Pictured: Social Kemistri's needs profiler system schematic example. humans do this work and then help them to use their compassion, empathy, experience, knowledge and expertise to do it better. We design and build decision support systems that recognise their unique human attributes and allow them to focus on the things they do best and that really matter.” To build the tool, Social Kemistri worked in partnership with three local authorities which provided sample data. From this it was able to conclude that the needs of a child with SEND and an EHCP could be accurately classified and assigned to nine clusters or groups. “Our method means more signal and less noise. Each cluster is sufficiently distinct as to be well differentiated one from another. A child or young person cannot be in two clusters at one time. This set of nine needs-clusters covers the entire SEND landscape. Each cluster is information rich but simple enough to understand to be accessible. It carries the essential data to join up needs (severity and complexity) with outcomes and provision. It simplifies how we communicate about a child’s needs and provision without reducing information content,” Penney added. Using the tool, a case worker enters the child’s age and answers 20 questions about their needs to enable them to be assigned to a cluster. In essence, it takes the 16-20 pages and 4,000 to 5,000 words of the ECHP and provides an ultimate summary. Penney added that the emphasis is on a system that supports professionals to make complex decisions better and more consistently. However, it is not a one-size-fits-all solution and therefore helps with compliance with The Special Educational Needs and Disability Regulations 2014 legislation, which includes the requirement to take the views, interests and aspirations of the child and their parents into account.
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There is a realisation that adopting the technology is not for the faint-hearted. It will require a period of adjustment where a local authority needs to correct any disparities and misalignment of how resources are currently allocated. Through looking at data from four local authorities so far, Penney acknowledges that process would be the same for any council. “There are no quick fixes. You have to give the schools space and time to adjust to the new realities that are revealed by the data and the model. Our approach is truly transformative – it really does change things for the better. Every child or young person with an EHCP and SENDs has a better chance of getting what they need from their education. This really matters in delivering better outcomes and life experiences for children and is even more important for their life chances as adults. “Better outcomes, and that's what parents and children really want and deserve, depend on more accurate targeting of resources. Data analytics uncover and shine a spotlight on the inadequacies of the existing system and processes so it's not surprising to find some local authorties are reluctant to take the next step. Some are really worried by change because they're concerned things might not work out or they will lose control. This is just a system or service reset based on some sound principles, values, simple maths, and common sense. The funding should follow the child and be commensurate with that child's needs and assessed outcomes. The provision should be matched to the outcome and needs and funded according to the cost. Our model and system does that quickly, consistently, and accurately,” Penney added. Social Kemistri estimates that an investment of around £500,000 is needed to create a fully operational system. A significant chunk of that money will be used to create a contextual feedback system to give children and parents more say about how well the EHCP is working for them. The company is developing efficacy metrics which will drive true outcomes-based commissioning and help with demand profiling and market shaping. That level of investment also funds a large-scale trial and developing a transition strategy and impact model. The core technology is in place and now the database requires populating to agree the detail and specific costs of each of the nine provision maps.
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Getting a consensus of a fair pricing across an education authority is time consuming and the schools need to be involved in the process. “The costing of recommended or standard provision maps and tables must be co-produced with schools to ensure they are realistic and fair. We have produced a financial impacts model which makes it easy to collaborate with schools to cost recommended provision profiles within any new top-up funding decision support system. Any winners and losers, by definition, are short term. A new model cannot, however, solve the problem of inadequate capacity or what might be perceived as excess demand. What it can do, is make sure that funding follows the child or young person and their needs. And that the local offer is better profiled to meet future demand. It can also allow the child or young person, their parent and carers a better chance to engage with and influence the system they deeply depend upon,” Penney concluded. • To find out more contact Tom Penney at Social Kemistri: tom@socialkemistri.com
CASE STUDY:
Brighter Futures for Children Gary Pyke, Interim Head of Transformation and IT at Brighter Futures for Children (BFfC), commissioned Social Kemistri to create the top-up funding modeller. BFfC is a not-for-profit organisation which delivers children’s services in Reading. Social Kemistri took 140 EHCPs from BFfC and did cluster analysis against the population of 1,400 EHCPs across the whole of Reading. Pyke explained the challenge that BFfC and other local authorities are facing and why he commissioned the project: “We have a schools education top-up funding challenge. We are spending a lot of money and a lot of that money is spent on a small number of children, so we need to find a way of allocating that money better,” he said. The organisation also wants to move away from a model which is cost-driven to one which is needs based. “We have got to create a model that is more efficient, taking time out of the system of people who are having to read a twenty-toforty-page document to determine funds allocation. I think the technology has now developed sufficiently that this is a viable use of AI to help the person in the loop to make better decisions. With a system like this, we can defend why an award is as it is. If we have something that acts as our base determinate, we can vary it up or down as required but it gives us something that is a very good starting point that can be developed very quickly and efficiently,” Pyke said. BFfC found that the product did what was required but was unable to invest the required amount to make it a viable product at this stage due to prioritising other needs.
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