The higher education sector faces multiple challenges. On the one hand, universities have burdening financial pressures due to a decrease in central funding, a reduction in student applications and stronger global competition.
On top of this, Brexit is creating uncertainty in the market. The Russell Group recently demanded greater clarity from the Government over its Brexit plans, which it says have left “a significant degree of uncertainty … concerning EU nationals’ rights and the process for acquiring them after the UK leaves the EU.”
Plus, recent restructuring within research councils brings into question the availability of research funding at existing levels. The changes will potentially make it harder to retain key staff and could deter lucrative international students from coming to the UK to study.
In this competitive environment, unless universities can improve student outcomes and research productivity then their financial sustainability will be put at risk. However, there is an opportunity. By deep analysis of all available data, universities can better understand their own business performance and the market they compete in.
The key to managing university performance better is contained within the incredible amount of data both generated and stored by universities and external bodies. There is more information available than can be managed or mined by conventional process and reporting methods and only sophisticated and structured data management and analytics systems can extract the insights that provide management and staff with what they need to plan and optimise operational, financial, student and research performance.
By implementing a data analytics system, universities can benefit from accurate and timely management data for planning and real-time management of i.e. student marketing, enrollment, retention, financial management and research grant applications. Intuitive and context sensitive reports and outputs can be simplified from masses of data from many sources. Managers and staff can make better decisions by being informed by descriptive, diagnostic, predictive and prescriptive analytics. And, coherent and robust plans will provide clarity about the most important priorities – updated with real-time performance against plan and remedial actions for plan deviations (using machine learning).
Then, and only then can universities identify, recruit and retain the best students, teaching and research staff – attracting exciting funded research projects.
5 to 7% improvement in performance targets and KPIs can be expected from an integrated university-wide deployment of data & analytics, creating many £M’s in additional revenues and savings. Outcomes in student and research performance can be expected at similar levels positively impacting the university standing on UK and World rankings.
So, by universities putting their education first, it will allow them to understand their business environment better to put the needs of their students first.