As higher education lurches into the 21st century, the lines of distinction between the private and public sector are becoming more and more blurred. From advancement (fundraising) to academics (honors programs) and from housing (residential colleges) to sticker price (the Miami University of Ohio model), there is less and less difference between what used to be very distinct institutional types. Low cost at public colleges meant access. Private colleges provided more choices through the generous use of financial aid. Today both public and private colleges and universities are competing on net price (i.e., sticker price minus financial aid), especially for nonresident students. This competitive playing field is one in which the private sector has over two decades of experience. The public sector needs to catch up fast to figure out how to get the net price (or discount) "right." So, looking to the private sector to model behavior makes sense, at least as a start.
But tuition discounting (currently practiced primarily by the private sector) has come under fire recently in studies such as the USA Group Foundation report released in December 2000 called "Discounting Toward Disaster" and the May 2003 Lumina Foundation research on "Unintended Consequences of Tuition Discounting." These studies point out that, in the aggregate, institutions that have increased their discounts have not seen corresponding improvement in their results (e.g., quality profile, enrollments, etc.). Certainly it is the case that, within those aggregates, some institutions have been successful with discounting strategies, while others have not. We believe that those who have succeeded have done so through a disciplined use of data.
Any IHE embarking on price
sensitivity analysis must ensure
the integrity of its records.
Any institution embarking on price sensitivity analysis has to begin by ensuring integrity and completeness of admissions and financial aid records. Because for the most part admissions and financial aid offices at state-supported institutions had never been called upon to use data from their files to do the kind of analysis necessary to understand price sensitivity, some critical elements may not have been captured in the student information system or may have been "written over." Similarly, many institutions, regardless of sector, have not annually retained financial aid offers for those students who were admitted and awarded but did not enroll. Price sensitivity analysis requires an understanding of enrollment behavior based on the need of the family, the financial aid offer, and other student characteristics. Such analysis is possible only if all information is available on both enrollees and non-enrollees.
One way some institutions have begun to understand differences in student net revenue production is to look at differences in the average net tuition revenue generated by students with different need and quality levels, segmented by in-state and out-of-state students. While very few businesses would survive if they didn't know precisely what customers "paid" to purchase their product or service--in short, what the net cost to the consumer was after average discounts--many colleges (private and public) just now are taking the time to figure this out. Routinely institutions track tuition income and financial aid expenditures in the aggregate. However, they are less likely to examine net revenue generated by a particular population of students. For public institutions the most obvious differential is between resident and non-resident tuition and fees. However, with merit and talent awards as well as need-based aid, it is likely that subpopulations of students within these categories also "pay" at very different levels depending on their quality, special talents, and need. Creating quality, talent, and need matrices that reflect the average net tuition revenue generated in each segment (e.g., low need, low quality; low need, high quality; high need, high quality; and high need, low quality) can be very instructive.
It is also instructive for institutions to be aware of their trends over time. Segmenting by in-state and out-of-state, freshmen and transfers, the type of trends which need to be followed would include:
