Many colleges and universities must respond quickly to pandemic-induced budget shortfalls in order to avoid unacceptable drawdowns of their reserves or even more severe financial disruption. However, the pandemic also may have upended their business models to the point where significantly new strategies must be found. They need to “Build Back Better” rather than simply close their budget gaps.
My September blog, Out of Crisis, Strategy!, described why, without the use of special tools, the urgency of gap-closing so easily crowds out the participative creativity needed to find good strategies. This blog digs more deeply into how today’s predictive academic resourcing models can resolve the tension. Details can be found in chapter five of my Reengineering the University and chapter six of Resource Management for Colleges and Universities.
A Multi-Year Planning Framework
Juxtapositioning thoughtful strategy development with urgent immediate action requires a planning framework that guides the short-run actions into channels that are consistent with the emergent longer-term direction. The framework sketched in the tableau divides the process into three phases: the “Budget Year” (during which urgent actions may need to be initiated), a “Horizon Year” (which reflects the longer-term strategy), and one or more “Transition Year(s)” for changing the institution. It has been adopted by a variety of schools since my colleagues and I developed it at Stanford in the 1970s. While created before modern academic resourcing models existed, the tableau provides a useful framework for deploying those models.
The example shows a current deficit of $15 million that’s forecast to grow to more than $32 million in the Horizon year (2024). (These figures are circled in the tableau, along with others I’ll get to later.) The gap stems mainly from enrollment erosion in the school’s current programs as taught with conventional methods, which tend to lock in the current cost structure. Applying the usual approaches to cost-cutting and income-enhancement at levels sufficient to solve the problem will cause huge difficulties if, indeed, they can solve it at all.
Changing the program portfolio and modes of teaching offer much better prospects, but such changes rarely can be accomplished in a single year. New offerings may need be designed and organized, contracts renegotiated or allowed to expire, and the organization prepared to accept disruption. Low-hanging fruit can be targeted during the Budget Year, but serious change usually requires a multi-year framework like the one presented above and elaborated in the diagram below.
The diagram highlights how the institution’s target scenario “pulls” the earlier decisions in desirable directions even though fruition won’t come until the Horizon Year. Decisions about how fast to reduce the deficit (which is one of the most important administrations and governing boards must make) trade off the cumulative amount to be drawn from reserves (almost $84 million in the tableau) against the time needed to identify and implement the desired longer-term strategy.
What remains is how to find the desired Horizon Year scenario. It is here that the new academic resourcing models make a crucial difference. These models allow planners to evaluate alternative strategies for growing, shrinking, or sunsetting programs, boosting curricular efficiency (e.g., by pruning courses), adjusting faculty rosters, and changing tuition and compensation rates. They operate at the level of individual programs, courses, and departments, which provides the granularity needed to effectively inform decision makers, and they are realistic and transparent enough to inspire confidence in the results.
The predictive models allow planners to experiment with alternative future scenarios until they settle on one they consider to be both desirable and feasible. The chosen scenario is not set in concrete (only the Budget Year’s decisions cannot be rescinded), but it does help make the institution’s immediate actions consistent with its desired longer-term scenario—thus reducing the possibility of producing cliffs and cul-de-sacs.
The model might find, for example, that adding reasonable changes in the program portfolio and teaching methods to modest conventional gap-closers can erase the Horizon Year deficit while sharply limiting the cumulative drawdown from reserves. This is not simply a numbers game. As elaborated below, it is based on an interlocking set of detailed assumptions that have been carefully vetted and whose consequences the model has predicted systematically.
What remains after specifying the Horizon Year is to interpolate back to the present while taking careful account of the implementation time-lags. This is not a terribly difficult process, and there is no need to model separate scenarios for each of the transition years. If close analysis of the transitions reveal that certain changes are not feasible, then the Horizon Year scenario can be adjusted accordingly. If conditions don’t change, and until the original Horizon Year becomes the Budget Year, the tableau can be rolled ahead year by year without redoing scenario development.
Importance of a Well-Grounded Predictive Model
To find actionable scenarios, the predictive model must operate on variables that academic officers actually use—not aggregations or abstract combinations that confound key policies and actions. For example, gap-closing usually must involve program-specific enrollments and course utilization, and departmental faculty/staff FTEs and compensation—in other words, on the heart of the academic enterprise. One must “get down into the weeds” of academic work—which, happily, is just what the modern resourcing models are designed to do.
The “Planned FTE Faculty” and “Average Compensation” lines of the planning tableau highlight the models’ distinction between prices and quantities (P’s and Q’s). Space prohibits discussing the many reasons for this distinction, but one of the most important is that planning requires judgments about the consequences of actions taken. Actions involve physical quantities (e.g., numbers of students and courses, size of classes and who teaches them, and faculty teaching loads). In contrast, when compensation levels change the figures for total faculty cost, they mask what’s really happening.
Finally, a well-grounded model permits academic officers to gauge the sustainability of their proposed scenarios. Sustainability requires not only that expenditures not materially exceed revenues, but also that there be no hidden financial or operational liabilities. The former often involve accruals of deferred maintenance and failure to adequately fund reserves. Operational liabilities may involve overly-large class sizes, adjunct usage, and faculty workloads that diminish quality, or workloads and compensation levels that produce burnout and turnover. Modern academic resourcing and financial models provide the information needed to assess both types of liability.