Analyzing analytics

The ever-changing role of analytics in higher education
Meghan Turjanica, 
Student Success Solutions Program Manager, 

Can you identify some of the major changes that are happening in the field of analytics?
First is the ease of analytics. What we’re able to do now with cloud technology has changed our ability to crunch data. Things like machine learning and artificial intelligence are possible because of the amount of computational power we can throw at data sets. Augmented analytics—for both data preparation and guided data analysis—is a big trend. Now a business user, a citizen data scientist, is able to leverage advanced analytic capabilities with greater ease. They can supplement existing data with new sources or even analyze data without having to know which algorithm will perform the best. This means someone who wants to go in and ask questions of the data can get answers without first needing a doctoral degree.

How are these improvements advancing higher ed?
These advances have great potential to move higher education forward, but they are not yet being harnessed very well across higher education.

Some early adopters are leveraging the tools to start answering the tough questions such as: Whom should we be recruiting? How much aid should we be giving? What about facilities management? Are we offering the right programs? Are we in a financial position to build a new residence hall? These early adopters have been drilling into the information available to find ways to support the institutional mission with the analysis they’ve done.

How can colleges leverage innovations in analytics?
Higher ed could be using this data in even more amazing ways. Imagine being able to take predictive information about a student, and from there, to prescriptively decide how frequently and what types of interventions are going to improve student outcomes. That’s powerful. Another example is program optimization. For leaders at institutions who are trying to do this on their own, it takes them months to understand the financial impact of their programs. This kind of review could be easily happening annually with the new advances in analytics—a more repeatable and set-it-and-forget-it model.

What solutions does Jenzabar provide that could help schools achieve their best results?
Our retention product leverages predictive analytics to assess which students are at risk even before they get on campus. That information can be leveraged to create intervention plans based on the risk category. Our clients are able to get in front of students before they’re at a point of crisis, which is usually midterm and too late to save the student. That’s really powerful.

We also have a Jenzabar cloud-based analytics solution to collect data and store it securely for analysis, and to apply best practices to areas such as financial health, program contribution or optimization, student success, and enrollment. The best practices element is incredibly important because it helps institutions get beyond the initial surface level of analysis to the deeper questions that provide more meaningful answers to help shape strategy.

If institutions want to be data-informed in culture and decision-making, we need to get people adopting analytics—but that’s not always easy. Jenzabar provides training and education to empower users to become citizen data scientists. And that’s the only way we can change culture and make it truly data-informed. We’ve got to get buy-in on all levels.

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