Uncertainty around funding has in recent years spurred on the use of advanced data analytics in higher education, especially for financial planning. But the sector is still lagging behind fields like healthcare, retail and government administration in really making data count for overall performance. Now is the time to catch up.
A recent survey by University Business and CACI revealed that 61% of readers say data analytics software has become more important for them after the political changes to university funding in recent years.
Data analytics, however, is by many still seen merely as a tool for financial planning, and not as an integral part of a university’s general strategy. Yet if higher education institutions in the UK are to continue to prosper, they need to adopt a data-led strategy for all aspects of performance.
Universities from York to Surrey and Bath to Cardiff have already started to incorporate data analytics into the broader aspects of their strategy.
Along with many other HE institutions, these organisations have long used data analytics for planning student numbers and, in extension, funding.
However, in recent times they have also started using data analytics to inform decisions across their institution, such as marketing campaigns and investments in new facilities.
In fact, University Business and CACI’s research revealed that as many as 56% of its surveyed readers work for universities that now use business intelligence or data analytics software to inform broader strategic plans, for instance, for developing facilities, student recruitment or course planning.
In the coming years, this broad approach to using data analytics across an organisation will be one of the key elements for successful HE institutions, regardless of future funding schemes.
Many of the challenges for data-driven decision-making are not caused by a lack of data, but by having too much data
Investing in the right place
An example to show how data analytics can be used in such a broad strategy is if a university is planning to expand because of growing student numbers, but is unsure as to which department or faculty it should construct new facilities for.
Before deciding on the investment, the university can employ predictive data analyses such as ‘SAP Predictive Analytics’ – using student and financing information it already has – to calculate which faculty has the greatest potential for increasing its student numbers. These calculations will also, crucially, show how much of an increase in income the uplift in student numbers at the different faculties will mean.
Then, along with the faculty expansion, the university can launch a data-led marketing campaign targeting the demographics of people most likely to apply for courses at the new faculty, even taking into account the mix of applications between domestic and international students. Such a joined-up approach to expansion will maximise the benefits from any investment in new resources.
Coupling data and demographic analyses like this can even be used to inform the widening participation agenda, while predictive analysis can help drive student attainment to higher levels.
The data is already there
Universities already sit on a huge quantity of data that can be used for data-led strategies. They only need the capabilities from a data consultancy like CACI to make use of the data and analyse it in a way that it leads to tangible recommendations for decision-making.
Indeed, many of the challenges for data-driven decision-making are not caused by a lack of data, but by having too much data, leading to confusing masses of information that are unusable. Attaining the capabilities to make sense of the expansive data is perhaps the most important investment of all for a university looking to grow.
It is heartening to see that data analytics has become so important for University Business readers in recent years. And one thing is sure: it will be even more important in the years to follow.