How to Boost Your University’s Data Literacy

Data literacy has become a must-have for university staff, but it’s often hard to build buy in and explain its benefits.

Data and technology now permeate everything we do, and for good reason.

Big data can highlight patterns in student behaviors, identify areas for improvement, and inform long-term strategic planning for your university.

However, it’s hard to make the most of big data if your university staff don’t understand how it works, its big benefits, and its limitations.

Why data literacy is so important

Alex Chisolm, Head of Analytics at QS, recently spoke at our 2019 EduData Summit about the pressing need for universities to understand, manipulate, and communicate data.

“Data should be a second language, there’s no ‘I’m not a data person’ anymore. Data touches everything now and data-driven decision making is more important than ever.”

In the 2018 QS report, The Global Skills Gap in the 21st Century, we found that data skills are highly valued with 89% of employers ranking data analysis as important and 83% of employers ranking technical skills as important.

Despite these findings, only 69% of employers said they were satisfied with their graduates’ data analysis skills and 78% were satisfied with their technical skills.

This highlights a general dearth of data skills and data literacy, which impacts both graduates and a range of seniority levels and workplaces.

It’s an essential knowledge base that often gets relegated into the too-hard basket, pawned off to IT teams whilst general university staff miss the opportunities and insights that data provides.

How to encourage data literacy and development

To nurture a strong, widespread data literacy and introduce data-driven development at your university, there’s several steps you can take.

Establish a centralized group that looks after the collection and analysis of data across your university and ensure that each department has a representative who continually feeds the group data.

This central team will be the owners of a common data lake for all data at the university. This normalizes the use of data in everyday planning and consultation, whilst also increasing the insights they could glean.

By creating a central group and emphasizing the data responsibility that each department holds, university staff will be able to buy in to the importance of big data and data analysis without having to dramatically upskill.

Data literacy is about your university staff understanding the importance of data, how it works, and the benefits it could bring, not about being some Mark Zuckerberg-esque IT whiz.

The use of data in higher education is quickly gaining traction as more and more universities adopt data-driven decision-making.

Discover the latest data in education trends and how technology is shaping the higher education sector at our 2020 EduData Summit at the United Nations in New York.


About the Author:

As the B2B Content Marketing Manager, Sarah Linney is responsible for communicating the insights, research, and market analysis that have positioned QS as a thought leader in the higher education sector. After completing a Communications-Journalism degree at Charles Sturt University in Australia, Sarah worked in radio news and B2B print publishing before joining the content marketing sector. While working at a content marketing agency, Sarah was transferred to their New York office. She then led content marketing efforts at two tech startups in New York as a Content Manager before deciding to make the move to the UK and QS. 

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