Across the UK’s higher education sector, competition to attract and retain students is fierce. To improve their competitiveness against their competitors and develop their portfolios to ensure student success in the labour market, universities are increasingly engaging with research and data to inform their decision-making and support the development of their degree portfolios and wider student offer. Our experience shows a growing number of requests from higher education institutions for primary research to support portfolio planning, often seeking information from current or prospective students and/or employers to answer these questions. While this view is indeed an important consideration, we argue that the existing data landscape provides universities with the vast majority of information needed for informed portfolio planning – with little primary research needed. By taking a ‘data re-sight’ approach, universities can themselves (or with expert guidance) mine existing data to take a data-driven, future-facing approach to portfolio strategy.
In order to undertake this type of informed and data-driven approach to portfolio planning, universities must blend internal knowledge of their strengths and weaknesses, university plans and overall capabilities with population projections, performance of the existing portfolio and graduate outcomes, and labour market projections to develop a comprehensive view of their current strengths and weaknesses vs. future labour market needs. This can be used to redevelop their portfolio and wider student offer to ensure the portfolio and student offer are designed to meet future skills needs and market gaps.
Whilst complex and often disparate, much of this data already exists within the public domain, with a range of potential sources of information that can be used to support the evaluation of each of these areas:
- Population Projections: which demonstrate how the population is expected to change and, from this, the volumes completing secondary education and therefore eligible to enter tertiary education over the coming years – as available from the Office of National Statistics, Department for Education or other Higher Education bodies like Universities UK, and from many local authorities who produce projections for the total population and for pupil/student demand.
- Portfolio Performance: from overall and subject-level league tables (like the Complete University Guide and the Guardian, as well as TEF ratings), course-based student satisfaction and outcomes from the National Student Survey (NSS), and data on graduate outcomes from the Destination of Leavers from Higher Education (DLHE and Longitudinal DLHE), going forward from the new Graduate Outcomes study, and from the new LEO data.
- Labour Market Projections: national-level projections have been produced by UKCES to 2024 (‘Working Futures’) and Nesta to 2030 (‘The Future of Skills’), whilst local authorities also create local-level projections that are worth consideration, e.g. Greater London Authority’s 2017 ‘Long Term Labour Market Projections’.
Combining data from these sources offers universities an indication of how they could leverage portfolio strengths to support future growth and/or address portfolio weaknesses where labour market projections show a positive picture. The table below is an example from our recent work, which compared sectors with strong labour market projections against existing portfolio performance (based on subject league tables and NSS results for all courses in that subject area) in order to create a SWOT analysis of the university’s portfolio to support future planning.
In this instance, the ‘re-sight’ exercise offered a clear picture of where the university’s portfolio was strong against its competitors and in the context of future labour market needs, giving a steer on where the portfolio could be leveraged to ensure growth and positive student outcomes. Areas of opportunity were identified based on subject areas with a strong outlook in the labour market, but where current performance was average and would need bolstering (especially in relation to student satisfaction and outcomes) in order to be competitive. Weak-performing courses were referenced as those where substantial investment would be needed to existing courses to make them truly competitive within the competitive landscape, despite their labour market strengths.
Using this method, primary research should be designed to build on these findings, mindfully supplementing existing data with additional insights. For example, recent data re-sight projects have included primary research components with stakeholder interviews to understand the internal perspective on the portfolio’s strengths, weaknesses and areas of opportunity; focus groups with students or local employers to develop their perspectives on what courses need to provide in order to better ensure competitive graduates that are workforce-ready; and desk research into the competitor landscape to assess portfolio gaps against what others offer.
Taking a data re-sight approach is a cost- and time-efficient means for universities to gather the necessary information needed to make informed choices when university portfolio planning or defining their portfolio strategy, supplementing this only where needed with primary research. By triangulating existing, publicly available information and taking into account future forecasts, this approach ensures focussed, clear results for universities to take forward as they work toward aligning their portfolio to meet future labour market and skills needs.