University cost management modeling: Moving beyond spreadsheets

Achieving transparency and financial stability in the higher education business model is a complex and difficult task. Business lines intertwine and academic departments, auxiliaries and administrative functions all compete for finite resources. While the higher education operating model has always been multifaceted, changes in student demographics and state funding, fluctuations in graduation rates, low donation growth, and competition are making it increasingly challenging for colleges and universities to deliver a high-quality education in a fiscally sound manner. As a result, leading-edge institutions are implementing a university cost management model (UCMM) to achieve greater insight into their financial performance.

Other solutions — e.g., enterprise resource planning (ERP) systems and spreadsheet-based modeling initiatives — are typically centered on financial reporting requirements. Further, very few of these systems are forward-looking and, commonly, those that are can’t be used to estimate future performance in a scenario-driven manner. Because of their varying levels of cost and performance analysis capability, these solutions have been found to be of limited value when attempting to optimize deployment of institutions’ resources.

In contrast, a UCMM links general ledger, facilities, HR, student records and course schedule data to create a true management information system. These systems can both define historical costs and serve as a baseline for predictive analysis. A UCMM enables informed business decisions based on past performance and anticipated future changes within an institution’s operating and business model.

Start with a current-state analysis
A UCMM solution provides detailed insights into institutional economics otherwise unavailable to university personnel. Looking across departments, courses and programs, student types, and enterprise-wide expenditure data, management gains an accurate understanding of the cost basis for operations, as well as corresponding revenues, delivering an appreciation for how various programs and operational elements affect margins and performance. Through this information-driven approach, management can adjust operations accordingly.
Well-configured UCMM implementations provide answers to current-state questions like these:
  • Which programs and courses are unsustainable? What courses/programs are running at a loss?
  • What is the minimum number of students needed for a course/program to break even?
  • How much time is spent on course preparation as compared with course delivery, course grading and advising?
  • What is the optimal class size?
  • How much does it really cost to educate a student?
  • What is a course’s marginal student or section cost?
  • What is the difference in attrition rates from course to course?
  • What is the fully burdened cost of teaching? How much of the cost of a course or program is direct, and how much is overhead?
  • To what extent is a school or one department supporting another?
  • How are institutional facilities being utilized? Is there spare capacity? If so, where?
  • What is the fully burdened cost of research?
UCMM benefits
Robust and transparent
Reconcilable back to source data
Rapid development with iterative improvements
Extremely flexible and adaptable
Highly automated/low maintenance
Use of business rules and profiles
Multiperiod comparisons
Simultaneous financial and operational analysis
Foundational for predictive scenario mode

Move on to future-state projections
Most importantly, a UCMM enables management to review the future profitability impact of decisions and “what-if” scenarios.
Leveraging historical cost and revenue data from a UCMM provides an understanding of the relationships between resources and outputs. This facilitates development of UCMM predictive models covering a vast array of potential future scenarios, including their financial implications. As a result, institutions are using UCMM predictive models to answer future-state questions such as these:
  • What is the impact of changes to academic workload (teaching, research, community outreach, etc.) on available capacity of teaching pools and support for strategic initiatives?
  • On a course or program basis, what are the effects of changing student-to-staff ratios in support of learner-centered initiatives?
  • What is the sustainable balance of the ratio of full-time to adjunct faculty given effectiveness standards and accreditation requirements?
  • What are the impacts of changes to academic offerings (courses and programs) on both faculty and staff support requirements, as well as overall university sustainability?
  • Where can the institution grow to utilize its existing resources?
  • Will the cost of expanding capacity be met by growth in revenue/margin?
5 steps to an efficient and effective UCMM
1.    Assess data availability, and define objectives. A UCMM system is highly dependent upon good source data. Assessing data availability and quality, as well as determining overall objectives in building a UCMM, is crucial to a successful implementation. Identifying source data deficiencies allows you to adjust the UCMM methodology, or in some cases, delay building a UCMM while deficiencies are addressed.
2.    Build a draft current-state model. A well-built UCMM makes strategic use of high-level business rules and assumptions based on data in existing systems. For example, workload profiles can be created to capture academic time spent on key activities, including teaching, research, community engagement and non-course-related administration. Further, more granular data can expand the “teaching” category and capture effort spent on course development, teaching, tutoring, advising, assessment and grading. In addition, a profile can be created for each course, with detailed information such as student numbers, credit hours, contact hours, course preparation time per hour of delivery, and grading/advising time per student. All this information can be used to establish a data-driven understanding of how university costs and revenues could be allocated across operations.
3.    Refine assumptions in coordination with key constituents. Once the initial draft model has been developed, it can be used as the basis for discussions with interested stakeholders — typically, schools and departments. Review the model and its results to show how underlying assumptions affect the model’s output. With constituents understanding the model, you can work together to adjust assumptions to achieve even higher accuracy. Further, leveraging validated, historical information will facilitate constituents’ determination of data-driven relationships between support resources and key teaching measures, such as student numbers, credit hours and academic personnel numbers.
4.    Collaborate to analyze current-state economics. There is no point in building a UCMM unless it is utilized to effect change. Using the model will promote familiarity with current-state economics, provide insights that may not have been previously available, and deliver immediate evidence that can be used to guide management’s day-to-day academic, operational and financial decisions. For widespread acceptance and use, management should encourage analysis of model results through a cross-functional working group.
5.    Build a predictive model and create forward-looking scenarios. The historical UCMM and its constituent-validated, data-driven relationships provide information essential to building a predictive model, such as academic workload profiles, course profiles and professor/adjunct ratios. Once a predictive model has been developed, you can use it to create any number of complex, forward-looking scenarios to evaluate anticipated or desired institutional future states (see “Predictive model uses”). Further, you can develop comparative scenarios to evaluate the economic impact of different options, providing information vital to decision-making.

Build your future from a historical and predictive vantage point
Universities and colleges are under increasing pressure to control costs without affecting agreed-upon service levels or their overall mission. They are turning to UCMMs to develop a comprehensive understanding of the cost to deliver — and the revenue generated by — teaching, research and auxiliaries, and to gain detailed insight into the drivers of institutional performance.
Through this understanding, decisions can be based on evidence and quantitative data, rather than on subjective judgment and emotions. Importantly, a UCMM produces decision-support evidence, saving time that can be applied to analysis and decision-making to shape future operations.

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