Is Enrollment Forecasting Cooperative or Collaborative?

Does your enrollment forecast process feel cooperative or collaborative? Both are good when used effectively, and can fall apart if not. Cooperation without collaboration lacks coherence and unity. Collaboration without cooperation fails to respect individual autonomy and can lead to group think (Spencer, 2019 ). Innovation comes when they are used together.

Universities and Colleges Lean Towards Cooperative, Rather Than Collaborative

For enrollment forecasting, many institutions I’ve seen have ended up more in the cooperation side. They’re high individual autonomy and each stakeholder is relatively independent, moving towards collaborative only where they have to (such as a large increase in business students necessitating an increase in English courses).

IR Professionals as Gatekeepers

One of the reasons why there are challenges with this approach is that Institutional Research professionals often end up as gatekeepers to the process, however unintentionally. In many cases, they built the institution’s enrolment forecast model by hand, using the tools and skills available to them at the time. For example, in a former life, me and a small team in IR built a model using R, Oracle, and Java. Many build their models in Excel.

The Models Don’t Scale

In most cases, these models were not built for scale. They were built for a single user working with them.

I’ve seen cases where an Excel model is shared around by email. Though well intentioned, this is not really collaborative as it introduces substantial lag and increases the risk of version control.

In other cases, the model isn’t shared at all, and all scenarios are built by the IR professional. They may take inputs from Deans, or they may well say “this is what is likely to happen”, after which the Deans engage in some horse trading to move the target up or down based on what they -think- is likely.

Being a Dean In This Process

To other stakeholders, like Deans or Associate Deans, the enrollment forecasting process can be painful. Each faculty has a different set of considerations when planning for the future – enrollment trends, budget pressures, number of faculty on sabbatical and so on. But it’s hard to engage in this process – it often takes weeks to get new scenarios modelled from the IR professional, at which point the answer is no longer helpful. So Deans end up disengaged, and plan their own way – often with a spreadsheet their finance team built, and work backwards to enrollment goals.

Being the IR Professional In This Process

On the other side, it’s also painful. I’ve been there! You want so badly to help, but there’s one of you, and you’re working with outdated technology that doesn’t allow you to move quickly. You have to make slide decks for each enrollment meeting, and they’re incredibly cumbersome and manual. You also have to respond as fast as you can to the AVP of enrollment or finance when a question arises, inevitably bumping everything else. On top of that, you have the rest of your job.

Moving Towards Collaboration

With budgets tightening, and enrollment patterns changing substantially through the pandemic, I’d argue we need to push that pendulum back towards collaboration, while maintaining a cooperative approach where it makes sense.

To get there, I suggest we need three things to start:

1. A revised business process that encourages stakeholders to plan together. This might involve shifting how targets are measured – rather than each faculty being measured against targets independently, perhaps there is a portion that measures how well they do collectively and intentionally, such as making sure that plans of one faculty don’t inadvertently torpedo the plans of another.
2. A way to incorporate additional data points into an enrollment forecast. Within the institution, we should take into account the standard data we can glean from our Student Information System, clearly, but what about incorporating data from our Learning Management System, Constituent Relationship Management System, or even surveys? Outside the institutional walls, data on demographic shifts, housing starts, your competitors, and many more could provide a helpful signal.
3. An interactive enrollment forecasting model, where every stakeholder could work simultaneously on scenarios and see in real time the impacts of changes in intakes, retention, progression, class size, modality, changed curriculum, and so on.

Planning together, with better data, using systems that provide answers in real time is a great way to encourage better enrollment forecasting, and ultimately encouraging Strategic Enrollment Management at your campus.

Need a hand with getting your Strategic Enrollment Management practice beyond just an idea? Let’s connect.