This report written by Institute for Government (IfG) in partnership with Nesta explores what data is available on children’s centres and youth services, and how government might overcome the barriers they face improving this data.
- Investment in preventive ‘upstream’ services, such as children’s centres and youth services, can improve outcomes for children and young people while also reducing demand for more expensive ‘downstream’ services, such as children’s social care.
- However, the lack of consistently good-quality data restricts the ability of frontline staff, local authorities and central government to understand what works and therefore to intervene in an evidence-based way.
- The core problem we have identified is that much of the data that is key to making more effective decisions in children’s services is held in a siloed and fragmented nature across central government, Local Authorities and their delivery partners.
- This lack of connectivity, combined with other issues, inhibits the public sector from taking a holistic and comprehensive approach to data usage for policymaking, service delivery and evaluation.
We recommend that the Department for Education (DfE) works in partnership with the Ministry of Housing, Communities and Local Government (MHCLG) and a single Local Authority to implement the following recommendations over the next 12–24 months. This process could then be refined and rolled out nationally.
1. Identify data demand:
- Consult a diverse range of stakeholders to define a set of objectives as to why various actors want to use children’s and young people’s data. This exercise should include policy, analytical and operational teams from across the department and the LA partner as well as relevant frontline practitioners.
- Once the objectives for data use have been specified and prioritised, DfE should map out who would need access to the data and within what time frames to meet the objectives
2. Identify data supply:
- Identify what data sources are available at the national, local and operational levels.
- Identify who is responsible for collating and governing this data.
- Identify those with whom the various data sources are being shared.
3. Conduct a gap analysis:
- Once the existing data landscape has been mapped, DfE should analyse whether any data is missing, incomplete or redundant in light of the defined objectives.
4. Initiate high-impact data transformation projects:
- Implement a data quality improvement service.
- Improve data linkage.
- Improve data access.
- Improve data literacy.
- Address wider cultural barriers to change.
