Robust forward planning for school places is an essential task for all local authorities in England, with each having a statutory responsibility to provide sufficient school places to meet local need. Common to all local authority areas are the challenges associated with unprecedented demographic change, a renaissance in the development of new homes, structural change to the funding and organisation of schools, plus the continuing uncertainty associated with the UK’s exit from the EU. The combination of all these factors means that school place forecasting is now more challenging than ever.
In planning education services, a PSS is an essential tool for anyone involved in school forecasting and planning. Without a PSS, the task of ensuring an appropriate balance between the supply and demand for school places would be unmanageable, particularly in the larger English counties (e.g., Kent, Lancashire, Hertfordshire, Surrey) with their diverse mix of urban and rural communities, range of school types and variable rates of demographic change.
Whilst all local authorities (without exception) will operate a PSS to support education planning, they will do so to varying degrees of sophistication and subject to constraints imposed by budgets, data availability, analytical expertise and local policy contexts.
Public spending in the UK has been subject to a period of constraint following the global financial crisis. A reduction in council budgets has inevitably had an impact upon school place planning activities, primarily through the loss of skilled expertise (through early-retirement, redundancy, et cetera). This has created real skills gaps in critical areas such as school place planning, often resulting in a greater dependence upon external resources and expertise. This dependency is not detrimental in itself, but it does require that an externally-delivered PSS maintains at least one internal expert analyst through which school place planning intelligence can be disseminated. A PSS is only as good as the person that is operating it. Maintaining an in-house ‘power user’ (or small team) with ownership of a PSS and responsibility for its management and application is a critical determinant of its success.
A real and continuing challenge with the development and management of school place PSS, is the availability, quality and processing of appropriate data from reliable data resources. Following a long-term dependence on the use of GP patient registration statistics for planning purposes, legal wrangling over the ownership of National Health Service (NHS) data in combination with concerns over the use of individual-level data records, has added further complexity to PSS model development. The EU’s General Data Protection Regulation (GDPR) has introduced a fundamental and important change to the UK’s data privacy regulation, which has required careful consideration and control over the future use and storage of pupil records for school place planning purposes. At a more prosaic level, the annual update to a school place PSS requires consistency of datasets, with changes to geographical boundaries, the school network and housing growth trajectories (for example) all requiring careful consideration to ensure robustness of forecasts and comparability with forecasts from previous iterations of the PSS.
Possibly the greatest challenge for a school place PSS is the degree of scrutiny to which its forecasts are subjected to. A range of stakeholders will have some level of interest in the projected growth (or decline) in pupil numbers in local communities: the DfE requires all local authorities to complete its annual SCAP return, from which localised funding is allocated; council leaders need to be sure that budgetary constraints will allow for the local authority’s statutory requirements to be met, given the pressures of demographic change and housing growth; education planning managers need to be confident that the school place pressures that they observe in their territories are reflected in the PSS forecasts; headteachers and school governing bodies are interested to know how their school’s intake and number on roll may change due to demographic and housing pressures; and housing developers will be keen to understand how their financial contributions to education services are calculated and allocated by council school place planning teams.
This diversity of interests invariably means that PSS forecasts are typically published at ‘macro’ level, i.e., for the local authority in total or for the ‘clusters’ of schools that form the local authority’s planning areas, rather than for individual schools. Macro-level forecasts provide a more robust outcome, avoiding some of the year-on-year fluctuations and small-number variability that often affects school-level forecasts. At present, it is the future impact of new housing growth that is of greatest concern to most councils, with uncertainties over the phasing, distribution and pupil yield associated with these new homes, lending itself to a ‘range’ of growth outcomes, rather than the single SCAP forecast presented to the DfE and to council stakeholders.
The national education policy context has meant that more and more schools have been removed from the direct (financial) control of local authorities, with an increasing proportion of the school estate formed of autonomous academies and free schools. This has the potential to make each council’s task of school place planning and the maintenance of an all-encompassing PSS, almost unmanageable. However, despite the fact that academies and free schools have operational and financial autonomy, most have continued to share key datasets with local authority planners. This has meant that school place PSS continue to benefit from a full suite of statistics on pupils in state education.
Whilst budgetary constraints, data availability and government policy are generic themes, each council will have its own local issues, adding complexity to the school place planning process and the ability of a PSS to support this process. These issues might include: a mix of selective and non-selective schools; schools with atypical year groups (e.g., middle schools, studio schools and infant/junior schools); substantial housing growth; a declining population; and a large number of new migrants; g. Good data management; a flexible and robust projection and scenario planning capability; fast and effective reporting capabilities; and an experienced data analyst to exploit these capabilities. All these are all essential components of a school place planning function that delivers the analytical evidence to inform asset management strategies in an increasingly dynamic education environment.