Universities do not adequately understand what drives students to leave their courses, despite increased pressure to improve student retention, research has shown.
Student churn rate is the number one challenge affecting university performance, according to 55% of senior university managers surveyed by MHR Analytics.
To shed light on the underlying causes of student attrition, MHR, the data analytics provider, asked students and university managers why students drop out of university. The findings uncovered conflicting opinions, showing that:
- 67% of students say they leave because of financial problems, while just 28% of respondents in senior management roles in universities agree
- 52% of students believe mental or physical health problems are a major drop out factor, yet only 12% university managers say the same
- Only 29% of students believe student churn is due to sub-standard student support from the university, compared with 61% of professionals citing this as the main cause
- More than half (54%) of university managers think conflicting work and family commitments cause attrition, yet just 16% of students agree
“Gross attrition within each budgeting cycle is a costly and growing challenge for universities,” said Nick Felton, MHR Analytics’ Senior Vice President. “But the vast data sets available to universities are key to unlocking answers to this problem – provided those data sets are managed and analysed effectively.”
“Data analytics provides evidence and visibility of a student’s learning experience from their initial application to their final exam, enabling targeted intervention before issues arise, increasing student retention, and maximising the potential of great results.”
“When we asked university managers about the business insights most important to them, 42% said student drop-out prevention data was a priority, highlighting the pressure universities are under to address attrition.”
A data analytics method of managing attrition allows institutions to see a comprehensive view of each student including data visualisations which identify fact-based attrition patterns and who might be at risk. Once identified, individual student issues potentially leading to churn can be addressed through additional academic counselling, health services or financial support, as well as tracking of progress and follow-ups.
Student attrition data is just one example of how analytics can be used as a strategic tool to meet business challenges and achieve future success – but the potential of data analytics in higher education is much bigger. MHR Analytics works with a range of higher education institutions who are harnessing analytics in different ways to transform their operations and compete, for example at Loughborough University, which is using Financial Workforce Planning to forecast up to ten years in the future and save around 30% in operational costs and cut wasted administration hours.
The finance team at another UK institution is using IBM Planning Analytics to visualise, test and predict various scenarios and revenues, and accurately break down data on student retention rates, course profitability and the impact of curriculum changes without the reliance on traditional spreadsheets.
Competing in an unpredictable economy is another key issue for universities, with more than half (52%) of respondents in the MHR Analytics survey saying their institution faced a challenge from non-EU student admissions and tuition fee income.
“It is not easy to deliver outstanding education while cutting costs and adapting to constant changes in income streams, policy and admissions,” added Felton. “Data visualisations showing accurate, real-time business insights give education leaders the confidence to address specific challenges.”
“Almost half (47%) of the senior university employees we polled said their university still plans for the future by using excel spreadsheets, which are known to be time-consuming and prone to costly human error.”
“Spreadsheets will not serve institutions in this decade where agility and the ability to plan for complex potential scenarios is essential. Instead, analytics technology is a tool that universities can adopt now, to increase their competitiveness by taking full advantage of their data.”
MHR Analytics has released The Complete University Guide to Thriving With Analytics, which features case studies of universities that have implemented data analytics successfully and step-by-step guides to addressing key business issues within higher education.
MHR Analytics commissioned Censuswide to survey 200 respondents in senior management roles in universities, as well as 501 university students, in November 2019.