3-11--2011
Florida A&M University
Program Productivity Methodology
Introduction
In Spring 2009, the Academic Affairs work group initiated the process of determining the productivity levels of the academic programs within the University. This was deemed necessary as we addressed issues of budget cuts, efficiency and effectiveness.
Methodology
The guiding question for this activity was: "How can the University's scarce resources be used most effectively to serve the needs of students and faculty, and the institutional mission?"
The initial task of the work group was to develop a process for assessing the multiple factors that contribute to the productivity of academic programs. A decision tree was developed which provided a basis for reviewing the academic programs. This framework enabled the work group to conceptualize important factors of productivity and filter the programs through a series of steps designed to address questions of productivity. As a result of faculty input, the decision tree was revised (see Attachment 1) and it led to the development of steps and identification of factors that were utilized later to score each program. The decision tree was also a guide in considering low-scoring programs for suspension, termination or for actions to increase productivity.
As a result of discussions within the work group, the University Budgeting and Planning Committee and with the academic deans, it was concluded that examination of data was a critical starting point for discussions and considerations. Data within degree programs in the following areas would be considered:
- Enrollmentof majors by level
- Degrees awardedby level
- Student FTEs by level
- Sponsored research awards
These factors were selected because they are standard data used by most institutions conducting program productivity reviews. Further, these factors impact program revenue and accountability. Objective data for each of the factors were available through the University data files used to report the official institutional data to national and state agencies.
In addition to the above factors, the University sought input from the academic units. Upon convening focus groups in the academic areas, consisting primarily of faculty,
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participants identified a number of factors to be considered in productivity. All but three were already part of the methodology. The three additional considerations that were recommended by the focus group participants were:
- Productivity perfaculty
- Return on investment
- Productivity in relation to similar programs at peer institutions
These additional factors were integrated in the subsequent analyses as described below. Using the data identified above, the following steps were used to determine program productivity.
1.Scoring model
All academic programs were rated based on the following factors:
- Enrollmentof majors
- Degrees awarded
- Student FTEs produced
- Sponsored research awards
- Cost per credit hour*
- Return on investment (ROI) on research*
*The last two factors (cost per credit hour and ROI research) were added based on recommendations of the academic focus groups.
The work group’s initial analysis, using the first four factors, led to a listing of programs, ranked from low to highproductivity scores. Programs with low scores, possibly indicative of low productivity, were addressed first. All aspects of the low scoring programs were reviewed. Deans were provided with the scoring results and were provided with opportunities to provide additional information to justify outcomes or recommend changes in the identified areas that emerged with low scores.
Upon adding the last two factors, based on focus group recommendations, all the programs were scored again, and ranked anew from low to highproductivity scores.
Following is a brief description of the factors. Bachelor’s degree measures on enrollment, degrees awarded and FTE were weighted by one (1), master’s degree measures by two (2), and doctoral degree measures by three (3), corresponding to the increasing levels of state funding for the respective degree levels.
For a given program, data in each of the factors enrollment, degrees awarded and FTE, were multiplied by the appropriate weight for the degree level and the resulting number was assigned a score. Sponsored research awards were also assigned scores depending on the size of the award.
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Cost per credit hour was considered as an indicator for productivity per faculty as it normalized the credit hours in relation to the instructional cost of a discipline, and the cost was largely determined by faculty salaries. Data for cost per credit hourwere calculated from data in the University’s and the State University System’s (SUS) Expenditure Analysis Reports. For each discipline category, by degree level, the direct cost per credit hour for FAMU was compared to the system average for the discipline. If the FAMU cost was lower than the system average, points were added to the program score. If the FAMU cost was greater than the system average, points were subtracted from the program score.
ROI data for research was calculated using the sponsored research awards for each discipline category and FAMU’s Education and General (E&G) expenditures for research in the discipline. If the discipline ratio of awards to E&G expenditures was greater than one (1), points were added to the program score. If the discipline ratio of awards to E&G expenditures was less than one (1), points were added to the program score.
All of the above led to a composite score for each program. The specifics on the scoring and an example are provided in Attachment2.
2. Model combining indicator of societal need with productivity
Societal need was indicated by whether a program was on the Board of Governors targeted list, in areas of critical needs in education and health, STEM fields, security and emergency services, and globalization.These are also the programs that FAMU has identified as priority areas that the University wishes to build upon.If a program was on the list, it was designated as high need; if not, it was designated as low need. The combination of the indicator of societal need and program productivity (from the score derived from item 2 above) resulted in all programs being assigned to one of four (4) quadrants:
- high need, high productivity
- low need, high productivity
- high need, low productivity
- low need, low productivity
The programs in the FAMU-FSU College of Engineering were not placed in the quadrants, because of the complexities involved as a joint college in which both FSU and FAMU offer identical degrees and share all resources.
Additional Dimensions
Assessing the productivity of programs is a complex task, that cannot be confined purely to quantitative measures. Therefore, upon assigning each program to one of the quadrants in item 3 above, further analyses were conducted, using multiple filters, many of them qualitative in nature, in an attempt to ensure that no important factors were overlooked prior to recommending suspension or termination of some programs. The additional factors include:
- Programs that are central to the FAMU mission;
- Programs that represented the strengths of FAMU and priorities for the future;
- Programs that provided significant potential for the future growth through radical redesign;
- Comparison to productivity of similar programs at peer institutions (the third factor recommended by the academic focus groups).
Next Steps
Initially, programs in the first (high need, high productivity) and fourth (low need, low productivity) quadrants will be identified. After careful scrutiny outlined in the steps above, including the additional dimensions, some programs in the fourth quadrant will be recommended for suspension or termination. Information will be collected on the number of students majoring in the program who will be affected, if any, a plan and a timetable to teach out the students. Subsequently, over a period of several months, the programs in the third quadrant (high need, low productivity) will receive further scrutiny to determine if any of them should be recommended for suspension or termination.
Low productivity programs that remain after this careful review will be asked to provide, within two months, action plans for increasing productivity and to implement those plans, once approved. The implementation of these plans will be monitored over a two year period with the expectation that enrollment data will demonstrate a significant increase. At the end of the two-year period, the programs will be reassessed for continuation.
The slate of academic programs an institution offers is one of the most important factors that determines the future of an institution. As we engage in the restructuring process, decisions regarding maintaining, suspending or terminating programs must be made with thoughtful consideration of multiple factors and a clear vision of the future.
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