How to use this report

What this tool is good for

• Rapid what-if analysis for a specific course offering (one section at a time).

• Identifying breakeven enrollment or the cost level needed to break even.

• Comparing FT vs PT and State-funded vs Self-support scenarios using the same course assumptions.

What this tool does not do

• It does not evaluate program-level economics (some courses can run at a loss while others run a surplus; the overall program may still net positive).

• It does not include labor force / community demand, strategic importance, accreditation requirements, or reputational considerations.

• It does not capture downstream impacts like schedule pathway design, cohort effects, or multi-section efficiency.

Decision philosophy

Some courses should run even if they lose money—especially when:

• A small group needs the course to graduate (completion obligation).

• The course is a prerequisite bottleneck in a pathway.

• Demand is strategically important (workforce alignment, community commitment, employer needs).

Also note: FT instruction often correlates with higher student success in many contexts. A low-cost staffing choice (e.g., PT-heavy) may look attractive short-term, but if it reduces student success and retention, it can reduce revenue over the mid-term. This tool estimates single-course margin, not multi-term retention impacts.

Variable guide (how/when to use each lever)

Revenue levers

Prefix (State FTE Tier)
Select the course prefix to pull the correct state funding tier and program context. Use the prefix that matches how the section will be reported/claimed.

Students
The enrolled student count for the section you’re evaluating. Use realistic values (current enrollment, expected enrollment, or a scenario range). This lever has the largest effect on revenue and often drives the go/no-go outcome.

Contact Hours
Weekly contact hours (or total contact hours depending on your model definition) used to allocate instructional cost to the course. Set this to the standard contact hours for the course.

Credit Hours
Credit hours for the course. Primarily impacts self-support tuition revenue (credits × students × SS rate).

Lab Fee
Lab fee per student. This tool assumes lab fee revenue is generally offset by lab-related instructional supplies, so lab fees typically don’t move margin much unless you also change the associated expense behavior.

SS Tuition (Self-support tuition rate per credit hour)
Used for self-support scenarios. Adjust when you want to test tuition pricing or when the course has a non-standard rate assumption.

Expense levers

Faculty (Funding Type)
Choose whether the section is staffed as FT or PT/Adjunct. This selection changes salary/benefit logic and drives different breakeven grids. For overload sections increase the total load assumed for the faculty member to allocate medical insurance costs.

FT Load (Contact hours per Week)
Used to prorate annual FT salary/benefits to the course. Set this to the typical contact-hour load used in your costing assumptions (e.g., 18).

FT Salary
Annual salary assumption used in FT cost allocation. Use a typical rate (median, average, or specific faculty scenario). This lever is explored extensively in the FT breakeven grids.

Adjunct Rate
Hourly/contact-hour pay rate for PT staffing. Use your current adjunct rate schedule or scenario rate.

Other Cost
A catch-all for additional direct costs you want included (materials, specialized software, unique supplies not covered by lab fee logic, etc.). If you don’t have any, leave it near 0—otherwise use it explicitly so the analysis reflects reality. The cost is flat, it does not vary based on the number of hours or the number of students.

How to interpret the results

1) Breakeven Grids (the four bubble charts)

Each chart shows a grid of possible combinations:

• X-axis: Students (5 to 50)

• Y-axis: Faculty cost driver

  • FT charts: Annual salary

  • PT charts: Adjunct rate

• Dot color:

  • Green = CM ≥ 0 (surplus)

  • Red = CM < 0 (loss)

• Dot size: Magnitude of gain/loss (bigger = larger absolute dollars)

• Gray step line: The breakeven boundary (closest-to-zero CM).

  • Points to the right of the line indicate where you move into surplus vs loss.

How to use:

• If your current scenario dot is red, use the chart to see what would move it to green:

  • More students,

  • Lower cost (salary or adjunct rate),

  • Or different pricing (self-support rate, credits).

• Use the boundary line to approximate:

  • “At this salary/rate, we break even around X students.”

  • “At this enrollment, we can afford up to $Y salary / $Z adjunct rate.”

2) Specific Course Analysis (cards + P&L)

This section explains why the scenario is green or red.

• CM and CM% cards summarize the outcome.

• P&L table shows revenue and expense components grouped by:

  • Revenue

  • Expenses

  • Margin

How to use:

• If margin is negative, identify which component dominates:

  • Too few students (revenue issue)

  • Salary/benefits too high for the enrollment (cost issue)

  • Self-support pricing too low for credits (pricing issue)

• Use this to document your decision rationale.

Making go/no-go decisions with the report

Use a structured approach:

Step 1 — Model the “most likely” scenario

Set the levers to your best estimate (expected enrollment, staffing plan, realistic salary/rate).

Step 2 — Check financial outcome

• If CM is meaningfully positive: proceed unless there are constraints (capacity, schedule conflicts, staffing limits).

• If CM is near zero: treat it as a borderline decision—use strategic considerations.

• If CM is materially negative: move to Step 3.

Step 3 — Identify the least-disruptive lever to move

Common levers (in priority order):

1. Enrollment actions (marketing, schedule optimization, combining sections)

2. Staffing plan (FT vs PT, or which FT cost scenario is most realistic)

3. Delivery efficiency (contact hour structure if applicable, modality)

4. Pricing (self-support rate or fees, where policy allows)

5. Cost containment (Other Cost, supplies where feasible)

Step 4 — Make the decision using mission + strategy guardrails

A negative CM does not automatically mean “no.” Consider “yes, with subsidy” when:

• Students need it to graduate (completion obligation).

• It prevents pathway bottlenecks that hurt retention.

• It supports workforce demand or community commitments.

• It is part of a program bundle where other courses generate surplus.

A positive CM does not automatically mean “yes” either—consider capacity, quality, and long-run success outcomes.

Important strategic notes (include with the report)

• Program portfolio reality: Some courses are expected to run at a loss while others run at a surplus. A healthy program may net slightly positive overall even with loss-leading courses. This report evaluates a single course, not the full program portfolio.

• Student success considerations: FT instruction can be associated with stronger student outcomes in many contexts. A short-term “lowest cost” staffing approach can reduce success and retention, which may reduce revenue in future terms. Use this tool for financial transparency, but treat staffing decisions as both cost and success levers.

• Demand is not modeled: The report does not incorporate labor market demand, employer partnerships, or community need. Use it alongside demand signals and pathway planning—not as a standalone decision engine.