Episode 2:
Emerging signals + Questions
4 Signals
to shape hawaiʻi’s higher education + workforce future
One of the most common — and consequential — assumptions in workforce planning is:
If you earn a college degree, you’ll get a good job.
But when we dig into the data, the reality is more complex.
Most four-year degree graduates from the University of Hawaiʻi do not earn a living wage in their first year after graduation. Some never reach it within five years. And not all graduates stay in Hawaiʻi — even when their degrees do lead to strong wages. This episode surfaces critical insights about the promise — and the limits — of higher education as a pathway to economic security in Hawaiʻi. Retention isn’t just about wages — it’s about the kinds of work available, the communities graduates are connected to, and the cost of staying home.
Signal 1
A Degree Helps — But Isn’t a Guarantee
UH graduates do tend to earn more over time. But no program earns graduates a living wage in year one — and many fall short even after five years.
Questions this raises:
1. Which degree programs lead to sustained economic mobility?
2. What support do recent grads need in those early, underpaid years?
3. How might we better align postsecondary pathways with in-demand, good-paying jobs?
Signal 2
Retention is About More Than Wages
High earnings don’t guarantee graduates will stay in Hawaiʻi. At the same time, many lower-earning grads — especially in mission-driven roles — choose to stay.
Questions this raises:
1. What role do values, mission, and community ties play in retention?
2. How do we uplift sectors like education and social work with better job quality, not just pay?
3. Why are high-wage grads leaving — and what would help them stay? How might remote work opportunities help Hawaiʻi learners gain entry-level experience in industries that may not have many entry-level jobs amongst Hawaiʻi employers?
Signal 3
High-Opportunity Programs Are Too Small
The degree programs that consistently deliver both high wages and high retention — like nursing and engineering — serve a relatively small share of graduates.
Questions this raises:
1. How can we expand access to high-opportunity programs?
2. Are there structural barriers limiting enrollment in these fields?
3. What would it take to replicate their success in other sectors?
Signal 4
We Need a Fuller, More Inclusive Data Picture
This episode revealed how much we can learn from existing wage and retention data — but also where the blind spots remain.
Questions this raises:
1. What are the outcomes for the 50% of Hawaiʻi youth who don’t go to college?
2. How can new data-sharing efforts like Act 154 help close these gaps?
3. What would a truly learner-centered, equity-informed data system look like?
A view from the forest canopy
Answers + Questions
By layering data from DXP and PSEO and visualizing it across campuses, we were able to begin answering questions like…
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Nursing, engineering, and computer science at UH Mānoa and Hilo.
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Programs in education, public service, psychology, and Hawaiian studies consistently show high local retention.
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Nursing and engineering at Mānoa; select IT programs at West Oʻahu; some education programs at Hilo.
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Large portions of grads fall into “low wage / low retention” categories — especially at Hilo, and in humanities or interdisciplinary majors at Mānoa.
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UH West Oʻahu serves highly rooted students but offers mostly low-wage programs. Mānoa offers more high-wage options, but many grads still leave.
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No — many low-wage fields have high retention, often tied to values-driven sectors like education, health, and social work.
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The Opportunity Matrix + campus-level breakdowns created a shared language to begin surfacing differences and strategy needs.
As powerful as this analysis is, it also highlighted major limitations — and raised critical new questions that future data efforts must address:
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DXP and PSEO only track individuals who enrolled in higher ed — we lack clear data on workforce outcomes for non-college goers.
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We need better data systems to compare no-degree training pathways with traditional college degrees.
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Neither dataset disaggregates these metrics — masking equity gaps that likely shape who wins and loses in the workforce.
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The data shows it’s happening, but we don’t know if it’s due to housing costs, career advancement opportunities, family reasons, or something else.
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Without job title, industry, or occupation-level detail in our wage data, we can’t fully assess sector health.
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There’s no rapid feedback loop to evaluate the effectiveness of newly launched certificates or programs tied to emerging sectors.
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Today’s dashboards are useful for researchers — but what would it take to build tools that truly serve students, parents, advisors, and employers?
The data tools in this episode helped us begin to unpack underemployment. But real transformation will come when we can stitch together a full story — one that tracks Hawaiʻi’s learners and workers over time, across systems, and toward a future where everyone has access to meaningful, well-paying work close to home.
Learn more about our process, sources, and assumptions for Episode 2.