In response to the national Troubled Families Programme, North Somerset Council’s Predicting Early Interventions project aimed to create new digital tools that would analyse family-specific data in the local area.
The Troubled Families programme is run from the Ministry of Housing, Communities and Local Government (MHCLG) and delivered by all 152 upper-tier local authorities and their partners. This includes the project in North Somerset that is labelled as the High Impact Families programme (HIF).
Making the best use of data has always been a key part of the Troubled Families programme, both in terms of the identification and analysis of families at a local level and the evaluation of the programme at a national level. Indeed, as part of the sign-up process for the Troubled Families Programme in 2015, all upper-tier local authority chief executives made a number of key commitments, including monitoring and evaluating the programme.
In North Somerset the monitoring and evaluation processes are carried out centrally by the Business Intelligence Service. This is done by analysing information within a broad range of databases, spreadsheets and systems.
However, by 2016 the council was finding it challenging to manage the growing workload associated with the monitoring and evaluation requirements of the programme. Increasing numbers of families were being identified to receive support (the government target is for over 1,000 families to show improvement following help from the council) and each of these families had to be monitored both on entry to the programme, during the programme and post-programme.
It was recognised that one of the root causes of the difficulties being experienced was the complex and silo-based digital architecture that supported management information in North Somerset’s children’s social services.
Recognising that the existing monitoring and evaluation process for dealing with the HIF programme was unsustainable within current costs, and given there wasn’t the option of increasing the budget, and forecasts clearly indicated that workloads would continue to grow, then it quickly became apparent that the team needed to ‘work smarter’ and redesign the processes to make these more efficient.
It was envisaged that this could be achieved by drawing all the related systems together under one umbrella, either via a single database or via interfaces, allowing the data within existing systems to be used in a smarter, more efficient way. Hence, this project, Predictive Early Interventions (PEI), was launched and this aimed to develop a tool that would use the data held within the various systems, to enable the team to analyse what support these families would need through their HIF journey.
As a result, frontline workers would be able to put the necessary measures in place to deal with those families at greatest risk both at the earliest opportunity and in a more joined-up way. For example, families where children had low school and nursery attendance could be prioritised for support by both education welfare officers and children’s centre support workers.
Full case study
Predicting early interventions
You can hear more from key people involved in the project via the videos below: