Phil Neal explores the challenge facing local authorities in predicting local availability of school places and discusses how the use of technology can help them meet families’ needs.
In many areas, the shortage of primary school places is a cause for concern that can generate anxiety among families seeking to secure a place for their child in their first choice school.
Media reports suggest that one in five primary schools in England is already full or near capacity. This is supported by the latest figures from the National Audit Office, which reveal that a quarter of a million additional school places will be needed by autumn 2014 if the rising demand is to be met.
Predicting the number of places required for school starters has always been a relatively complex undertaking. Birth rates rise and fall, and migration levels change over time, resulting in variations in the need for primary places.
In recent years, the effects of the changing economic climate have also had a major impact throughout the country, creating an even greater challenge for those responsible for mapping future school populations. In some local authority areas, an increase in the number of families relocating have been prompted by the need to find work following redundancy. Housing crises can bring additional uncertainty, with more families moving into temporary accommodation.
These factors add further layers of complexity to school place prediction, and when fewer places are available, local authorities are under increasing pressure to be more accurate in their forecasting so that they can meet the needs of the children in their area.
A technology based solution
The need to adapt to the ebb and flow of the marketplace and understand consumer behaviour has driven the development of effective business intelligence tools in the corporate world. The public sector can also take advantage of systems which analyse population shifts, trends in school popularity and local variation, to provide a more accurate picture on which to base decisions about school place provision and other public services.
Technology provides the framework for a more focused prediction of school place demand. Analysis of current and historical data from a range of local sources is useful for building a matrix of information. And by having all the data in one central location, council staff have easy access to a greater pool of knowledge to inform school place needs.
Weighting factors which call upon local knowledge can be applied to population data, pinpointing more closely the influences on a particular area. Factors such as the closure of a factory that previously provided employment in a town, or the expansion of a successful local business could be considered.
Key data sources
Much of the valuable information about a school’s catchment area is provided by planning departments. A new housing development will have an impact on school place demand by attracting more families to an area. In turn, additional funds from developers enable a school to accommodate new pupils, which can also be factored in.
Postcoding software and Geographical Information Systems (GIS) help councils to understand the profile of a school’s catchment area, identifying where the families of prospective parents live and constructing an outline of future school age populations.
In addition, predictions of school place demand can be made using data such as births and pregnancy rates provided by Primary Healthcare Trusts. This, combined with population profile figures from the Office of National Statistics, gives councils a guide to the number of children that may need school places, should the population remain stable.
Early Years settings are another key source of data for estimating the potential requirement for school places a few years down the line. Children’s centres and nurseries provide information about the children who are likely to be populating the classrooms at the local primary school in future. Authorities can also track movements from infant to junior schools, and identify the age flux in particular year groups, including the overlap caused by children leaving a primary school early to attend a high performing middle school.
Building the local picture
Population data provides a solid foundation on which to make predictions, but there are other influences which could supply greater depth to the overall picture. When supplemented by local information, such as shifts in employment patterns or shortages of affordable housing, decisions can be even more informed.
Just as businesses spend much time analysing the behaviour of their customers, authorities can consider the way attitudes to schools change. The popularity of a school can rise or fall in a relatively short time in response to the appointment of a new headteacher or the publication of an Ofsted report, for example. A technology-based approach to forecasting can add school popularity shifts into the mix. These short-term changes can be combined with information about year-on-year school choice trends by investigating patterns of gains and losses in pupils over longer time periods.
The opening of free schools and academies is another factor that can alter the pattern of the education provision in an area quite rapidly. As more parents consider these schools, predictions are becoming harder to make. A powerful IT system that includes business intelligence tools enables councils to examine the impact of these schools on the maintained sector and build this into the model.
There are many sources of information for authorities to include in developing accurate predictions on the demand for school places in their local area. The process of analysing and evaluating the available data can, however, be extremely laborious and time consuming. A system which stores all of the data in one place, eliminating the need to consult other teams or multiple databases, could represent significant savings for councils in both time and resources.
Having one central database reduces the need for additional information gathering, analysis and data entry, helping to decrease the risk of error inherent in completing these tasks. Local authorities which have embraced a technology driven approach to forecasting also find that conducting school place reviews is much simpler. Calculating the requirements for new school builds or additional accommodation for existing schools can be carried out using a robust IT system. Assessment of budgets, staff numbers and resources can be built into the decision making process too.
Using specialist technology takes the guesswork out of planning for future school places by enabling councils to consider a range of scenarios to measure their impact. Predictions can be made with greater confidence allowing councils to respond more effectively to local demand for school places.
Predicting future demand for school places will always be a complex task, but, with the right technology in place, councils can take an efficient and informed approach to the decision making process. And with more accurate forecasting, staff have the insight provided by historical and current data and will be better equipped to help more families to secure a place for their child at the school of their choice.
Phil Neal is managing director of Capita One, whose management information system is used by 120 local authorities to manage data on children and families.