Objectives
This section should be read alongside the separate Placemaking project document on metrics. Using demographic, housing, involvement and satisfaction measures to track progress on a regular basis is a foundation for continuing improvement into the long term future.
The distance travelled becomes a key concept as it helps capture qualitative changes in individuals and communities engaged with placemaking initiatives.
Establishing useful and relevant measures
Almost all providers in the Placemaking study mentioned the need to keep track of data that gives an insight into what is happening with an estate. But many also acknowledged that their work on this is at an early stage.
Providers should build a profile or map of a neighbourhood, combining data with local insights from the community. Providers should ensure they have a baseline set of data at the start of their placemaking journey, to enable them to evaluate the success and cost effectiveness of initiatives. They should keep a dashboard of data that is updated regularly, and reported to senior management. This data should be analysed, and action taken on the findings.
Tenants and social capital: a quick checklist
The Placemaking project sets out here five quick questions to help community housing providers gauge whether they are asking the right questions of themselves when approaching the question of monitoring and metrics. The questions should help providers to check whether they are doing all they can to learn from what works and good practice, and take their placemaking work forward.
Download the Self-assessmentResources
Stage 6 Self-Assessment
This is a template which you can use to manage your community’s assessment for Stage 6 Tracking Success placemaking practices and track your improvement.
Case Studies
Beyond Housing Dormanstown UK
Beaumont Estates East London UK
Beyond Housing Dormanstown UK
Provider Beyond Housing developed a ‘shape tool’ that encompasses housing management data, crime statistics, demographics (IMD scores down to lower super output areas covering
perhaps a few hundred homes), satisfaction ratings, complaints and more, that can be used at a very local level. It can help to identify issues on a particular street or area, so that action can be taken to improve tenants’ quality of life. It can also identify the costs associated with, for example, empty homes, and point to reasons why a home might be empty for longer than average.
In one example, operatives were repeatedly called out to mend broken windows in one small group of homes. The windows were always at the back of the houses and overlaying maps to the data revealed that an area of open space behind the houses had become a magnet for antisocial behaviour. The open space had poor lighting and no natural surveillance. There was also a link to fly tipping, driving further customer dissatisfaction and creating costs. The next steps therefore were to deliver investment to the rear of the properties to close alleyways and increase lighting. This should show in the data as a reduction of broken windows, reduced cost of repairs and rubbish
clearance and improved tenant satisfaction.
