You know what it’s like when a new gadget or app comes onto the market and starts really taking off? We all start hearing about what it is and what it can do for us, especially as the early adopters can’t stop waxing lyrical about its apparent greatness. Then, slowly but surely, others follow suit, and whilst some also start using it to the max, there are also those who never really quite get what the fuss was all about and who end up only ever using it sporadically, if at all.
Labour Market Insight (LMI) is a little bit like this. All universities will be familiar with it at some level. Some are already using it in amazing ways and can’t quite seem to understand how they managed without it. Then there are those that perhaps use a smattering of it here and there, but really don’t see it as much of a big deal. And still others who, after hearing what other institutions are doing with it, invest in it, but never quite get its potential to transform a whole array of things in the life of their university.
When I say a whole array of transformational things, I really do mean it. Across our customer base, in the UK, US, Canada and Australia, universities are using LMI to inform their student employability, portfolio planning, course design, degree apprenticeships, work placements, market intelligence, horizon scanning, understanding of skills demand, marketing and outreach, schools engagement, widening participation, contextualising research, knowledge exchange, the civic agenda, and much, much more. That’s quite an extensive list, and for those universities which have LMI on their radar, but haven’t really seen its potential yet, a question might arise: how exactly can LMI, which at the end of the day is just a bunch of numbers, be used in such a wide variety of university activities to affect positive change?
In a very real sense, it all depends on whether a university is using LMI “because we need data”, or whether it is using it to answer specific questions. If the former, the university is unlikely to get much out of it. If the latter, it is far more likely to see a return.
For instance, the university that invests in LMI to improve its employability, but without actually defining what this really means, is unlikely to realise the full potential of the data. Whereas a portfolio planning team that seeks to find out how well its current portfolio is aligned to demand for graduate labour in their area, will be able to use LMI to map the portfolio to the labour market. This will highlight areas of misalignment, as well as potential opportunities to create new programmes to meet market demand.
A university that invests in LMI in the hope that it can help with its widening participation strategy, but without specific questions to answer, is unlikely to get much from it. The university that seeks to answer the following question – how can we show the cohort we are targeting that a degree with us can help their career prospects? – can use the LMI to demonstrate to that cohort the link between its courses and possible careers in their town or city. This promotes the message that enrolling in the university can improve their career prospects and salary expectations where they live.
The key to getting the most out of LMI is therefore all about bringing it down from the somewhat nebulous – “to help with our employability, our marketing, our employer engagement” – to very specific questions. However, this can lead to another error, which is that after having answered the particular question it was brought in to answer, the data gets – as it were – packed back into the box, never to see the light of day again, unless that specific question needs answering next year.
The really successful users of LMI, however, are those who not only see its use for answering specific questions in one department, but who then look to bring in colleagues from other departments to see if the data might be able to answer the questions they are grappling with as well. For example, one institution we are working with, which invested in LMI to answer questions their CPD and apprenticeships team had, soon realised the potential the data gave for answering questions in their planning and employability teams. Months after making that initial investment, the data is being rolled out across the university, where it is being embedded in multiple functions to answer multiple questions.
How can your university use LMI to bring positive transformation? By using it to answer very specific questions that only data can solve; by looking across your institution to see what other teams could benefit from using it; and, finally, by embedding it across the university to help answer the many big questions and themes that your institution is currently grappling with.