Tools for financial stabilization

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The following “assets” are central to PASSHE’s work stabilizing the system and its university financially. The Board mandates university leadership's use of these assets in exercising fiduciary responsibility for the state systems.

All of the assets are accessible from this page which will be kept updated as assets are added, and include:

• The comprehensive planning process (CPPs)
• Predictive measures of financial distress
• An academic master planning tool
• An Academic program planning tool
• An Enrollment management playbook

Under the system’s financial sustainability policy (2019), universities are required annually to submit three-year comprehensive plans (CPPs) that:

• specify how universities will advance the Board’s priorities by identifying specific goals; 
• identify strategies that will drive progress towards goals; 
• identify changes in their academic program array (think introduction or elimination of degrees, majors, minors, and areas of concentration as well as interest in sharing programs with other universities); and
• provide a budget forecast.

Budgets are built using templates designed collaboratively by system and university leadership as part of the CPP process. Templates require that budgets be balanced, show how scarce reserves are being utilized, and use common data definitions, budget assumptions, and methodologies. 

PASSHE uses four indicators, as shown in Figure 1, to assess universities’ financial health. Except for enrollments, each has a minimum threshold recommended by the National Association of Chief University and College Budget Officers (NACUBO). 

Figure 1. Indicators of financial health 

Using historical data, it is possible in any year to identify universities experiencing trends experienced by the most seriously challenged five and six years before their precipitous decline began. Where universities suffering from enrollment losses don’t adjust expenditure, they log negative annual operating margins, draw down on reserves to balance budgets and depress primary reserves ratios and cash on hand, respectively. In effect, when lined up in this manner, the indicators turn negative, moving from left to right, as shown in Figure 2, which summarizes the results of the annual financial health review conducted for universities in Fall 2019 (the table is purposefully anonymized). Used in this way, the data are an early warning system and can be used to drive organizational adjustment before it is too late.

Figure 2. State System universities’ financial health as measured in 2019. Measures are coded red, yellow, and green in a manner defined in Figure 1 (university names shown in column one are redacted).

The tool supports universities in planning and managing their academic program array in three ways.

1. Calculating instructional and non-instructional costs per full-time equivalent (FTE) student, by course discipline, student academic program, and organizational structure (e.g. department or college). 

2. Calculating revenues generated per student credit hour (again by course, program of study, department, etc.). 

3. Showing workforce demand by regions for graduates by program of study.

It integrates workforce demand data from the Bureau of Labor Statistics with System student enrollment and HR (e.g., payroll) data and data about a university’s program array and departmental structures. Two use cases follow, demonstrating exemplary uses.

Use case 1. Determining the financial viability of a program array. Figure 1 was generated by the AMPT for two State System Universities using 2021 data. It shows the net economic impact of all programs of study represented using the National Center for Education Statistics Categorization of Instructional Program (CIP) data. Blue lines to the right of the central vertical lines represent programs with a positive net impact. The orange lines to the left are ones with negative economic impact. While one expects universities to have a portfolio approach with programs, some, maybe several, programs operating at a loss, the portfolio as a whole has to break even or better. The university on the left operates its program array with a significant positive margin. The one shown on the right is significantly underwater.

Figure 1. Financial net impact of two universities’ academic program array, 2021 data

Use case 2. Supporting academic program planning at the System level. Using a crosswalk between the codes from the standard Classification of Instructional Programs (CIPs) and the Standard Occupational Classification system, universities can evaluate regional workforce demand for graduates from each program of study. Figure 2 shows how the tool is used to assess Physics programs across the System, including their enrollments, regional labor market demand for physicists, and financial viability (e.g., as discussed above concerning net financial impacts). Thirteen physics programs are included in this analysis (3 BAs, 5 BSs, and 5 B.S.Eds.). Programs with the weakest enrolments and the most significant financial challenges are at universities that serve regional labor markets with the lowest demand for physicists. Such analyses drive universities’ consideration about where to curtail program investments in programs or seek to offer them jointly with one or more other universities.

Figure 2. Relative viability of thirteen State System University physics programs 

This tool is available as part of the CPP process. It enables universities to schedule courses efficiently, ensuring faculty are fully assigned to course sections running at or near capacity. It allows academic managers to marry demand (number of credit hours of instruction required by program – degree, major, minor, etc.) with supply (teaching hours available to instructional faculty). Using the tool and including assumptions about the average student-faculty ratio and course section size per program, academic managers can ensure faculty are distributed efficiently and fairly and rationalize the use of contract faculty and overload for permanent faculty.

The playbook includes a policy requiring universities to continually review and revise enrollment management practices to ensure they are current with industry best practices. A related procedures and standards document details how reviews should be conducted and the criteria used. Tools for financial stabilization

The following “assets” are central to PASSHE’s work stabilizing the system and its university financially. The Board mandates university leadership's use of these assets in exercising fiduciary responsibilityfor the state systems.

All of the assets are accessible from this page and include

· The comprehensive planning process (CPPs)

· Predictive measures of financial distress

· An academic master planning tool

· An Academic program planning tool

· An Enrollment management playbook

The toolset keeps expanding and the page will be updated to reflect additions to it.

Under the system’s financial sustainability policy (2019), universities are required annually to submit three-year comprehensive plans (CPPs) that:

· specify how universities will advance the Board’s priorities by identifying specific goals; 

· identify strategies that will drive progress towards goals; 

· identify changes in their academic program array (think introduction or elimination of degrees, majors, minors, and areas of concentration as well as interest in sharing programs with other universities); and

· provide a budget forecast. 

Budgets are built using templates designed collaboratively by system and university leadership as part of the CPP process. Templates require that budgets be balanced, show how scarce reserves are being utilized, and use common data definitions, budget assumptions, and methodologies. 

PASSHE uses four indicators, as shown in Figure 1, to assess universities’ financial health. Except for enrollments, each has a minimum threshold recommended by the National Association of Chief University and College Budget Officers (NACUBO). 

Figure 1. Key to sustainability metrics

Using historical data, it is possible in any year to identify universities experiencing trends experienced by the most seriously challenged five and six years before their precipitous decline began. Where universities suffering from enrollment losses don’t adjust expenditure, they log negative annual operating margins, draw down on reserves to balance budgets and depress primary reserves ratios and cash on hand, respectively. In effect, when lined up in this manner, the indicators turn negative, moving from left to right, as shown in Figure 2, which summarizes the results of the annual financial health review conducted for universities in Fall 2019 (the table is purposefully anonymized). Used in this way, the data are an early warning system and can be used to drive organizational adjustment before it is too late.

Figure 2. State System universities’ financial health as measured in 2019. Measures are coded red, yellow, and green in a manner defined in Figure 1 (university names shown in column one are redacted).

The tool supports universities in planning and managing their academic program array in three ways.

1. Calculating instructional and non-instructional costs per full-time equivalent (FTE) student, by course discipline, student academic program, and organizational structure (e.g. department or college). 

2. Calculating revenues generated per student credit hour (again by course, program of study, department, etc.). 

3. Showing workforce demand by regions for graduates by program of study.

It integrates workforce demand data from the Bureau of Labor Statistics with System student enrollment and HR (e.g., payroll) data and data about a university’s program array and departmental structures. Two use cases follow, demonstrating exemplary uses.

Use case 1. Determining the financial viability of a program array. Figure 1 was generated by the AMPT for two State System Universities using 2021 data. It shows the net economic impact of all programs of study represented using the National Center for Education Statistics Categorization of Instructional Program (CIP) data. Blue lines to the right of the central vertical lines represent programs with a positive net impact. The orange lines to the left are ones with negative economic impact. While one expects universities to have a portfolio approach with programs, some, maybe several, programs operating at a loss, the portfolio as a whole has to break even or better. The university on the left operates its program array with a significant positive margin. The one shown on the right is significantly underwater.

Figure 1. Financial net impact of two universities’ academic program array, 2021 data

Use case 2. Supporting academic program planning at the System level. Using a crosswalk between the codes from the standard Classification of Instructional Programs (CIPs) and the Standard Occupational Classification system, universities can evaluate regional workforce demand for graduates from each program of study. Figure 2 shows how the tool is used to assess Physics programs across the System, including their enrollments, regional labor market demand for physicists, and financial viability (e.g., as discussed above concerning net financial impacts). Thirteen physics programs are included in this analysis (3 BAs, 5 BSs, and 5 B.S.Eds.). Programs with the weakest enrolments and the most significant financial challenges are at universities that serve regional labor markets with the lowest demand for physicists. Such analyses drive universities’ consideration about where to curtail program investments in programs or seek to offer them jointly with one or more other universities.

Figure 2. Relative viability of thirteen State System University physics programs 

This tool is available as part of the CPP process. It enables universities to schedule courses efficiently, ensuring faculty are fully assigned to course sections running at or near capacity. It allows academic managers to marry demand (number of credit hours of instruction required by program – degree, major, minor, etc.) with supply (teaching hours available to instructional faculty). Using the tool and including assumptions about the average student-faculty ratio and course section size per program, academic managers can ensure faculty are distributed efficiently and fairly and rationalize the use of contract faculty and overload for permanent faculty.

The playbook includes a policy requiring universities to continually review and revise enrollment management practices to ensure they are current with industry best practices. A related procedures and standards document details how reviews should be conducted and the criteria used.