The Institutional Researcher: The Unsung Hero on Campus
Tell me if this sounds familiar:
A campus staff or faculty member heads to a conference and hears a great idea. Once they return to campus, they want to quickly combine data gathered from a campus-based survey to create a series of visualizations in some form of dashboard. After determining who owns the necessary data, they realize it needs to be extracted. The data is likely to come in various formats — perhaps some in Excel, some in SPSS, and some in a campus-wide data warehouse. After enrolling the help of Institutional Research to clean the data, the researcher will quality-check the holistic data set to make sure that all merges were done appropriately and complete individual records for students actually exist. Then, the new, merged data file is loaded into a business intelligence product to create visualizations and eventually a dashboard. The dashboard will need to be manually updated through the same process every time the data changes.
I know, I’m exhausted just thinking about it, too. And that was all for a single request.
Now, multiply the desires of this one faculty or staff member by the total number of campus employees and you can begin to envision the pain points that institutional researchers experience. Outside of providing information to stakeholders across campus in a timely manner, each day poses additional hurdles for institutional researchers — changing federal requirements for IPEDS to new regional and disciplinary accreditation standards and data expectations. In fact, members of the campus community typically don’t understand the role institutional research serves, and so they ask for the impossible. In some cases, they even fail to ask IR for help.
For dedicated researchers and analysts, there is no question that data exists across campus. The struggle is figuring out what lives where. While much of an institution’s data houses itself in the student information system, there is no telling what has been collected in different offices. Having data spread across campus in separate warehouses is difficult, but eliminating these silos can be a challenge. Some of them have been created accidentally; others stand strong for political reasons. Collecting, formatting, combining, and parsing the data — often through manual processes — presents opportunities for error at every turn. And this doesn’t even account for the amount of time it takes to collect the data.
When the IR office monitors or houses all of the data on a campus, does this mean many small silos are replaced by one giant silo? Not necessarily. But because the risk is there, the key is to democratize access. Every stakeholder should get access to the data silo; only then will the larger campus community be able to make use of it. All campus data should live in one place, but not just one person or office should understand the database or be able to query it for answers. A campus should move away from a disjointed approach to data management and instead adopt a holistic, integrated approach to data and analytics.
But beyond these general data pain points, what are some of the specific hurdles institutional researchers are expected to jump as part of their daily routine?
Centralizing the data
Today, a campus likely needs separate tools to explore their data, monitor information, assess it in a multitude of ways, and disseminate results to internal or external constituencies through the creation of dashboards or raw data exports. Most institutional researchers have experienced the frustration of finding out that a sought-after data point exists on the desktop of a random staff member in a random office. Designing a system that helps integrate data means first figuring out where all the data points live. By utilizing a tool that captures the campus’ data ecosystem in a singular location, you can explore, monitor, assess, and disseminate it without bouncing back and forth between various point-solutions. A well-designed system offers efficiency — in terms of cost, data utilization, and time. And these efficiencies allow for staff, faculty, and other stakeholders to meaningfully engage with the data.
Assembling the information
If institutional researchers wish to have all the data living in one place, they’ll need to play a role in bringing it together. This means successfully merging together data from various data sets. SIS data, assessment data, and even random survey data from a faculty member need to come together for a holistic view of students and campus. A system that seeks to minimize the manual nature of merging data can give staff time back to actually help the campus community use data.
Sharing the data
To prevent IR from becoming little more than a locked data warehouse, your staff must work to determine how to make information accessible to the larger audience. After all, if the data is brought together but not used, an entirely different type of inefficiency will occur. Systems that help create visualizations and dashboards that can be shared with multiple users provide access. They also allow for different members of the campus community to begin thinking about questions they wish to investigate. An effective solution will house data in a singular location, where it can be updated dynamically without a repeated heavy manual lift by institutional research or institutional technology. In sum, the data should be available where and when you need it.
Prioritizing requests
The IR office is often responsible for a lot of reports required by accrediting bodies and other external stakeholders. Beyond this, campus community members routinely make specific requests for information and analyses. Determining how to best prioritize projects, minimize unnecessary duplication of efforts, and ensure requesters receive complete and proper information is time-consuming. For example, how does an office prioritize IPEDS reporting, Board Report requests, and a Vice President for Enrollment Management’s urgent request for data on freshman cohorts from the last two years — especially when each will require manual work and analysis? Tools that facilitate the creation of shareable, editable reports and visualizations lessen stressful multitasking and increase the ability to respond to more ad hoc requests.
Being more responsive
Once an initial data request is met, it cannot simply be marked as closed. Many requests from campus of institutional researchers can be viewed as initial questions. As results and data are passed back and forth, new questions will emerge, or additional layers will be needed. Systems that allow users to filter information with a simple click of a button help expedite the ability of institutional researchers to respond to the needs of campus. After all, why tell a constituent it will take you a few days to get back to them when you could instead respond in the moment?
Training users
Part of why institutional researchers handle much of the data analysis on a campus today is the need for a specialized skill set. It can be difficult for most staff and faculty to learn the coding language needed to do it themselves. But if the interface can become more point-and-click-based as opposed to code-based, then end-users — regardless of skill level — will be empowered to take ownership of the entire process.
In short, campuses should be moving from disjointed, insular approaches to data analytics to a holistic, integrated one. For this to happen, the data should be centralized within a single platform, represented by meaningful visualizations, and accessible to multiple stakeholders. Ideally, any terminology should be customized to the campus so it’s easy to understand and manage the data infrastructure. More energy can then be devoted to using the data to surface new insights rather than building or cleaning the original database.
The role of institutional researchers may vary depending on the campus. On some campuses, they are data providers, while on others they are more directly involved in asking questions, interpreting data, and informing discussions, processes, and strategies. Regardless of which scenario you find yourself in, if the data your office houses and produces has utility for stakeholders, you’re providing a service in the name of progress. And while you may not be able to organize tall data warehouses in a single act, you can certainly work to alleviate common data pain points on campus. The benefit for your institution is that you’ll spend less time lassoing myriad data points, and more time assuring your stakeholders that students can succeed.
