Andrew Drinkwater

Last Friday, I listened to the One Thought Podcast focused on Strategic Enrolment Management (SEM) in Canada, featuring Melissa Padfield (Deputy Provost of Students and Enrolment at the University of Alberta), Darran Fernandez (Assistant Vice Provost and University Registrar at York University), and Jonathan McQuarrie (Director, Academic Planning at the Higher Education Strategy Associates). The podcast is hosted by Alex Usher of HESA. If you haven’t had a chance to listen to it, I’d highly encourage you to give it a listen – it’s excellent. You can do so here.

There were a few concepts that jumped out to me as they pertain to enrolment forecasting and SEM, and I wanted to share my thoughts. First off – what is SEM? Well, it depends on the context and situation of each institution, but in general, many of the higher ed leaders I talk to say that the art of the start with SEM is understanding who your students are and helping them to achieve their goals while supporting the institutional mission. Here’s a more fulsome definition from Thompson Rivers University:

Strategic Enrolment Management (SEM) is a planning practice centred on expressing an institution’s overarching strategic priorities in terms of the optimal number and mix of students enrolled, and seeks to align enrolment with the values of the organization.

SEM prompts consideration of the many variables — both academic and administrative — across an institution that impact a student’s experience and progress toward pursuing their educational goals, and ultimately their decision and/or ability to enrol and/or remain enrolled.

As such, enrolment goals are defined and pursued through collaborative planning and action, fostering alignment of curriculum, delivery, processes and services with institutional priorities and values.

And what’s enrolment forecasting? Definitions vary, but I’ll go with my own interpretation: an enrolment forecast enables an institution to predict how many students will be enrolled in programs and in courses at different levels of granularity several years into the future. It helps to answer the question of how many students an institution will have in three years, and can potentially help answer the question of how much they’ll pay in tuition revenue.

In the podcast, both Melissa and Darran discussed the influence in data, or a lack thereof, in a higher ed institution’s ability to define what its future student populations may look like. Any lack of data to creates a barrier to both an interpretation of the present and to an appreciation of possible future outcomes and therefore hinders successful planning.

In my experience working at institutions of higher ed, the data available for modelling potential future classes was extremely limited; we were usually confined to assuming history would repeat itself, which is not conducive to endeavors aimed at changing the institutional population. The pursuit of change, such as implementing measures to ensure your student population represents the communities in which you operate, is not a passive process.

While enrolment forecasting is not all of SEM, it is one of many tools that help support SEM. In my ideal world, I’d love to see an enrolment forecasting tool that provides an institution with the agency to craft the composition of its future class and anticipates what will happen in the near term coupled with more aspirational goals for the long term. As undergraduate students at a research university generally take 5-6 years to complete a baccalaureate credential, if you started crafting your future classes today, it could take 5-6 years to fully turn the corner to the future perfect you’re planning for. A quality tool would blend these perspectives, projecting what will likely happen based on your current and incoming populations in the near term, with consideration of your future classes as you get further out in the projection.

Of course, even if after we conceive of how the future should look to meet our goals, we still need to plan and strategize how we will get there. A great forecasting tool therefore also suggests next steps for meeting your goals, for example, by recommending areas for growth – perhaps educational accessibility is a significant barrier, perhaps there are minor changes you could institute that would increase the rate of your prospective student population in becoming applicants.

In the podcast, Melissa also spoke of the need to centre SEM within the context of collegial governance, and avoiding the impression of SEM as corporate initiative aimed solely at financial goals. In my view, a great enrolment forecast supports community engagement in SEM goals by increasing transparency for all levels of stakeholders (e.g., faculty members, deans, institutional staff, community members, and even students). Community buy-in for SEM is increased when the process changes from one reliant on gatekeepers to a community campaign wherein every stakeholder can be informed of possible plans and understands the respective impacts as they relate to their role.

The idea of “what’s in it for me?” is really important here. Let’s say that we want to increase enrolments by 15% - achievement of this goal would almost certainly necessitate changing teaching schedules. Why would a faculty member want to support that? Here are some ideas:

  • By having a plan for growing enrolments, rather than a reaction to it, we can expand our professoriate or hire part-time faculty sooner in the cycle, allowing better preparation for classes, which can help both students and instructors succeed
  • By adjusting our schedules, we might make it more realistic for students to complete their classes on time, promoting and supporting student success and reducing course waitlists over time

Last but not least, a quality enrolment forecast promotes collaboration. In my ideal world, everyone who needs to be involved in the process can be. For example, perhaps each faculty could create its own scenarios in addition to those created by the central administrative teams. A robust approval mechanism could allow those scenarios to bubble to the surface as they proceed towards Senate or other approval bodies. Invitation of collaboration encourages engagement and also allows for differing perspectives that stimulate innovation.

The next recommendation I have for enrolment forecasting and SEM is the integration of data governance into both. I briefly wrote about the role of data governance in enrollment forecasting a couple of weeks ago – stay tuned for how data governance fits into SEM.

What’s your experience like? Is your SEM process intricately connected to enrolment forecasting? Or do they feel a bit like ships passing in the night?