Two recent articles in The Independent highlighted the increasing trend for Local Authorities to be challenged by the courts to justify the way they fund and manage their SEND provision. This made us here at Mastodon C think about ways in which our Witan SEND model can be used to help authorities when judgements are made in the courts, or when similar kinds of unplanned and unexpected situations arise that could impact on their decisions and ability to deliver a broad range of complex services.
The first article from Sarah Ward and Michael Yong, highlighted a case where the High Court ordered a council to reverse cuts to their SEND budget, with Judge Barry Cotter QC telling the local authority that it had “acted unlawfully and there was no need for a reduction”. The High Court deemed that the decision was targeted at reducing overall spending, without taking sufficient account of its impact on the welfare of children affected.
Education leaders are faced with the enormous challenge of balancing welfare needs with extremely tight budgets, and so need to trade off extremely carefully between different ways they could configure services – or be able to very confidently evidence the future cost of delivering any acceptable service, in order to argue for the budget that is needed. These ideas and tradeoffs can include investing in special resource provision in mainstream settings, to later reduce special school demand; juggling expansion of existing settings versus using out of borough settings where some needs are expected to remain very rare; and understanding the timing and resource impacts of all these ideas in the most rigorous way possible.
We have been supporting leaders in thinking through this difficult situation, by modelling out what would happen in terms of pupil numbers and budget per year in each case. While those leaders are the experts in what types of services are right for what types of pupils, we can then work out in fine detail what the resource implications are of delivering that service in the unique local context.
We are able to do this because our model takes into account not only the current number of children with SEND and their cost, but also how those individuals have transitioned and moved through the SEND system in the past. This means we are able to apply a modifier to the rate of, for example, people who historically joined special schools with a particular need, and see what would happen if for example they joined mainstream schools with special SEND support, combining both the observed increase to inclusion and education and the projected reduction in cost due to a limiting of new people joining special schools.
The second article, from Eleanor Busby, argued that in future schools will find it “harder” to exclude children with SEND due to aggressive behaviour clearly linked to their condition, following a landmark court judgement.
Exclusion rates have dramatically increased in preceding years, with some reports suggesting that this behaviour is linked to an attempt by schools to not allow poorly achieving students to bring down a schools overall performance, so-called “off-rolling”. With our modelling and an authority’s data we are able to observe the rate by which students may move to “alternative provision” due to exclusion from mainstream schools. A policy change like this, whereby an authority may anticipate a decrease in the number of individuals moving between two specific settings, mainstream and alternative provision, can easily be modelled with the Witan SEND model. We can even provide multiple sets of results whereby we test different rates of change, for example if the policy didn’t come into effect for a few years or if the decrease in movement to alternative provision was to be very high (90% reduction) or relatively low (50% reduction). All of these parameters to the Witan SEND model are tailored to a specific authority and their data.
For more information about the Witan SEND model and the possible scenarios that it can provide please see the links above. If you are working within local government, we would welcome your feedback and would also like to hear about your experiences and approaches to these perceived risks – email@example.com
An example of two potential future SEND populations based on policy changes
With thanks to Fran Bennett, Shawn Jhanji and Chris Taylor for their input and feedback to this post
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