11 Shared Governance Data Requirements for Higher Ed

11 Shared Governance Data Requirements for Higher Ed

Professor William Massy of Stanford University recently interviewed around 50 individuals at several higher education institutions across Australia to better understand what academics and administrators really need to support both their day-to-day as well as big picture decision making. He learned that academics want to be involved in the financial management of their institutions to ensure they are sustainable. This makes sense because teaching is the economic engine of the institution and those who are best positioned to impact the financial sustainability of the institution are the academics who actually do the teaching. Below he distills what he learned over the course of this higher ed tour into 11 shared governance data requirements.

In the coming weeks, Professor Massy and Michelle Brooke will expand on each requirement in a series of blog posts with one post dedicated to each of the 11 requirements respectively. Professor Massy will also detail these requirements via use cases in a forthcoming article. In summary, all 11 requirements point to this: proper shared governance requires a shared platform. A single view of the institution that includes data required for both financial management as well as academic management.

1) Analyzing Workload Profiles

Being able to produce data-supported evidence regarding the total teaching output required by the school to support all programs and compare that to the available teaching hours. This will allow schools to identify and report on areas that are under-resourced and appropriately manage areas that may be over-resourced.

2) Understanding Teaching and Research Relationships

Being able to understand how much teaching may be subsidizing research or in some cases vice-versa, in particular at the discipline or school level. This is important for policy purposes and in some cases for budgeting. It requires a good understanding of full costs (direct and overhead) and all revenue generated.

3) Understanding Teaching Delivery Options

Being able to see a detailed view of individual courses broken out into when it is taught, where it is taught, how it is taught – and what program it’s in. This will allow decision makers to highlight areas of duplication that might be consolidated to save costs. In addition, if the institution captures teaching / learning performance metrics then the cost and performance of different options can be compared, e.g. differing class sizes or online delivery vs face-to-face delivery.

4) Identify courses that are candidates for redesign or elimination

Being able to easily compare individual courses/subjects and their respective margins and student numbers, and being able to easily see if that course is integral to a particular program or not. If the course has low student numbers but high margins could we increase students? If the course has low margins but high number of students can we make it more efficient? If low student numbers and low margins can they be eliminated or are they core to the university mission?

5) Identify programs that are candidates for investment or disinvestment

Being able to easily compare all programs currently being offered and all resourcing (people, dollars, buildings) required to support these programs. What investments should be considered to properly deliver these programs or which programs could be candidates for disinvestment.

6) Understanding Marginal Costs

How much does it cost to increase or decrease a course by one student, five students, ten students etc? For departmental or school budgets this requires understanding the detailed cost structures of individual courses, and perhaps direct (local level) variable overheads. At the university level, especially for large enrollment changes, this also requires estimates of the fixed and variable components of central overheads.

7) Price Setting

Being able to provide data-supported evidence on the full costs of both teaching and research programs. Full-cost data are an essential supplement to separately-obtained data on market demand, segmentation, target audiences etc., for teaching programs. Within research, full-cost information is essential for what kinds of projects to seek, designing cooperative research agreements, and working with industry, in particular where research grant proposals are allowed to include nominated overheads.

8) Course and Program Relationships

Being able to easily identify the complex relationship between courses and programs, particularly where a course may be owned by one school but included in a different school’s program. Understand how Course and Program decisions made in one school could have an impact across the institution, and the impact of curricular decisions on costs and margins.

9) Improvement of Program Review

Being able to integrate knowledge of the economics (revenue, cost, margin, and operating details like class sizes and adjunct usage) of each program into the regular program review process in addition to quality and demand considerations.

10) Redesign the Budget Process

Being able to build up a budget based on anticipated teaching and research requirements as expected for the upcoming year (e.g., based on forecast enrollments and research trends), rather than just adding a percentage to last year’s budget. Using the result as a starting point for negotiations will improve transparency and allow academic decision-makers to become more effectively involved in budgeting. Such transparency also will improve understanding of overheads and allow academics to more constructively contribute to discussions about service levels and efficiency.

11) Scenario Planning

Being able to quickly calculate the impact of possible future changes: e.g., changes in Government funding policies, significant increases or decreases in international students, decisions to offer new programs or close old ones, and efforts to boost teaching quality by increasing contact or assessment time.

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