What does the new research tell us about….
1. Variation in existing practice
IFF’s qualitative study found that there is variation across local authorities in England in how RONI tools are used, including who leads the process (local authorities or schools), how data is collected and used, and how interventions are delivered.
The effectiveness of RONI tools in identifying at‑risk young people depends on several factors. Strong relationships between local authorities and schools, skilled staff, and good cross‑service collaboration support effective data sharing. However, patchy school engagement, data‑sharing barriers, and limited resources, at both school and local authority level, can create challenges.
2. The potential of an enhanced RONI tool in providing nuanced understanding of risk
NatCen’s new NEET Early Risk Index (NERI) which drew on learnings from previous approaches to identifying risk of NEET used in Blackpool. NERI is a response to challenges experienced locally, and is an enhanced tool offers a more nuanced and accurate way of identifying young people who may need support. The new tool focused on improving earlier identification and accuracy through weighting the different risk factors, whilst at the same time ensuring no additional data burden on practitioners.
Key findings about at-risk young people from developing this enhanced data driven tool included:
- That whilst GCSE attainment remains the most influential indicator of later NEET outcomes, risk shows up earlier and prior attainment is a strong predictor, with educational gaps emerging by the end of primary school.
- That supporting young people with Special Educational Needs (SEN) requires a differentiated approach: SEN status is often used as a single marker. However, when attainment and background were accounted for, young people with dyslexia, dyscalculia, dyspraxia or language disorders faced a similar NEET risk to peers without SEN. Young people with profound, multiple or severe learning difficulties, on the other hand, have a NEET risk 2.6 times higher than those without SEN even after accounting for other factors, and those with autism spectrum disorder, remained at substantially higher risk.
- That disadvantage compounds risk – eligibility for free school meals (FSM), care experience, and neighbourhood disadvantage sharply increase NEET risk.
Taken together, these changes enable the tool to support practitioners with earlier identification of at-risk NEET young people, with improved accuracy, and requiring little additional reporting data from schools, and thus less burdensome overall.
3. The importance of professional judgement
Both reports provide examples of how existing and new RONI approaches can help identify risk earlier and more consistently, and there is a benefit when they:
- Focus on earlier prevention – NEET risk is identifiable from Year 6, making timely support at key transitions critical.
- Account for local contexts – risk indicators can cluster locally, with disadvantage compounding risk, so national strategies should support place-based approaches.
- Prioritise tailored, differentiated support.
However, another key message across both reports, is that data-driven tools should support professional judgement, not replace it. Tools cannot capture the full complexity of young people’s lives. Teachers, pastoral staff and career leads will always hold critical contextual information that cannot be captured in administrative datasets, and as such, they play a key role in identifying and engaging at risk young people.
