Do You Know Why Your Enrollment Will Drop This Semester?

If you’re reading beyond our headline above, you’re probably among thousands of higher education professionals increasingly concerned over falling enrollment and urgent retention issues. It’s probably the key subject of your weekly meetings…and your monthly meetings…and your quarterly meetings…

The question we’re constantly asking of higher education staff is: how well do you understand the issues behind your enrollment and retention trends? It’s not good enough to simply see these trends happening. You need to really dive into the details and understand what’s happening under the surface that’s causing students to drop out, or transfer, or not enroll in the first place. More importantly, you need to know why it’s happening so you can prevent it from happening again.

To achieve this, we offer the following guideline we’ll call “Pool, Predict and Prevent” and suggest that you challenge your university or college to follow this guideline to help you identify and use your organizational data to greatest effect. What is our guideline? Let’s look at each section in turn.


Also known as the technical hurdle. Pool your data sources together into one location so you can analyze trends campus-wide. Overcome this hurdle and you can finally analyze one set of numbers. But before you can pool, you have to address some common challenges. The answers you’re seeking—hidden in your university’s data—can be hard to consolidate for several reasons, some technical, some not. See if any of these sound familiar:

  • “The data we need is scattered throughout campus, often in different software platforms, always involving dozens, if not, hundreds of spreadsheets.”
  • “We have no data warehouse. Our data is never consolidated into a single location which would offer the ability to analyze trends across all data points.”
  • “It’s too difficult and cumbersome to squeeze trends out of our spreadsheets. We have complex formulas, tabs, updates, links, multiple contributing authors—introducing data error, calculation error, and out-of-date data problems. This result is a complete inability to rely on the data for any meaningful decision-making.”
  • “Data quality suffers. Starting from the source, data errors and inconsistent standards and definitions find their way all the way through our data management process and onto our summary analysis.”
  • “We have no time for extra analysis. We’re bogged down with requests from faculty and staff for data and analysis!”

I bet you could add 2-3 more items to that list. The point is that it’s not as easy as it appears to simply gather the data before you can analyze it. But pool you must, because the advantages of operating on a single set of numbers are too good to ignore.


Moving on, let’s imagine you can overcome this hurdle and have clean data in one centralized location, primed for expert analysis. Now what? Let’s go back to my earlier question: how well do you understand the issues behind your enrollment and retention trends?

Time to predict. Let’s call this the dashboard hurdle. Overcome this and you can finally see the trends. But how do you do this? Simple. Choose from any of the 1000s of business intelligence solutions out there and you can link that data to a host of colorful dashboards with all sorts of clicking, swiping, selecting and more. OK good. Now you can at least see the trends.

But is that enough?

Imagine you’re looking at your enrollment line graph. Does this solve your problem? Are you able to understand what’s happening? More importantly, are you able to prevent it? You need to start looking under the surface. Take that deep dive and start exploring.

When you’re focused on retention issues, you’ll likely start looking at what happened to the students that dropped out in the last 2 years. Are there trends in their GPAs? Were their GPAs falling in prior semesters? Did those students lighten their course load in the preceding semesters? Did they change the focus of their course load to easier courses or courses that didn’t support their major? Did their class attendance drop off?

Any of these trends might suggest dissatisfaction with the curriculum, or the faculty, or the campus, or some other element of their university experience. These are issues at the core of the problem—issues that you must address. If you could roll back time and engage those students, you might’ve been able to prevent some of them from dropping out. You should at least, learn from these trends and use them to help the cause going forward.

The idea is to put this experience to work for you. Consider having a magic wand that can sweep across your student performance history and scrutinize what happened over the past several semesters. Chances are that there were early warning signs that emerged in the data that foretold the outcome we wanted to avoid. Now that we’ve found them, we can watch for them and set triggers to help us prevent future problems.


We’ll call this the watchdog hurdle. Overcome this and you can finally prevent future problems before they happen. This requires the right tools and processes to be sure. Instead of waiting another 6 months only to find ourselves in this same situation—looking in the rear view mirror, trying to fix retention issues—we need tools that can “watch our back”, so to speak.

Leveraging tools here is the right idea. Let technology and your data work for you in the background, watching for specific early warning indications to arise. Do we have technology to do this? Leading business intelligence software solutions are learning that users need more than just dashboards, more than fancy ways to click through everything for hours on end. Users need real help finding answers, supporting decisions and taking action. Thankfully, advances in automation, report generation, data mining, monitoring, alerting, sharing and collaborating are helping business intelligence users lighten their workload, offload detailed data monitoring for critical conditions, and facilitate sharing of analysis tools to help alleviate the constant stream of requests.

So, to help prevent future retention issues, we can use this type of technology to detect and report so we can engage the students and address any concerns to counter falling enrollment trends. For example, we might want to watch for GPAs falling more than 5% among sophomores in our Geology program and automatically email the academic counselors when any single or group of students falls into this category. Of course, we could watch these numbers manually without too much effort. But in reality, the trends are more complex and more in number. Watching for a few key conditions is one thing. Watching for a larger list of targeted problem areas across university data at varying depths of detail is entirely a different problem, and one that could be very time consuming. But that is the challenge. That’s where the opportunity exists to address these issues—down in those details. So, to prevent in those cases we’d likely want to leverage automation and technology.

With the right tools, we can be given advanced warning and the opportunity to prevent students from dropping the program, or dropping out altogether. Stop our falling enrollment at its source. This is, at least, one critical approach to preventing known problem trends from repeating.

Pool, Predict and Prevent – Combined

Universities following this “Pool, Predict and Prevent” guideline can answer our question about understanding root causes of retention issues with a confident ‘yes, we can’. It’s not unreasonable to assume that—with this advanced preventative approach—they will be among the leading (or surviving?) universities in the future.

With the right technology at work, our scattered data sources consolidated into one location, early warning indicators watching our back, and the proper staff and faculty response procedures in place, universities can consider themselves far more equipped than ever before to be able to fully understand why enrollment falls at any time in any area—and be able to take preventative action to engage at-risk students and address issues that are behind those trends.

Authored by (SDD), a company that has been helping higher education professionals establish and maintain a clear picture of their organizational data, trends, outliers, problems and opportunities. SDD offers business intelligence workshops and consulting for higher education. To learn more about SDD’s workshops, please visit