An Early Alert System Will Fail Without an Early Alert Philosophy

Congratulations to the two schools I spoke to over this weekend in their decision to recommend against investing in an early alert system before they were ready.

Early Alert systems are designed to highlight students who are at high-risk of negative behavior, like struggling, withdrawing from a course, or worse, dropping out of college entirely. Hundreds of companies worldwide have been offering systems to track and target at-risk students in every type of educational environment, but for some reason higher education is the most profitable one. Any idea why that is?

Maybe it’s because higher education is constantly looking for money to spend, even though what it should spend money on is right under its nose (hint: it’s students). Early Alert systems are often seen as the magic ingredient that your college has been missing. At last, a piece of software that will get more of our students completing degrees and certificates faster than ever before!

Eric McIntosh of Civitas Learning Systems sums up how a lot of administrators feel when it comes to the potential of early alert systems on their campus:

Knowledge of which students need which supports, and when they need those supports, would be a great way to ensure every student has access to the support they need, when they need it. Unfortunately, it is has been difficult to know what intervention – or inspiration – each student needs, and it has been difficult to know exactly when they need the outreach. Fortunately, predictive modeling affords a more nuanced and focused perspective on student engagement and risk, and let’s us be more precise in our efforts to support every student’s journey.

Yes! Data Science in Higher Education for the win!

Except there’s a flaw with Early Alert systems, and that flaw has nothing to do with the systems themselves. EAB, Pharos, Civitas, Hobson’s Starfish, and more are doing a great job building great software to do great things. I’ve worked with many tools over the years (even though I’m a huge advocate of building your own) and I’m very impressed with what they can do with the right data. The problem is that institutions are buying and implementing these tools before they need them.

It’s the cart before the horse, folks. We’re buying tools to get early alerts on student dropout behavior before we have a plan to collect the data we need to plug into the system! Why is that? Maybe it has something to do with the Law of Triviality, where a group of people will tend to spend the most amount of time on the most trivial of problems in a given problem set. That is, maybe we want to spend all our time playing with the tools because we are afraid to admit that we’re not ready to use them.

To be fair, an old colleague who now works at Deloitte said that there are good people at these third-party vendors that try to use the demos of their early alert tools as a way of showing colleges just what is possible if you are collecting the right data. If you’re not, though, it’s very easy to be swept away with what you could be doing (and enter into a huge annual contract), instead of focusing on what you should be doing.

We need an Early Alert Philosophy. Before we spend any money, let’s spend some time thinking about what data we need, how we are collecting it, and most importantly, what we will do with the information about at-risk students. If we don’t have at least a philosophy about what we will be doing with our early alert data, then we cannot possibly benefit from investing in the tools that generates that data for us.

The foundational mindset needed to capitalize on an early alert system can be forged by following my free checklist for Analytics Readiness. Spend some time with your college leaders and the professionals in student services to come up with a solid plan of what you will do with early alert information. Early alert systems should augment existing processes, not create them. 

In summary:

  • Don’t invest in Early Alert software unless you are prepared to take action with what it produces
  • Good intelligence is only as useful as the knowledge it creates
  • Knowledge is only as useful as the action is it inspires