Objective: Identifying Patterns in Pupil Withdrawal
Research question: Is there a correlation or causal relationship between school pupil withdrawals and school transport pickup points, or the distance travelled?
Abstract: The school under research is an Independent Boarding and Day school of 820 pupils who are aged between 11-18, located in Gloucestershire. They operate in a very busy market that has not only five competing similar schools within the local area, but also several accomplished state schools and other colleges. In this increasingly competitive marketplace, we are observing an increasing trend in those leaving post GCSEs, and heightened competitiveness in the day pupil market.
Further Info
The organisation collects and holds vast volumes of data, both financial and non-financial, in various sizes and formats; however, this is highly fragmented and has made the implementation of a robust data management framework extremely difficult – this is extremely common, and traditionally there has always been a lack of joined-up interaction between key business units. For this organisation, this includes finance, admissions, alumni, and academic staff – none of which are effectively coordinated.
They have both internal (Admissions, social media, financial) and external (Independent Schools Council, league tables) data sources at their disposal. Financial reports and datasets from the Finance Office can help identify, for example, a pupil’s ‘lifetime value’, which in turn, can identify the profit generated from a successful retention drive. However, most CLV calculations do not factor in the cost of acquisition. It is clear from the previous section and figure 1, that whilst there are vast amounts of stored data, some of this is not linked and, in some cases, does not exist.