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Troubled Families

Analytics to support early identification and intervention 

Challenges

When the UK Government first launched the Troubled Families programme back in 2012, its plan was to turn around the lives of 120,000 troubled families by getting children back into school, reducing youth crime and putting adults on a path back to work.

Since then it has extended the programme, injecting an additional £200M to identify and support a further 400,000 families. Incentivising local authorities and their partners to identify and monitor families with a high level and complexity of needs.

But with data siloed in various systems, analysts and managers can spend hours identifying one troubled family. All of which makes it a challenge to plan appropriate interventions and ensure turnaround times are met.

Solution

Our Family Intelligence Hub streamlines the task of identifying and monitoring families, using data from a variety of organisational sources and partner agencies modelled in an environment to support Phase 2 of the Troubled Families programme. Providing clear, concise and accurate intelligence in a number of formats for analysts, social care teams and senior management underpinned by robust data analysis to identify service users' needs and determine future service development.

With a drive towards "joined up" programs, Portal's solution is designed to support multi-source, multi-agency intelligence covering, for example: modern slavery, gang violence, benefits and environmental health investigations. Significant financial returns have been reported, in addition to wider community and operational benefits.

Benefits

  • Automate Troubled Families identification supported by reports to assist PBR claims.
  • Multi-source data fusion to support adjacent Local Government programmes - Modern Slavery, Gang Violence and Explotation programmes, PAUSE etc..
  • Uncover complex hidden connections between individuals and families through visual analytics.
  • Significantly enhance business processes, from case referral to review by up to 60%.