The need for better business intelligence (BI) has become almost a given in the sector. Improved competitive insights and more strategic decision making are needed more than ever now that efficiency and greater student choice are centre stage.
The Green Paper on higher education in England and the Spending Review have made it very clear that these are going to remain key areas of focus for the sector.
However, as many of us are finding, the realities of achieving more sophisticated BI capability are proving far more complex. Those of us working within the planning sphere understand the fantastic potential we have to create the foundations of a more evidence-based approach. So what’s standing in the way?
We have seen huge strides in the professionalisation of the planning and management information function. However, one of the biggest stumbling blocks in realising the full benefits of this development is the historic ‘ghettoisation’ of data. The sector’s understanding of data’s potential to help HE providers develop business management systems that will help it perform better should run, like the words in a stick of rock, right throughout our organisations. We all need high-quality insights about the wider environment in which we operate to help us make better informed decisions about our courses, products and services, and to help us pinpoint potential effectiveness and efficiency gains. Senior managers need increasingly to see it as a strategic tool and engage with its potential.
For the past year I’ve been a consultant for the Business Intelligence project being run jointly by HESA and Jisc. The first major milestone from this project is the launch of Heidi Plus, which is to old heidi what the bullet train was to the Flying Scotsman. While heidi has been a much-loved and valuable part of our data and planning system for some eight years, the need for a data and analytics tool with significantly upgraded capability is clear.
Heidi Plus will make it possible for decision makers at all levels of an organisation to more easily access, analyse, understand and act on information anytime and anywhere. The combination of more detailed data sets alongside cutting edge analytics functionality should help data professionals make the case for more sophisticated use of data as a management tool.
It will both provide prepared content and enable users to get creative to generate their own insights to inform evidence-based decision making. Dashboards and visualisations have been developed to help answer the common business questions we in provider organisations face, but it will also make it possible to generate bespoke analyses and visualisations based on HESA data sets, and other sector data, to answer our own individual priority business questions. Jisc will use its Heidi Lab project to experiment with data-driven insights and features that may be migrated into Heidi Plus.
The new service differs in how users interact with data and is more flexible, with extra features including visualisations, case studies, narrative, examples of insights gained and actions taken. It aims to open up access to closed data sets provide better access and application of data. This should help us react faster and more intelligently to increasing resource constraints and assist in compliance with existing regulation, such as OFFA fair access.
As we all work through the changes needed to keep up with the demands of delivering more efficiency and more student-centric service delivery, we need to be focussed on maximising the value of our management information and raising awareness of this powerful asset. We now have big data, but with big data comes big responsibility to make sure we generate insight and not simply more data.
Thank you for a very interesting piece showing us that HE is not just about idealised teaching and research. It is indeed about the ‘mundane’ task of using the data at our disposal. i found your last sentence telling of the opportunities and challenges facing us. indeed, ‘We now have big data, but with big data comes big responsibility to make sure we generate insight and not simply more data.’ Speaking from the perspective of the lecturer, it seems that, in the strive to know more about everything we do, we are creating more and more data. We are caught in one of the most frequent pitfalls of research and one that i guard my PhD students off: more data does not mean more knowledge, especially if you do not have the time and a plan of how to analyse it and a clear idea of what you want to get out of it. It seems to me that, paradoxically, the HE sector is flooded with data but lacking a clear sense of what to do with it. the tendency is to collect it for the purpose of accounting and ticking the box. Moreover, data collected in one place does not seem to be coherently used in another and the communication of findings and the implementation of recommendations gets lost in the myriad of committees and sub-committees, various reports, new policies, old policies and so on. Rather than a sector, HE is sectorial. This brings me to reflect on what the responsibility you talk about might actually be. Could it be the technical and instrumental responsibility of using the right analytical procedures? or the ethical responsibility of ensuring that the data analysis is not biased? or maybe a civic responsibility to share with all members of the institution the way the evidence is gathered, analysed and collected? In regard to ‘more data’, i would like the sector to realise that there is a difference between collecting more of the ‘same’ data and collecting different types of data. This shift implies to think more carefully about the nature of the product and services the HE sector provides and the data which are required to show its impact. In this regard, we should contemplate taking the challenge of collecting, reporting and utilising data on the intangible assets and in particular data on the intellectual capital, both forming a substantial part of what a university produces. Finally, a word of warning: schools have been asked to provide evidence-based practice for years and we still need to work out how to do it. This is to say that the main challenge ahead of us is to think differently about a) what data we have; b) what data we need; and c) how to use them. May 2016 being us the wisdom we need.