forecasting ftes using a yield projection model
DESCRIPTION
Forecasting FTES Using a Yield Projection Model. Sam Ballard, Research Analyst Daniel Miramontez, Research Analyst San Diego Community College District. Presented at the 2009 RP/CISOA Conference Tahoe City, CA: April 27, 2009. San Diego Community College District. Enrollment. - PowerPoint PPT PresentationTRANSCRIPT
Forecasting FTES Using a Yield Projection Model
Presented at the 2009 RP/CISOA ConferenceTahoe City, CA: April 27, 2009
Sam Ballard, Research AnalystDaniel Miramontez, Research AnalystSan Diego Community College District
San Diego Community College District
Enrollment
• FTES for 2007-08 = 41,925– College Total = 31,938– Continuing Education Total = 9,987
• Number of sections offered at colleges in 2007-08 = 11,132
• Duplicated Headcount = 397,615• 3.6% increase in Fall 2008 growth
Office of Institutional Research & Planning Organizational Chart
Office of Institutional Research & Planning Scope of Work
Research and Information for:• Program and services– Program review reports (i.e., EOPS, TRIO, etc.)
• External accrediting agencies– Accreditation self-study reports for WASC/ACCJC
• Accountability– ARCC report
• Planning and decision-making process – Productivity and projection reports (i.e. FTES)
FTES Yield Projection Model
• Yield Model– Adjusts to the number of sections being offered in
the current term– Takes the previous yields multiplied by the current
sections being offered
Purpose
• Primary function of the FTES Yield Projection Model– Manage growth and enrollment
• establish growth targets– Budget development
• budget guidelines • Who uses the information– Chancellor– College Presidents– Vice Chancellors
• Instruction, Student Services and Business Services• FTES Yield Projection Model Pilot Testing– Last 3 years (06 07, 07 08, 08 09)
Method
• Start with FTES file from comparable term from previous year
• Make exclusions– i.e. cancelled sections, non-residents
• Total by different variables– i.e. accounting method, subject, course number
• Calculate number of sections per course– i.e. 27 sections of PSYC 101
Method Cont.
• Calculate FTES for the total number of sections– 100.35 FTES for 27 sections
• Calculate yield by dividing total FTES by the number of sections– i.e. 100.35/27 = 3.72 FTES per section
Method Cont.
• Now get file with current sections offered• Aggregate the number of sections offered– Current term is offering 20 sections of PSYC 101
• Match prior year’s yields to current term– Unique ID (PSYC101)
• Multiply number of current sections by previous year’s yield– i.e. 20 sections * 3.72 yield = 74.4 FTES
Method Cont.
• Adjustments– Change in number of sections– CT – ((CT-PT)/PT)– Multiply adjusted sections by .99
• Increase Yields– Yield can be adjusted according to current trends– yield + 0.10
Results
• In the past three years we projected spring during fall– Spring 2006 to 2007• The projection was off by 243 FTES• -1.81% error
– Spring 2007 to 2008• The projection was off by 654 FTES• -4.78% error
Results Cont.
– Spring 2008 to 2009• The projection was off by 605 FTES• -4.44% error• Data as of 4/8/09
Discussion
• Limitations– Can only be calculated when the schedule is ready– New courses are given a marginal mean– Only used for three years
• Possible Improvements– Add factors
• unemployment rate• fill rates• physical improvements• % increase from term
Worksheet Exercise!
Discussion Questions
• What do you see as other limitations of this model?
• What are other ways to improve this model?
• How does this model compare to other projection models?