Welcome to a new blog series on one of the most critical—and often least understood—elements of strategic enrollment planning: setting enrollment targets.

Over the next four weeks, we’ll explore this topic from several angles:

• Part 1: Defining Targets—Balancing Vision with Reality (Below)
• Part 2: From Proposal to Practice—Your Process Map
• Part 3: Pitfalls to Avoid—Lessons from the Trenches
• Part 4: The Next Frontier—Predictive Analytics & AI

Part 1: What Are Enrollment Targets—and How Do We Set Them?

At their core, enrollment targets are goals. They represent the future state an institution wants to achieve at a defined point in time.

In our personal lives, a target might be, “Retire by 55” or “Lose 10 pounds by September.” In higher education, they sound more like:

• “175 new international direct-entry students in the Bachelor of Arts program in Fall 2027.”
• “24 new domestic transfer students in the Bachelor of Nursing program in Winter 2026.”

Some targets are absolute. Others are relative, especially when tied to government policy or internal planning priorities:

• “Increase first-year Engineering enrollment by 5% per year over the next three years.”
• “British Columbians will soon benefit from more nurses to support their health-care needs as 602 new nursing seats are being added to public post-secondary institutions.”

Good targets follow the SMART principle: Specific, Measurable, Actionable, Realistic, and Time-bound. The SMART mnemonic is a solid starting point for setting enrollment targets because:

• Specific forces you to nail down exactly what you’re measuring (e.g. “175 new international BA students in Fall 2027”), which aligns all downstream activities (recruitment channels, scholarship awards, space planning) to the same goal.
• Measurable ensures you have clear metrics (applications, admits, deposits, headcounts) and a cadence for tracking progress.
• Actionable/Attainable reminds you to choose targets you can directly influence through levers you control (marketing spend, faculty allocations, admission criteria).
• Realistic keeps you honest about capacity constraints (lab seats, faculty load, collective agreements) and market realities (demographic trends, competitor moves).
• Time-bound ties the target to a defined cycle, ensuring that you synchronize budget, staffing and facilities planning to academic calendars.

But enrollment planning layers on additional complexity that SMART alone doesn’t capture:

• Governance & Iteration: Enrollment targets live in a multi-layered approval process (deans, Senate, Board) and often need mid-cycle tweaks. You need decision-rights and “fast-track” protocols to adjust in real time when policy or market shifts.
• Multi-Scenario Risk: A single target doesn’t show you the levers you might pull if you fall short—or overshoot. Embedding scenario-based forecasts alongside your SMART goal helps you see “if deposits dip by 10% in Program A, here’s how to respond.”
• Cross-Unit Collaboration: A target set in isolation can still founder if stakeholders (faculty, registrar, IR, recruitment, finance) aren’t co-owning it. Embedding shared dashboards and regular touchpoints is critical.
• Data Quality & Automation: assumes you have reliable, timely data—yet many IR teams spend more time reconciling spreadsheets than analyzing insights. Automating your data pipelines and defining a single source of truth is a prerequisite for truly SMART targets.

In practice, targets also differ by type. Here are a few examples:

Critically, targets aren’t limited to new student intakes. Institutions may also set targets for:

• Total enrollment
• Student retention or graduation numbers
• Enrollment by demographic (e.g., in-state, Indigenous students)
• Program mix (e.g., graduate vs. undergraduate)
• Delivery mode (e.g., online vs. on-campus)

Targets can also be influenced by a variety of other factors:

You may have noted that I’m glossing over the intersection of online education and targets, where physical constraints and pedagogical reasons are very different. I think this merits further discussion, and will bring it to a future post.

Two Common Models: Top-Down vs. Bottom-Up

From experience, most institutions follow one of two broad approaches when setting targets:

• Top-Down Target Setting Senior leadership (typically the Provost / VP Academic) defines the overall target and allocates portions to faculties or divisions. Faculties may then negotiate their share among themselves or with the Provost —often informally referred to as “horse-trading.”
• Bottom-Up Target Setting Faculties or departments define their own targets based on internal factors: faculty availability, classroom capacity, historical performance, or strategic priorities. Central administration then consolidates these into an institutional plan.

Each approach has its pros and cons. Bottom-up processes tend to generate more scenarios and foster engagement at the academic unit level. Top-down processes may produce fewer variants but streamline coordination and ensure alignment with institutional strategy.

The Government Factor: Autonomy vs. Alignment

For public institutions, the degree of institutional autonomy plays a major role in how targets are set:

• High autonomy institutions—typically research-intensive or block-funded universities—may independently set targets based on market demand, internal capacity, and long-term goals.

• High alignment institutions—often in more centralized systems, must align closely with government direction. Governments may:

1. Mandate enrollment targets in specific disciplines
2. Tie funding directly to those targets
3. Specify demographic or geographic enrollment priorities

Where institutional autonomy is high, enrollment targets reflect strategic positioning. Where government direction is strong, target-setting becomes a complex exercise in policy translation.

Coming Up

In Part 2, we’ll explore the mechanics of how enrollment targets move from idea to implementation. What are the internal approvals? Who’s involved? How are capacity and constraints surfaced and resolved?

If you’ve ever wrestled with how to “make the numbers real” in a budget or planning cycle, you won’t want to miss it.