Early alert systems: why yours is sitting unused.
Early alert didn't fail because the idea was wrong. It failed because it needed two things nobody had — faculty filling out forms, and staff with time to follow up.
What early alert was supposed to do
Faculty flags a struggling student. An alert routes to an advisor. The advisor intervenes. The idea was right — someone struggling should be noticed, and the person who noticed should be able to hand it to someone who can help. The mechanism wasn't.
Why it didn't work
the buyer's own peer group, rendering a verdict
of community college leaders believe their early alert system is a very effective strategy for student retention and completion across the whole student body.
New America, citing Ruffalo Noel Levitz, 2019 Effective Practices for Student Success, Retention, and Completion Reportof faculty report flagging students. Adjuncts teaching five sections across three campuses do not fill out flag forms. Arithmetic, not apathy.
EABIt only saw academic signals. A student stopping out over an unpaid lab fee never appears. Faculty flag what they can see, and they cannot see a bursar hold.
The flag arrived after the fact. By the time a faculty member notices, the student has been gone for weeks.
advisees per advisor at public 2-year institutions. Someone had to open the dashboard, read it, and act. The arithmetic never worked.
Driving Toward a Degree 2025, Tyton PartnersWhat detection has to do instead
Four requirements. Use them against any vendor, including Boom.
Detect without asking overloaded people to report.
See non-academic barriers — financial, life-event, belonging.
Name the barrier, not just the risk. A score tells you who; it doesn't tell you what to do.
End in an action, not an alert.
The Tinto frame
Boom classifies four barriers: registration holds, financial aid, unpaid balances, and life events. Classification beats scoring because a named barrier has a defined fix. A score has a dashboard.
See how Signal works →In practice
Registration hold detected the day it posts. Student texted for a transcript photo. Photo returned. Staff clear it. The whole exchange takes hours, not weeks — and nobody filled out a form.
See the barrier workflows →Evidence
reduction in summer melt vs. control
LCTCS
n = 1,847 treatment / 1,623 control, Spring 2026
The 41% is melt evidence. It's here as company credibility — proof that the detection approach produces results.
Preliminary and in progress. Quasi-experimental, not randomized. One state network, two campuses, one cycle. Full methodology publishes when the study completes — including if the number gets worse.
Bring us a semester of your data.
We'll show you who you were about to lose.