Institutional Research and IT are working together—here’s what that means for campus analytics


Institutional Research and IT are working together—here’s what that means for campus analytics

Last week, EAB’s Education Data Hub team attended this year’s Association of Institutional Research (AIR) Forum—virtually, of course. Institutional Research (IR) professionals gathered online from all corners of the country for three days of learning and collaboration, and to discuss how higher education will need to adapt in the years ahead. From presenters and attendees alike, I noted a key shift taking place that inspires optimism for analytics programs that have often suffered from poor outcomes: the strengthening of the IT/IR relationship on campus.

Recommitting to campus collaboration

Historically, different campus functions have taken different approaches to data—from using different tools and processes to caring about different outcomes entirely:

  • IR has focused on data integrity for compliance and reporting
  • Business officers have invested in improved technology suites to drive business process digitization and improvements
  • IT has needed to speed up new technology projects and scale data access while simultaneously strengthening data security

These efforts are all part of a unified set of goals: to empower data-informed leadership to impact broader institutional efforts around student success, sustainability, and equity. Yet these different focuses and separate budgets mean that, for a long time, leaders have worked—and invested—at cross purposes.

Then last year, the professional associations for IR (AIR), IT (Educause), and Chief Business Officers (NACUBO) in higher education released a joint statement to promote shared investments in data and analytics initiatives, providing a first step for institutions to build a shared vision for progress. In March, at the Indiana regional AIR conference, we heard leaders lamenting the ongoing struggles around data management. But in the sessions and chatrooms of AIR Virtual, participants pointed to their relationships with IT as key factors in improving data access and accelerating progress towards enterprise data goals.

IR and IT are approaching the full data lifecycle, together

Both IT and IR leaders have unique perspectives of their institutions: their teams have relationships in most corners of campus. Where IT professionals are helping business leaders and academic staff set up technologies to transform their workflows, their IR counterparts are working with those same stakeholders to identify opportunities for analytics that drive institutional effectiveness—accounting for both ends of the data lifecycle.


But it’s at the heart of the data lifecycle that the two groups must come together to collaborate, especially as they look to improve analytics efforts on campus. In the middle of the data lifecycle, where data are aggregated from the various systems in use, technical and business experts must come together to define the data appropriately for campus-wide use.

At most institutions, neither IR nor IT will have the full perspective (or the bandwidth) to build and maintain an appropriate enterprise framework. IT holds the keys to the systems and their complexity, and IR works hand-in-hand with campus leaders to build the models for exploring opportunities for improvement. Working together, these two groups can generate significant progress by creating governed, enterprise-wide data repositories that bridge technical and business data needs—reducing workloads and improving data usability for all of campus.

A new way forward

This year’s AIR Forum presenters demonstrated that analytics in higher education is beginning to thrive—from predictive models aimed at reducing equity gaps, through to geolocation mapping to fast-track contact tracing on a reopening campus. And while the outcomes themselves are impressive, for those still looking to improve, it’s important to recognize how these institutions are making progress: through collaborative IR/IT relationships that treat data as an asset to be cared for communally.


Translate your data aspirations into action steps

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