Whilst the AUDE annual report looks at universities as a whole, there has been a view within the sector that individual institutions need to compare themselves against a more appropriate set of institutions which share a number of key characteristics.
There have been a number of groupings over the years which could have formed the basis for peer groups; these groups have not included all institutions (i.e. not all institutions found themselves in one of these groupings). There was concern that the groupings may not enable appropriate comparison of key performance indicators given that estates may not have been central to the identification of members to these groups.
Work had been undertaken to review the performance of institutions in Wales and Scotland and this had generated a high level methodology to group institutions into different classifications based on the size of the institution (measured by academic income) and the amount of income that the institution generated from research (% research). The rationale behind reviewing the research percentage being the different demand for space that a more research intensive institution requires over one which is more teaching focused.
The research also examined the TRAC groupings as potential peer groups, and this has also informed some of the further analysis. There is similar work being undertaken in other HE groups from funding councils to JISC to understand various drivers in different parts of the sector.
The university sector is not a homogenous set of institutions doing the same work in the same environment. This work sets out some of the distinctions between institutions and attempts to group institutions based on some simple measures to help understand where there are similarities.
The aim of this work is to enable institutions to better compare themselves with other more broadly similar institutions so that best practice can be identified and developed.
What we have found is that whilst there are differences (for example in space per FTE, and in income per m2) there are also broad similarities (for example in the percentage of income expended on total property costs).
This work is intended to be the basis for further analysis using this segmentation to generate key performance indicators for the benefit of the sector as a whole.
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