Embedding Data in Review Process to Improve Resource Allocation

Embedding Data in Review Process to Improve Resource Allocation

St. Ambrose University, Private Masters University in Davenport, IA


St. Ambrose University (SAU) is a private university with a total enrollment of 3,184.


The Challenge

Department chairs and deans lacked accessible data to inform and measure the impact of resource allocation decisions. Existing reports included disparate data points and required extensive manual analysis.


The Solution

Using Academic Performance Solutions (APS), SAU was able to use key department-level metrics to inform resource requests and make allocation decisions.


The Results

SAU’s partnership with APS has improved transparency into the resource allocation process. With easily accessible data, the labor-intensive and time-consuming process of analyzing different data points has been drastically reduced. Additionally, SAU has identified opportunities to shift resources to high-demand departments.

Impact Highlights

0 Hours

Time saved by eliminating manual data collection and analysis


Dollars saved by reallocating 2.5 new faculty lines to departments with demonstrated need

Streamlining Department Review Process with Standardized Data

In previous years, SAU’s Faculty Finance Committee (FFC) reviewed data for a few select departments. Using APS metrics and analyses, the finance team was able to create comprehensive department-level reports to measure the health of all departments. By including both operational and financial metrics, department chairs were able to understand how their operational decisions impacted their financial results.

Building Comprehensive Department-Level Reports


40 departments analyzed

18 APS metrics used

APS Analyses Used to Create Departmental Reports

Enrollment Trends

  • How many majors are enrolled in my department’s courses?
  • How have attempted student credit hours changed over time?

Faculty Mix and Workload

  • How many courses are instructors teaching?
  • How has courseload changed over time?

Section Size and Utilization

  • How full are classes?
  • Can we offer courses less often?


  • What is the current distribution of costs in my department?
  • How does this compare to my peers?

Surfacing Resource Reallocation Opportunities Across Departments

Leveraging the reports generated for each department, the FFC was able to engage in data-supported conversations with deans, chairs, and faculty. Together, they reviewed the reports to identify insights and opportunities.

Faculty Finance Committee Meetings

Reviewed reports with academic stakeholders

  • Used departmental reports to facilitate discussions about the current use of resources
  • Asked targeted questions to illuminate existing efficiencies and potential opportunities
checkmark, Improved transparency and standardized process

Improved transparency and standardized process

Department Chair Buy-In and Agreement

Used reports to understand departmental performance and resource use

  • Achieved consensus about which departments to prioritize for resources
  • Did not submit requests to replace five retired faculty lines – allowing SAU to add 2.5 new lines for high demand departments

Faculty Finance Committee Meetings

  • Maximum Capacity

    Accurately document maximum capacity to correctly measure fill rates and instructional capacity

  • Intercurricular Dependency

    Align distinct course offerings with student enrollment trends, such as in departments teaching large share of non-majors

  • Faculty Course Loads

    Balance course loads – particularly for full-time, tenured faculty who currently teach most courses

  • Bottleneck Courses

    Consolidate low-fill sections and reallocate resources to bottleneck courses

Surfacing Resource Reallocation Opportunities Across Departments

Making Data-Informed Decisions with APS.

Administrative Impact

0 Hours

Time saved by eliminating manual data collection and analysis

Academic Planning Outcome


reallocated faculty lines to their Computer Science Program and for a new Analytics Program

Departments Served


departments reviewed, instead of select handful of departments

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