed."

Right-to-buy

Discussing right-to-buy Chris says,

"We started with our property data and then added length of tenure to it from our housing management system, Civica. We then included fields to help us identify properties specifically built for older people, where the council had imposed restrictions on a property’s use, and also whether a property was part of a section 106 agreement or adapted for those with a disability or rural support. Clearview was great for this as it was easy to combine data sets and add extra columns and filters. We were also able to see early on where we had missing data."

Pay-to-stay

Pay-to-stay was similar but required more tenant related data in the model. Chris continues,

"For pay-to-stay we needed more data about tenants and also an assessment of what market rent was. For this we identified a data set on average rents in the UK from gov.uk and used it in the model. We expanded our tenant data with rent payment history information: looking at arrears, those on benefits, and so on, to assess eligibility."

Fully understanding the impact

The resulting model has enabled the TVH finance team to fully assess and understand the impact of right-to-buy and pay-to-stay policies on the organisation.

Chris summarises,

"We needed to quickly build a model to assess the impact of these policies on TVH and allow us to budget effectively. Without the Clearview tools we simply would not have been able to do this as efficiently and effectively as we did."