As someone once remarked “running a university is akin to operating all the businesses needed to support a small village. Universities are simultaneously a real estate property management company (residential student housing), restaurant with multiple outlets (dining halls), retailer (bookstore), events management and ticketing agency (athletics and speaker events), police department (campus security), professional fundraiser (alumni development), consumer financial services company (financial aid), investment firm (endowment management), venture capitalist (research and development), job placement firm (career planning), construction company (buildings and facilities maintenance), and medical services provider (health clinic). In addition to these varied functions, higher education institutions are obviously also focused on attracting high caliber students and talented faculty to create a robust educational environment.”

In this first blog post of a blog series I will be discussing Higher Education reporting and Analytics, top metrics used to report on “Faculty Workload “(based on an intensive project experience), current source systems being used by most of Higher Ed institutions and their limitations/ challenges relating to personnel, processes and technology.

I have been assigned to an Extreme Business Intelligence or (Extreme BI) project for one of our Higher Education clients, which ranks in the top three university systems in the U.S, in terms of enrollment. I conducted user driven requirements gathering using an agile approach, broken into iterative development and continuous rapid delivery of working modules and content which feeds the requirements to the RPD for modeling after identifying the facts, dimensions and hierarchies.

What are some of the top metrics for Faculty Workload?

1. Full-time Faculty Overload hours: using this metrics, you will be able to report on the hourly workload assigned to full-time faculty members and the hourly compensation: This metric can be displayed as a hierarchy (assuming you have created the Academic organization hierarchy in the RPD’s BMM) over a time dimension (Academic term or Academic year).

Tip: Some Higher Ed institutions have what’s called a “three year window” for reporting on faculty workload. You can create a three year average using the Calculated item functionality in the front-end.

2. Adjunct Faculty Overload Hours: using this metrics, you will be able to report on the hourly workload assigned to part-time or adjunct faculty members and the hourly compensation: This metric can be displayed as a hierarchy (assuming you have created the Academic organization hierarchy in the RPD’s BMM) over a time dimension (Academic term or Academic year).

3. Pathways Teaching: This metric can be broken down into several analyses to show the different ways that pathways teaching can be shown.

a. Pathways/non-Pathways courses by Faculty Status (Full-time, faculty part-time faculty, other, etc.)

b. Pathways/non-Pathways courses by discipline.

c. Pathways/non-Pathways courses by Academic rank (Lecturer, Professor, Assistant Professor, Associate Professor, etc.)

4. Faculty Profile metric: this metric could contain analysis about faculty demographics and census.

a. Full-time and/or Part-time Faculty distribution by race/ethnicity.

b. Distribution by Gender.

c. Distribution by Age.

d. Distribution by Academic Rank.

e. Distribution by Tenure Status: (Tenured, Tenure Track, Non-Tenure Track, etc.)

5. Student to Faculty Ratio: Using Student FTE (Full-Time Equivalent) and Faculty FTE we will be able to achieve this metric.

a. Undergraduate: Student to Faculty Ratio

b. Graduate: Student to Faculty Ratio

6. Percentage of Workload type (teaching, advising, research, dissertations supervision, etc.) by:

a. University wide

b. Department

c. Program

d. Course

7. Workload exceptions and edits.

a. Over/under appointed hours (This is not the same as contract balance. Based on the appointment hours field and zero hours of active faculty will also be displayed)

b. Teaching on non-instructional: Record view of any teaching assignment recorded without class information.

c. Workload for inactive faculty: Workload that was assigned to faculty with inactive or leave status.

Something to bear in mind:

While these metrics provide important insights and valuable understanding of Higher Ed reporting and organizational complexity. We need to be aware that no single metric is best suited to the analysis of all Higher Ed institutions, departments, programs etc. When dealing with these metrics, each campus, department, and program should be evaluated independently.