Nearly two thirds of universities in the US reported in June 2012 that analytics (or business intelligence*) was a major priority for their institution, or some departments within their institution. And 84% reported that it was more important to them than two years ago. As a single fact, that doesn’t seem significant – what’s really useful to see from the report is the areas of the universities that are using analytics. Beyond the stalwart of finance and budgeting, the main focus appears to be on using analytics for student-centric processes – enrolments, student progress, instructional management. And relatively lower use of analytics in areas such as human resources, facilities, and staff management.
One of the key findings of the report was that whilst analytics is widely viewed as important, data use at most institutions is still limited to reporting. They also found that programs were most successful when they involved partnership across teams – IT, functional leaders and organisational leaders. They also recommended that institutions should focus their investments on expertise, process, and policies before acquiring new tools or collecting additional data. Although, I think there is a real danger – observed across many analytics projects – of analysis paralysis, resulting in an ever-expanding project scope, and the resulting delays in project deliverables.
Are analytics tools too expensive?
The Executive Summary at the front of the report highlights two key questions:
- Is data mainly collected to enable reporting, rather than to address strategic organisational issues?
- Is cost a major barrier to widespread use of analytics?
In fact, ‘affordability’ was the largest concern about the growing use of analytics in Higher Education (Fig 5, page 13) As the Executive Summary says on page 3:
One of the major barriers to analytics in higher education is cost. Many institutions view analytics as an expensive endeavour rather than as an investment. Much of the concern around affordability centres on the perceived need for expensive tools or data collection methods. What is needed most, however, is investment in analytics professionals who can contribute to the entire process, from defining the key questions to developing data models to designing and delivering alerts, dashboards, recommendations, and reports.
I’ve heard similar views expressed – but in a growing mindset of ‘self service BI’, where the end user is often going to be doing their own data analysis in the tools they are already familiar with – like Excel – I think the need for additional BI tools for everybody is fading. Given that in most Australian universities, all of the staff are already licensed for the common-place analytics tools like Excel, then cost should hopefully not be a barrier to widespread use, and perhaps the need is more of training to help users interpret standard sets of information, and how to analyse it together with their own local datasets.
Which areas of universities are using analytics?
The chart below comes from the 2012 ECAR Study of Analytics in Higher Education (the full infographic is a 13MB PDF file here). The area labelled ‘student progress’ also includes student retention, which I think is a key scenario for analytics with students.
Given the report’s view that a lot of the use of BI/analytics was for ‘reporting’ rather than true analytics, perhaps there’s not a huge surprise here – but it’s a timely reminder that reporting data is exploiting a small part of the potential of a analytics/business intelligence system.
If you, or colleagues, are involved in discussions or projects around business intelligence or analytics, then I’d recommend the full report, as it’s written in a very approachable way, with many useful insights. You can view the full 2012 ECAR Study of "Analytics in Higher Education" on the EDUCAUSE website
I think there appears to be a shift in language that’s happened here. What’s called ‘analytics’ in this report has traditionally been called ‘business intelligence’ more widely. I know that the phrase ‘learning analytics’ has become the norm for student-centric BI, but I wonder if the name change we see in this report has come because of the word ‘business’ in ‘business intelligence’ – and the perceived need to ensure that people don’t apply the label ‘business’ to education (echoed by one of the response options under ‘concerns’ about the use of analytics which was "Another means of running higher education like a business")