For university CFOs, Provosts, and VPs of Strategic Planning, the pressure to demonstrate the financial return on investment (ROI) for every academic program has never been higher. With rising costs and budget cuts, a simple spreadsheet-based analysis is no longer sufficient.
Gray Decision Intelligence emphasizes that effective academic program management requires a data-informed process that is transparent, comprehensive, and collaborative. The challenge of calculating program ROI isn’t the math; it’s the complexity, volume, and integrity of the data you use and the ability to maintain the analysis.
Here are three common pitfalls that sink traditional ROI analyses, and why Direct Instructional Margin is the key metric you should be tracking.
The Power of Precision
Many administrators are dependent on budgetary analyses due to a lack of a more sophisticated tool to make program decisions. Gray DI’s analysis inherently includes cross-subsidization in the calculation of Program Economics. By accounting for the following complexities, Gray DI offers a precise view of each program’s contribution to the overall health of the portfolio.
- Shared Revenue: Without the flexibility to analyze margins at both the program and department level, service departments with a small number of majors can incorrectly be labeled “low-margin.” In reality, most programs rely on required general education (Gen Ed) courses taught by faculty in departments like English or History. Using section-level detail, Gray DI assigns a pro-rata portion of each student’s tuition revenue to every course and every department that taught them. In this way, the high volume of revenue generated by large programs, such as Nursing or Business, can be attributed to the departments delivering the instruction, highlighting that Gen Ed courses are vital components of the institution’s overall financial health.
- Interdisciplinary Instruction: Often, instructors teach outside of their budgetary department. Limiting an analysis to assigning instructional cost to the department responsible for the instructor’s salary will miss efficiencies gained by instructors teaching across content areas, and make courses without a direct link to a departmental budget look “free.”
The Data Gaps in Calculating Student ROI
The modern student and their parents are increasingly treating college as an investment, demanding transparency around their personal ROI. However, understanding the actual value a degree provides is fraught with data gaps that go beyond your institution’s walls:
- Direct Prep Fallacy: Using the direct preparation assignment of programs to occupations offers an extremely narrow view of the earnings potential of a program. Instead, Gray DI uses wage data related to where graduates actually become employed. For example, History majors are associated with only four direct preparation occupations, one of which is Historian. According to BLS, the annual median wage for Historians is $73,000. Using Gray DI’s data, all jobs held by graduates are incorporated to evaluate the post-entry salary (four years after graduation) for Bachelor’s degree holders in History, which is $82,800. In this way, Liberal Arts program outcomes are more accurately captured and reflect the fact that History graduates become lawyers, CEOs, and other professionals, to name a few occupations. By using accurate, multidimensional data, academic leaders can understand and promote the real earnings potential of each program.
The Challenge of Mission-Critical Program Valuation
A sensitive topic for leaders is the decision to grow, maintain, or sunset programs that are central to your institution’s mission. If these programs are small, they can be threatened when only using enrollment numbers to justify cutting programs. Program decisions based solely on enrollment are often a recipe for bad financial decisions.
Gray DI’s benchmarking data reveals a surprising truth: most small programs are contribution-positive.
- Only about 9% of programs in the smallest enrollment quartile of an institution’s portfolio are actually contribution-negative.
- Cutting programs based on enrollment alone means you have a 9 out of 10 chance of eliminating a program that was positively contributing to the institution.
A comprehensive, data-informed program review process will help ensure you avoid these mistakes. A healthy program portfolio includes high-growth, high-margin programs. It is sustained through a web of cross-subsidies where strong programs support the smaller or mission-critical programs that are essential to your identity and academic breadth.
The Path Forward: Embracing Comprehensive Data
To move beyond the budget and make strategic academic decisions, university leaders must adopt tools and processes that centralize and integrate complex data sets:
- Internal Institutional Data (course revenue, direct instructional costs, faculty workload).
- External Market Data (student demand, competitor programs, job market trends).
- Benchmarking (performance against peers).
The goal is to build a data-informed consensus that directs investment toward high-potential opportunities while protecting the programs that support your mission and overall financial health.
