Key takeaways
1. Prioritize activation over notification: Identifying a student is at-risk is only half the battle won. Success requires shifting from automated alerts to personal outreach that uncovers the root causes of struggle.
2. Track leading vs. lagging indicators: Move beyond lagging data like graduation rates and focus on real-time behavioral changes, such as sudden shifts in dining hall patterns or engagement.
3. Build a culture of psychological safety: Scaling innovation requires a model where staff feel safe to experiment with new intervention strategies, without fear of personal failure for every student departure.
In a recent roundtable discussion hosted by Genio, two prominent voices in the field shared about their experiences identifying and acting upon the lightbulb moments that drove institutional success:
From moving beyond ‘black hole' early alerts to shifting from notification to activation, here are the key themes and strategies from their conversation.
How can institutions move from predictive modeling to proactive intervention?
Knowing a student is likely to struggle by week four is common, but acting on that data is where most institutions fail. To bridge this gap, leaders must move toward a human-centric framework.
Glenn Davis shared a wake-up call from 2020 at BGSU. While the institution was great at identifying students likely to struggle by week four, they were unsure about how to act on that data.
The breakthrough came when BGSU shifted its early intervention framework to ask a central, challenging question:
"What would BGSU look like if students really mattered?"
Here’s how they acted on that question:
- The data: A student fails a biology test.
- The discovery: The student didn’t just fail, they lost their job and were working overnight to pay rent.
- The action: Developed Outreach Coordinators who reached out via phone or text to find the root cause.
- The result: A 30% retention gap began to close, leading to a sustained 4% to 4.5% increase in overall retention.
What is the difference between leading and lagging indicators?
To intervene effectively, success teams must distinguish between data that tells a story of the past and data that predicts the immediate future.
- Lagging indicators: These are metrics like GPA and retention rates that don’t necessarily give the opportunity for early intervention.
- Leading indicators: These are real-time behaviors happening now.
To identify these, Bill Watts suggests empowering frontline teams to surface the barriers they see daily. This led to innovative data discoveries, such as tracking dining hall card swipe patterns.
If a student who usually eats lunch at noon every day suddenly stops, an RA can check on them within 48 hours, long before an academic failure occurs.
How to build a sustainable culture of discovery in higher education
Both leaders agreed that scaling these lightbulb moments requires more than just new software, it requires institutional trust and psychological safety.
1. Responsibility vs. Accountability
Glenn Davis highlighted that while leaders are accountable to the Board of Trustees for numbers, individual staff should only be responsible for the implementation of the idea. This safety allows staff to innovate without the fear that a single student’s departure is their personal failure.
2. Closing the feedback loop
To maintain trust with faculty, BGSU began sending reports that combine hard data with human stories.
- The strategy: Showing that 2,145 interactions occurred from 2,529 alerts.
- The human touch: Sharing the story of a student who stopped attending due to a car accident and was saved by emergency funding.
How to scale from local success to campus-wide impact
Scaling is not about finding a silver bullet, but about creating a synergy between data-driven systems and human activation.
- Set innovation guardrails: Define where teams can experiment and where they must follow the established course.
- Target specific sub-populations: Once systemic improvements stabilize, dive deep into specific majors or students in academic recovery to find the next 1% of growth.
- Leverage high-impact tools: Use AI-enabled transcription and simple UDL aligned platforms to remove unproductive friction for students, allowing them to focus on learning.
Conclusion: Merging systems with human activation
Structuring a student success strategy for the modern era requires a balance of clear hierarchy and human empathy. Data provides the map, but the lightbulb moments experienced by frontline staff drive the actual journey home.
By prioritizing leading indicators, psychological safety, and closed-loop communication, institutions can move beyond the statistics to support the human stories that define retention.
