Methodology
This guide summarizes the data inputs and ranking logic that power the Programs experience. It is written for a broad audience—no advanced math required.
The program rankings highlight degree programs reported through the federal Classification of Instructional Programs (CIP) taxonomy. We currently cover associate (level 2), bachelor's (level 3), and master's (level 5) programs in the latest dataset shared by our partners.
Azimuth's program ROI benchmarks every credential against the question “What if a student didn't enroll?” We anchor earnings to College Scorecard's highest-credential median earnings measure, then tier the opportunity cost by credential level:
The ROI we publish is the ten-year incremental earnings surplus divided by the appropriate baseline cost. Negative scores indicate programs that currently trail their opportunity cost.
Azimuth calculates four main metrics for each program, presented as percentile indices (1–99) where higher is better:
Earnings figures represent median annual earnings for graduates at specific time horizons after completion. When available, we display the most seasoned data point (typically 5 years post-graduation) as it provides the most stable picture of career outcomes.
Key context for interpreting earnings:
We display two types of debt separately to help families understand who bears the burden:
Note: Debt figures are measured at the time of graduation and don't reflect post-graduation borrowing (like graduate school loans) or payments made after graduation.
We use the official NCES (National Center for Education Statistics) CIP 2020 taxonomy to translate numeric program codes into clear, human-readable names. Every six-digit CIP code carries a title and definition, and we group programs into broader categories (like “Computer Science” or “Nursing”) to help you explore related fields. You'll never need to know the CIP codes — just search or browse by program name.
You can narrow the list by degree level, state, or a CIP family. Filters update the URL so you can copy and share views directly. As new six-digit CIP rows flow through the API, the program selector will expose them automatically.
All program-level data comes from the U.S. Department of Education's College Scorecard, a publicly available dataset that provides information on institutional characteristics, enrollment, costs, and student outcomes including earnings after graduation.
The College Scorecard combines data from multiple federal sources:
Azimuth performs its own analysis on this base data to calculate our proprietary metrics including return on investment, program size indices, and aggregate scores. We do not modify the underlying federal data — we build upon it to create insights not available in the raw Scorecard.
Official Citation:
U.S. Department of Education. (2025). College Scorecard Data. Retrieved from https://collegescorecard.ed.gov/data/
We refresh program rankings when the U.S. Department of Education releases new College Scorecard data, typically once or twice per year (usually October/November). Each update recalculates all scores to ensure internal consistency across programs and institutions.
Current data vintage: Academic Year 2021-22 completers, with earnings measured through Calendar Year 2023.
Federal education data is powerful but has inherent limitations. Understanding these caveats helps you interpret the numbers correctly and make better-informed decisions.
Transparency builds trust — we surface these limitations so you know exactly what you're seeing.
Earnings data only includes students who received federal financial aid (Title IV: Pell Grants, Stafford Loans, etc.). Students who paid full price or used only private/institutional aid are NOT in this data.
Who's missing: Full-pay students at wealthy private schools, students with only merit scholarships (no federal component), international students, and some military/veteran students using GI Bill only.
Impact: Elite private schools may show lower earnings than reality because wealthy full-pay students aren't counted. Community colleges and for-profit schools are more representative since most students use federal aid.
The percentage of graduates we can track varies dramatically by institution type:
When comparing programs, consider that different tracking rates mean different levels of representativeness.
Graduates and earnings are measured on different calendars:
A June 2018 graduate's "1-year earnings" are from calendar 2019, meaning they may have only worked 6–7 months of that year. This depresses 1-year earnings compared to later years.
The 2-year post-graduation earnings use a "highest credential" filter — they EXCLUDE graduates who went on to earn a higher degree.
Result: 2-year earnings often look lower than 1-year because high-earning grad school pursuers are excluded. The Economics major who got an MBA? Not in 2-year earnings. The Biology major in med school? Also excluded.
This is why you may see a "dip" at the 2-year mark in earnings progressions.
Debt data is measured at the time of graduation/separation and doesn't change across earnings horizons.
What this means:
Federal policy requires suppression of earnings data when cohorts are too small to protect individual privacy.
Suppression rules:
When you see "—" for earnings or debt, it usually means data exists but cannot be shown for privacy reasons, NOT that no graduates exist.
Earnings data only includes people who had W-2 or 1099 income in the measurement year.
Who's NOT counted:
This means earnings data skews toward employed graduates. Programs with high unemployment may look better than reality.
Parent PLUS loan data has very limited coverage at the program level:
When parent debt is blank but student debt is shown, it usually means the borrower cohort was too small for reporting, not that no parents borrowed.
We review the methodology each release to make sure the rankings remain clear and actionable. If you have questions or suggestions, reach out through our contact channel.