Institutional Research and Planning

Breaking Down Costs: Understanding the Instructional Cost of Programs at Marshall University

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In an era of increasing financial scrutiny and accountability in higher education, understanding the cost of program delivery is critical. At Marshall University, the Institutional Research and Planning (IRP) team has developed a detailed methodology to analyze instructional costs across academic programs. This approach offers transparency and the ability to compare costs to the course level effectively.

Why Program Cost Analysis Matters

Higher education institutions face growing challenges, from managing budgets to ensuring tuition affordability. Analyzing program costs helps:

  • Align resources with institutional priorities by understanding which programs are cost-efficient and which require additional support.
  • Provide insights on return on investment (ROI) for programs at all levels and courses of all types.
  • Offer transparency to leadership, faculty, and stakeholders about where instructional dollars are spent.
  • Enhance financial sustainability by uncovering areas of inefficiency, helping the institution make informed adjustments to staffing, course offerings, and delivery methods.

By breaking down instructional costs at the section, course, program, and college level institutions gain a clear view of how tuition dollars are used to support teaching and conversely, the cost of instruction as measured through instructional salaries.

To achieve this, we created a Power BI dashboard that allows university leaders to compare instructional costs at multiple levels. Below, we detail the methodology used to build this analysis.

Methodology for Calculating Instructional Cost for Program Delivery Costs

  1. Create a list of sections being taught in Fall, Spring, and Summer of a given academic year, removing 3rd Party Contract, Dual Credit and WV Rocks sections.
    1. This allows us to total student credit hours at the section (and course) level
  2. Generate a list of students who are enrolled in the sections from #1 above
    1. For each student, recorded their primary college, primary major, total SCHs, and assessed tuition for each semester of enrollment.
    2. Calculated tuitionPerSCH for each student per semester of their enrollment by taking AssessedTuition / sum(SCHs) – this is at the student level
  3. Created a list of instructors assigned to any of the sections generated in #1 above.
  4. Calculated a salaryTowardTeaching figured for each individual in #3 above, per semester.
    1. First cut, normalize the annual salary
      1. If 12-month faculty, annual salary at 9/11
      2. If 11-month faculty, annual salary at 9/11
      3. If 10-month faculty, annual salary at 9/10
      4. If 9-month faculty, annual salary
    2. Second cut, if that person received 26 pays in the year, each major semester (fall/spring) gets 50% of the salary
      1. If the person received 13 pays, they were only here one semester of the AY, use that as the base for the semester salary
    3. Before making this salary “final”, we run it through the following formula to get to the instructional portion of the salary:
      1. SemSalary * .8 (80% of a full-time faculty’s time is assumed to be teaching) * InstructionalFTE / 100
        InstructionalFTE is 100% for someone teaching 12 hours in load in a term, 75% for someone with 3 hours of release, 50% for someone with 6 hours of release, 25% with 9 hours of release
    4. Compensation for overloads is added as a full amount directly to the salaryTowardTeaching variable for that instructor in the semester
    5. Compensation for adjuncts is added as a full amount directly to salaryTowardTeaching
    6. Summer teaching compensation is added as a full amount to salaryTowardTeaching
  1. Created a listing for each section from query #1, joined with each instructor with teaching responsibilities and a normalized % responsibility for each section and each instructor was established. Examples:
    1. Section with a single instructor of record, that instructor’s responsibility is 100%
    2. Multiple instructors assigned to a section, if total responsibility adds to 100% in Banner, each is left as is
    3. Multiple instructors assigned to a section, if total responsibility > 100%, each is normalized so that the sum of all is 100%. IE, one at 100, one at 50, one goes to 66.7 the other to 33.3, etc.
  2. Calculations from #5 are used to generate the SCHs of Responsibility for a faculty member, by semester.
    1. As an example, if, they are the sole instructor of record on sections with SCHs of 50 and 50, and 50% responsibility on a section w/50% responsibility, the SCHs are 50 + 50 + (50*.5) = 125.
  3. A cost per SCH is then generated per instructor, per semester by taking their salaryTowardTeaching / SCHs of Responsibility

This allows us to model instructional cost by section, course, a student’s major, an instructor, etc. since we have both a tuition $ assessed for each hour and a $ per hour of responsibility of instruction.

Insights and Impact

This was the first step in determining the true cost of a program as instructional cost is typically the largest expense in an academic program. Future work will add in the cost of supplies, staffing, facilities, and other associated expenses, providing a more comprehensive view of program delivery costs.

The ability to break down program delivery costs equips leadership with actionable insights. For example:

  • Cost Transparency: Compare instructional costs across programs to identify efficiency opportunities.
  • Strategic Planning: Use cost data to inform decisions about program growth, faculty staffing, and curricular adjustments.
  • Improved Accountability: Demonstrate to stakeholders how dollars are allocated and spent, fostering trust and alignment with institutional goals.
  • Data-Informed Investments: Identify opportunities to invest in programs with strong ROI or improve programs that may be underperforming.

The Power BI dashboard built from this analysis allows stakeholders to explore these insights dynamically, supporting informed decision-making. By linking costs to tuition revenue, it also provides a clearer picture of program ROI and sustainability.

For leadership, this data provides the foundation to ask critical questions:

  • Are program costs aligned with enrollment and revenue trends?
  • Where can efficiencies be found without compromising quality?

Looking Ahead

Understanding the cost of program delivery is not a one-time exercise. As instructional methods evolve, student enrollment shifts, and institutional priorities adapt, maintaining an up-to-date analysis ensures the university remains agile, sustainable, and transparent in its financial decisions. By expanding this analysis to include additional cost factors like facilities and staffing, we can offer a full cost-to-value perspective for every program.

We are committed to providing the tools and data needed to navigate these challenges. Our work supports strategic decisions that ensure Marshall University continues to serve its students effectively and efficiently.

Driving all decisions, with data!

Brian M. Morgan
Chief Data Officer, Marshall University

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