The Fundamental Truth
"Every kid needs a champion—an adult who will never give up on them, who understands the power of connection and insists that they become the best that they can possibly be." — Rita Pierson. No algorithm, however sophisticated, can replace this human element.
The email from the early warning system arrived at 7:23 AM: "Alert: Student Marcus Thompson has triggered multiple risk indicators. Attendance: 82%. Math grade: F. Two behavior incidents this quarter." The data was accurate, the flag was appropriate, and the system was working exactly as designed.
What happened next had nothing to do with algorithms.
Counselor Denise Williams read the alert and walked to Marcus's first-period classroom. She caught his eye through the window and gestured for him to step out. In the hallway, she didn't mention the data or the flag. She simply asked: "Hey Marcus, how are things going? I've been thinking about you."
That conversation—not the algorithm—changed Marcus's trajectory. He opened up about his mother's illness, his new responsibilities at home, his fear that he was falling too far behind to catch up. Ms. Williams listened, validated, and problem-solved. Together they created a plan: modified deadlines, a peer tutor, a weekly check-in, and a referral to the school social worker for family support.
Six months later, Marcus was back on track. When asked what made the difference, he didn't mention the early warning system. He said: "Ms. Williams. She actually cared. She made me believe I could do it."
What Algorithms Can and Cannot Do
Early warning systems are remarkable tools. They can process thousands of data points, identify patterns invisible to human observation, and surface students who might otherwise be overlooked. They can do this consistently, at scale, without the fatigue or cognitive biases that affect human judgment.
But they cannot do the things that actually change student outcomes:
Algorithms cannot build relationships.
Students persist through challenges when they feel connected to adults who believe in them. No data system can create that connection.
Algorithms cannot understand context.
A student's 82% attendance rate is just a number. Understanding why—and what would help—requires human conversation and judgment.
Algorithms cannot inspire hope.
Students who've lost belief in themselves need someone to hold hope for them until they can hold it themselves. That's profoundly human work.
Algorithms cannot adapt in the moment.
Effective intervention requires reading emotional cues, adjusting approaches, and responding to what a specific student needs in a specific moment.
The most sophisticated early warning system in the world is useless without humans who can transform identification into intervention, data into dialogue, and alerts into action.
The Research on Relationships
The centrality of human relationships in student success isn't just intuition—it's documented in decades of research:
Studies of resilience consistently find that the single most important factor differentiating children who overcome adversity from those who don't is the presence of at least one stable, caring adult who provides support and models appropriate behavior.
Research on dropout prevention shows that students' relationships with teachers are among the strongest predictors of school completion—more predictive, in some studies, than academic performance itself.
Surveys of students who've overcome significant challenges consistently identify specific adults—teachers, counselors, coaches—whose belief in them made the critical difference.
What Students Say Makes the Difference
"My counselor believed in me when I didn't believe in myself."
"Mr. Jackson noticed I was struggling before I even said anything."
"She didn't just look at my grades—she asked about my life."
"He told me he wouldn't give up on me, and he meant it."
"She saw something in me I couldn't see in myself."
Notice what these statements have in common: they're about being seen, being believed in, being cared for. Not about data, algorithms, or systems. The technology points us to the students; the relationships change them.
ABC Early Warning System
Identify at-risk students before they fall behind with our comprehensive ABC framework.
Designing for the Human Element
If relationships are what matter, how do we design early warning systems that enhance rather than replace human connection? Several principles emerge:
Technology Should Create Time for Relationships
The best use of early warning technology is freeing educators from data-digging so they can spend more time with students. Instead of counselors spending hours combing through records to identify struggling students, the system surfaces those students automatically—giving counselors more time for actual counseling.
"Our EWS saves me probably four hours a week that I used to spend pulling reports and cross-referencing data," reflects counselor Patricia Williams. "That's four more hours I can spend actually talking to kids."
Alerts Should Prompt Conversations, Not Conclusions
An early warning flag should be understood as an invitation to investigate, not a verdict to act upon. The data tells us something might be wrong; only human conversation can reveal what's actually happening and what would help.
Training for staff using early warning systems should emphasize this investigative stance. When a student is flagged, the first question isn't "what intervention do we apply?" but "what's going on for this student, and how can we find out?"
Systems Should Support Relationship Tracking
Beyond tracking attendance and grades, early warning systems can track something equally important: whether students have caring adults in their corner. Relationship mapping—systematically identifying which students are and aren't connected to adults in the building—ensures that no student is left without a champion.
Some schools add relationship indicators to their early warning dashboards: Does this student have an assigned mentor? When was their last documented check-in? This keeps the human element visible in a data-driven system.
Response Protocols Should Center Relationship Building
When response protocols focus exclusively on interventions—tutoring, counseling, behavior plans—they miss the deeper opportunity. The first response to any flag should be relationship building: Who will be this student's consistent point of connection? How will we ensure they feel known and valued?
Interventions work better when they happen within the context of caring relationships. A student is more likely to engage with tutoring when it comes from a tutor they trust. They're more likely to open up in counseling when they feel the counselor genuinely cares. Relationship is the foundation on which intervention effectiveness depends.
The Champion Model
Many schools implementing early warning systems have adopted some version of the "champion model"—ensuring that every flagged student has a specific adult assigned as their advocate and primary point of contact.
The champion isn't necessarily the person who delivers interventions. They're the person who:
Knows the student — their strengths, challenges, interests, and circumstances
Checks in regularly — not just when there's a problem, but consistently over time
Advocates for the student — in intervention team meetings, with teachers, with administration
Coordinates support — ensuring that various interventions work together coherently
Maintains hope — believing in the student's potential even when progress is slow
Research on mentoring suggests that the consistency and duration of the relationship matter more than the specific interventions provided. A champion who shows up week after week, semester after semester, creates the foundation of trust on which everything else is built.
Training for Relational Response
If relationships are central to early warning success, staff training should emphasize relational skills alongside data literacy. Key competencies include:
Relational Competencies for EWS Response
Authentic Curiosity
Approaching flagged students with genuine interest in understanding their experience, not just diagnosing their deficits.
Empathic Listening
Hearing the whole student—their feelings, fears, hopes—not just gathering information for an intervention plan.
Strength-Based Framing
Seeing and naming student strengths even while addressing challenges. Students rise to expectations.
Patience and Persistence
Understanding that trust builds slowly and setbacks are normal. Commitment to students doesn't waver with slow progress.
Cultural Responsiveness
Building relationships that honor students' identities and contexts, not imposing one-size-fits-all approaches.
Appropriate Boundaries
Caring deeply while maintaining professional relationships that serve students' long-term wellbeing.
Success Stories
See how Michigan charter schools are achieving results with AcumenEd.
When Technology Undermines Humanity
It's worth acknowledging the ways early warning systems can actually undermine the human element when implemented poorly:
Data substitutes for dialogue. When staff believe they understand a student because they've seen their data profile, they may skip the conversations that would reveal what's really going on. The data creates an illusion of knowledge that forecloses deeper understanding.
Standardized interventions replace individualized support. Systems that prescribe specific interventions based on flag types can lead to cookie-cutter responses that don't fit individual students' needs or circumstances.
Documentation displaces relationship. When responding to alerts requires extensive documentation, staff may spend more time entering data than talking to students. The system that's supposed to help students can end up competing for the attention students need.
Labels replace complexity. Flagging students as "at-risk" can create deficit-focused framing that shapes how staff see and interact with them. Students can become their labels rather than full human beings.
Guarding against these tendencies requires constant vigilance. The question to keep asking: Is this system making us more connected to students, or less? Is it enabling relationships, or replacing them?
The Partnership Model
The healthiest framing for early warning systems is partnership: technology and humanity working together, each contributing what they do best.
Technology contributes: scale (monitoring thousands of students simultaneously), consistency (checking the same indicators in the same way every time), pattern recognition (seeing connections humans might miss), and efficiency (surfacing information without manual searching).
Humans contribute: relationship (the connection that motivates student effort), judgment (understanding context and nuance), flexibility (adapting approaches to individual needs), and hope (believing in students' potential for growth).
Neither partner can succeed alone. Technology without humanity generates alerts that no one acts on meaningfully. Humanity without technology struggles to identify all students who need support in time to help. Together, they can create systems that are both comprehensive and deeply personal.
Keeping the Human at the Center
Return to Marcus Thompson, flagged by the early warning system on that morning six months ago. The system did its job: it identified a student in trouble early enough to help. But it was Ms. Williams who made the difference—her choice to walk down the hallway, her question about how things were going, her genuine care that opened Marcus up, her creative problem-solving that charted a path forward, and her ongoing presence that kept him accountable and supported.
Marcus doesn't remember the algorithm. He remembers the person.
That's as it should be. Early warning systems are powerful tools, but they're tools in service of something more important: human relationships that help young people believe in themselves and persist toward their potential. The technology matters. The protocols matter. But in the end, what changes lives is one caring adult who refuses to give up on one struggling student.
Every decision about early warning systems—what technology to purchase, how to configure it, what protocols to establish, how to train staff—should be evaluated against a simple question: Will this help more students find their champion? If yes, proceed. If no, reconsider.
Because in the end, that's what this work is about. Not dashboards, not algorithms, not data. Champions. And the students whose lives they change.
See AcumenEd in Action
Request a personalized demo and see how AcumenEd can transform your school's data.
Key Takeaways
- Algorithms identify at-risk students, but human relationships change their trajectories.
- Technology should create time for relationships by automating data gathering so staff can focus on students.
- Every flagged student should have a "champion"—a specific adult committed to knowing them, believing in them, and advocating for them.
- Staff training should emphasize relational skills alongside data literacy.
Dr. Sarah Chen
Chief Education Officer
Former school principal with 20 years of experience in K-12 education. Dr. Chen leads AcumenEd's educational research and curriculum alignment initiatives.
