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ED&IS Interview: Christine L. Borgman discusses new study, “Data blind: Universities lag in capturing and exploiting data"

By John McDonald
Christine L. Borgman

New research published in Science shines a bright light on the ways in which universities are data rich and data poor — and sometimes intentionally data blind

Christine L. Borgman, distinguished research professor at the UCLA School of Education & Information Studies, and Amy Brand, director and publisher of the MIT Press, have conducted a new study exploring the complex challenges universities face in the capture and use of data. “Data blind: Universities lag in capturing and exploiting data,” published in the December 23, 2022 issue of the journal Science, finds a pervasive lack of data infrastructure and strategy in North American higher education, and argues that most universities lag behind industry, business and government when it comes to leveraging data for strategic decision-making and planning.

“They are struggling to capture and exploit the true value of their data resources and reluctant to initiate the conversations necessary to build consensus for data governance,” says Professor Borgman.

We talk with Professor Borgman here about the study’s findings and implications. The full article is available free on her website and in Science.

UCLA ED&ISIn your view, what's most important about this research? 

Christine L. Borgman: The goal of our study of university leaders was to identify both pain points and innovative solutions to data-informed decision-making. We identified individual perspectives on opportunities and challenges they face in exploiting their data. We found few data-informed planning successes and a greater void of infra­structure thinking than we expected. 

Our findings offer several paths forward to invest in infrastructure thinking, governance, and innovative solutions to data-informed decision-making in universities.

Ed&ISWhat do you hope the study helps people to understand?

Borgman: Research universities are drowning in administrative and research data. They need better data, and better ways to exploit those data for strategic decision making, rather than more data, per se.  Failures to invest in data management and data governance are costing universities money and other forms of value – these gaps are an invisible tax on an organization’s efficiency.

Improving data exploitation in universities is more a matter of governance and policy than of technology per se. Our findings suggest the need for more investment in interoperability of systems and more coordination across organizational units.

Investing in siloed corporate solutions within individual operating units can lead to duplication of systems and effort, barriers to interoperability across the university, and can constrain an institution’s ability to take an infrastructure perspective across all aspects of teaching, learning, research, and operations. 

Ed &ISWhat do you hope the study will help to make happen? 

Borgman: We hope that university administrators and faculty will work together to improve the governance of data resources and exploit these resources in strategic and ethical ways.  Administrators, faculty, researchers, students, and other university stakeholders all can benefit from more data-informed decision making. Better governance and coordination can reduce various administrative burdens, reduce duplication of effort, and yield more useful and timely information. 

Many benefits can be gained by training staff in data skills, by employing more of the data science professionals now graduating from research universities, by pursuing simple innovations identified by other universities, and examining data governance and policy related to the use of data in decision making. We encourage university leaders to embrace more objec­tive and transparent data-informed approaches to decision making.

A summary article exploring the study’s findings is available on the UCLA newsroom website at https://newsroom.ucla.edu/releases/universities-struggle-to-leverage-data

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