Contributed by:
This pdf proposes a network approach to leadership—one that creates transparency around institutional financial data using business
model analysis and empowers those on the front lines to make data-informed decisions
that improve institutional practices aligned with performance outcomes
1.
Higher Education
Business Models
Leading with Data to Deliver Results
Louis Soares, Patricia Steele, and Lindsay Wayt
2.
American Council on Education
Founded in 1918, ACE is the major coordinating body for all the nation’s higher education institutions,
representing more than 1,600 college and university presidents and related associations. It provides leadership
on key higher education issues and influences public policy through advocacy. For more information, please visit
www.acenet.edu or follow ACE on Twitter @ACEducation.
Center for Policy Research and Strategy
The American Council on Education’s Center for Policy Research and Strategy (CPRS) pursues thought leader-
ship at the intersection of public policy and institutional strategy. CPRS provides senior postsecondary leaders
and public policymakers with an evidence base to responsibly promote emergent practices in higher education
with an emphasis on long-term and systemic solutions for an evolving higher education landscape and changing
American demographic.
TIAA Institute
The TIAA Institute helps advance the ways individuals and institutions plan for financial security and organiza-
tional effectiveness. The Institute conducts in-depth research, provides access to a network of thought leaders,
and enables those it serves to anticipate trends, plan future strategies, and maximize opportunities for success.
The Institute’s higher education program focuses on leadership and higher education workforce trends and
issues. Its financial security program addresses key questions in three thematic areas: lifetime income and retire-
ment security; retirement plan design; and financial literacy and capability.
To learn more about the TIAA Institute’s research and initiatives for higher education leaders, please visit its
website at www.tiaainstitute.org.
ACE and the American Council on Education are registered marks of the American Council on Education and may not
be used or reproduced without the express written permission of ACE.
American Council on Education
One Dupont Circle NW
Washington, DC 20036
© 2016. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means
electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, with-
out permission in writing from the publisher.
3.
Evolving Higher Education Business Models:
Leading with Data to Deliver Results
Louis Soares
Vice President
Center for Policy Research and Strategy
American Council on Education
Patricia Steele
Principal Consultant
Higher Ed Insight
Lindsay Wayt
Graduate Research Associate
Center for Policy Research and Strategy
American Council on Education
This report is the product of a roundtable jointly convened by ACE and the TIAA Institute in September
2015 and related background papers. The initiative was funded by the TIAA Institute.
Suggested Citation: Soares, Louis, Patricia Steele, and Lindsay Wayt. 2016. Evolving Higher Education
Business Models: Leading with Data to Deliver Results. Washington, DC: American Council on Education.
4.
Forward.................................................................................................................................................................................................. i
Executive Summary....................................................................................................................................................................iii
ACE/TIAA Institute September 2015 Convening and Other Sources of Inspiration..................3
Background........................................................................................................................................................................................ 5
The Demand for More........................................................................................................................................................... 5
Shrinking Revenues................................................................................................................................................................6
Rising Prices and Where They Lead............................................................................................................................8
Innovation Is Underway.......................................................................................................................................................9
Business Model Basics.............................................................................................................................................................14
Illuminating the “Black Box” of College Spending................................................................................................. 17
The Challenges and Needs for Financial Transparency...............................................................................18
The Need for Understanding Activity Costs .......................................................................................................21
Network Leaders Needed: Unlocking the Value of Financial Transparency..........................................25
Networked Leadership and Organizations ...........................................................................................................27
Rationale for a Networked Approach....................................................................................................................... 28
Empowering the Front Line and Moving Toward a Culture of Evidence.......................................... 32
Conclusion...................................................................................................................................................................................... 35
Appendix A: ACE and TIAA Institute Convening.................................................................................................41
Appendix B: What Do Higher Education Leaders Need to Know About Institutional
Finance? And What Can Available Data Tell Them?........................................................................................... 44
Appendix C: Financial Data at the Crossroads of Cost Containment and Educational
Appendix D: Key Challenges in Higher Education: An Economic Models Perspective....................61
5.
Evolving Higher Education Business Models
FOREW0RD
Anyone concerned about how colleges and universities can remain viable, and indeed
thrive, in the face of today’s many challenges should read this paper carefully. The ideas
are profound and the recommendations are potential game-changers that challenge the
conventional wisdom. They will help institutions transform themselves—in ways appropri-
ate to twenty-first-century values, market conditions, and technology—to become better
and more innovative.
The authors call for rethinking the university’s “business model.” The idea is not to
become like a business, but rather to analyze how processes, technologies, and resources
are used to deliver value. The model begins with the institution’s “value propositions”: in
particular, meeting the needs of traditional and post-traditional students. (Research and
scholarship also are important, for their own sake as well as contributing to education.)
Next come resources: the mix of people, technology, products, partners, facilities, and
equipment necessary to meet student needs. Processes use resources in particular ways to
deliver on the value proposition, and the so-called “profit formula” considers the revenue
needed to cover the cost of delivering services and maintaining sustainability. The tradi-
tional business model remains fit for purpose in many ways, but the current challenges
have revealed significant flaws. My own work (Massy 2016) examines these flaws in detail,
and proposes some practical solutions. This paper addresses similar issues as it considers
the business model, the cost of teaching, and the need for “networked leadership.”
“Illuminating the ‘Black Box’ of College Spending” may be the paper’s most advanced and
provocative section. Institutions cannot innovate effectively without knowledge of costs
in relation to revenue: both historically, in terms of what they have actually done, and
prospectively in terms of what they might do in the future. This is particularly important
for the cost of teaching, the “business of the business.” The required data go far beyond
what can be gleaned from financial statements or even from conventional cost accounting.
What’s needed are structural models that describe how resources are applied to particular
activities in sufficient detail to allow in-depth understanding of what’s being done at what
cost, and “what-if analysis” of what might be done to effect improvements.
The needed results can be obtained from a new generation of activity based costing
(ABC) models, applied at the level of individual courses, which provide bottom-up infor-
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Evolving Higher Education Business Models
mation about modes of teaching, the resources consumed by each mode, and the cost
of the resources—plus revenues earned and the margins generated (Massy 2016). These
highly flexible models can include quality-related variables such as numbers of sections
and breakouts, average class size, use of teaching assistants and adjunct faculty, and
whether the classes involve online work or special technology. They can readily incor-
porate learning metrics when they become available in particular fields. It is still early
days for these models, but institutions that learn to employ them effectively will empower
faculty and department chairs, deans and provosts, financial executives, and governing
boards to fulfill their responsibilities more effectively.
The paper points out that achieving these benefits will require a working knowledge of
activities, costs, revenues, and margins by faculty and staff across the institution. Such
internal transparency means, inevitably, that the information will become available to
external stakeholders—including government funding agencies. This challenges the tra-
ditional view that internal data should be held closely in order to avoid criticism and sec-
ond-guessing. However, the modern view holds that such problems must be dealt with on
their merits—using evidence-based arguments—because eschewing transparency makes it
impossible for internal parties to use the data effectively.
The last main theme of the paper is that “network leaders” are needed to unlock the
value of financial transparency. Such leadership broadens participation in shared gover-
nance and, at the same time, organizes it around coordinated information and criteria for
systemic improvement. The new leaders “awaken” networks of faculty, administrators,
and others—both within institutions and across groups of institutions—to create deeper
insights about best practices and financial consequences. These networks exist already,
but they operate in an uncoordinated fashion without benefit of common data. Indeed, the
paucity and concentration of data mean that even shared governance (a kind of network)
works mainly through proxies rather than wide participation. One of the network leaders’
key jobs is to “orchestrate” the development of common data sets and decision support
tools like the ABC models described above, and use them to help people align objectives
and get things done. The idea of networked management provides important insights
about how universities can fix the flaws in their academic business models.
William F. Massy
Professor Emeritus, Former Vice President for Business and Finance
Stanford University (CA)
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Evolving Higher Education Business Models
EXECUTIVE SUMMARY
Higher education is more important than ever to both individual opportunity and national
competitiveness. While the pressures vary across stakeholder groups, college and uni-
versity leaders, public policymakers, and students and families are eager for new ways to
deliver and receive a quality and affordable postsecondary education. Moreover, there is a
growing expectation that college and university presidents, provosts, and chief financial
officers will use data to drive decisions, including those about overall institutional expen-
ditures, needed investment in innovation, and the tie between these dollars and student
outcomes. Yet, at many institutions today, leaders are often left to make financial decisions
in the dark. Higher education finance is often viewed as a “black box,” with revenue gen-
eration, spending, and the monitoring of student outcomes often taking place separately
from each other. Investment and expenditure decisions are sometimes made on hunches
or in year-to-year increments.
In answer to these and other challenges, this paper proposes a network approach to lead-
ership—one that creates transparency around institutional financial data using business
model analysis and empowers those on the front lines to make data-informed decisions
that improve institutional practices aligned with performance outcomes. Inspired in part
by proceedings from a September 2015 American Council on Education/TIAA Institute
convening of college and university presidents, provosts, chief financial officers, and
higher education thought leaders and researchers, this paper was further guided by the
business model and networked organization literature.
This paper explores the real possibility that making the black box transparent and deploy-
ing the business intelligence therein are among the keys to re-imagining the academic
enterprise itself. Key takeaways include the following:
Financial Decision Making is Best Guided through Business Model Approaches that
Prioritize Data Transparency
In the case of higher education, the business model lens can provide a useful way of
thinking about the mix of resources and processes used to deliver a high-quality, afford-
able education. A model that prioritizes granular data transparency provides stakeholders
visibility into the connections between expenses, revenues, and educational outcomes.
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Evolving Higher Education Business Models
Among the benefits of this thinking is the ability to explore the implications of cross
subsidies across academic programs and the ability to understand relative return on
investment. This level of transparency in turn requires improved understanding of costs
at the program and course level, ultimately allowing for data-driven program and course
Shared Governance Models Can Adapt to Use “Networked” Tools
True financial data transparency necessitates an enhanced vision of shared gover-
nance. Through the purposeful implementation of the described “networked leadership”
approach—in which leaders increase transparency, empower frontline community mem-
bers, and guide performance standards and metrics—institutions are able to more agilely
respond to environmental demands. Faculty and staff become empowered to make deci-
sions guided by financial data, with the ability to unbundle and re-bundle program deliv-
ery and services in ways that align with their costs in accordance with established network
performance indicators. The network approach, in essence, shifts shared governance from
an emphasis on institutional dialogue and coherence towards institutional performance
based on agreed-upon metrics.
Institutional Practices—and Their Leaders—Must Purposefully Evolve
Change is not a conclusive process but is ongoing—especially change that necessitates a
structural shift in how colleges and universities operate. As the higher education land-
scape continues to evolve, so necessitates the development of network-oriented skills in
higher education leaders. Under the networked model, leaders must continuously work
to embed data-informed decision capabilities at all network levels; promote collaborative,
networked approaches to established performance outcomes; and continue to utilize tech-
nologies that facilitate the use of accessible financial and outcomes data.
Noted management guru Peter Drucker said that “innovation is change that creates a new
dimension of performance.” For organizations with a social mission, such as colleges and
universities, he posited that systematic approaches to change based on good data, insight,
and leadership would allow for innovation with integrity through which institutions might
improve the lives of the individuals they serve. Using new conceptual tools to analyze
financial and academic models, granular financial data to unpack return on investment,
and networked organization approaches to drive efficiency and effectiveness, college
presidents and their leadership teams can systematically innovate within their institutions
with integrity and help boost education attainment, thus serving both their students and
the nation at large.
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Evolving Higher Education Business Models
INTRODUCTION
Colleges and universities are under extraordinary pressure not only to produce more
and better-trained, skilled graduates but also to do so with decreasing revenues. Despite
limited budgets for some, institutions are expected to provide more services for students
and the community. They are further expected to innovate within their curriculum and
co-curriculum by providing new pedagogies, delivery models, high-impact learning
experiences, and technologies. Meanwhile, steadily climbing prices of higher education
frequently hinder potential applicants from pursuing and completing degree programs.
Colleges and universities engage these challenges in myriad ways, including with lead-
ership and management practices based largely on tradition. The management practices
that made U.S. colleges and universities world leaders in the twentieth century are ripe for
evolution. In this paper, we propose a movement away from the traditional shared gov-
ernance approach to a related, more effective network approach that empowers those on
the front line and creates transparency around financial data and decision making. This
transparency would improve resource investments so that innovations are being selected
because they yield outcomes in education.
In this paper, we propose a movement away from the
traditional shared governance approach to a related,
more effective network approach that empowers those
on the front line and creates transparency around
financial data and decision making.
The rise of bureaucratic, specialized education administration carried out by professionals
in the twentieth century enabled the United States to standardize degree production and
to efficiently scale higher education capacity. This incredible achievement supported a
massive expansion of postsecondary degree production over the last 100 years. The man-
agement practices in higher education that facilitated growth include formalized decision
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Evolving Higher Education Business Models
making, annual budgeting and planning cycles, and a separation of administration and
faculty roles and responsibilities such as recruiting and admissions, financial aid, student
affairs, and business affairs. These practices produced well-governed colleges and univer-
sities, but they also move the important discussion on cost of instructional delivery, the
components of cost, and quality of outcomes far from those in the delivery of instruction,
and in some cases to just an elite group of those in planning and decision-making roles.
Today, some colleges and universities are augmenting these traditional management
systems with new, network-aware practices and business models that enable them to more
rapidly change their offerings, better align programs with student and employer needs,
and improve the personal value of higher education for each student. These new net-
work-aware practices include shared governance, but expand upon it to distribute lead-
ership and decision making more broadly throughout the organization with the goal of
improving performance. Similar to the shared governance concept, distributed leadership
is one that maximizes the potential of all organization members by empowering them
through strong lines of communication and collaboration, and harnessing their individual
strengths and expertise in both formal and informal settings (Jones, Lefoe, Harvey, and
Ryland 2012).
These new network-aware practices include shared
governance, but expand upon it to distribute
leadership and decision making more broadly
throughout the organization with the goal of
improving performance.
The network model, while providing overall empowerment to frontline organization mem-
bers, is organized so that ultimate leadership remains within formalized structures. This
version of leadership allows for maximization of the use of frontline organization mem-
bers’ expertise and provides uniform standards for information and for performance used
to evaluate outcomes relative to institutional mission. Business management literature
calls this organization structure a network, and the type of leadership called for is one in
which its leader is the “network orchestrator” who functions as facilitator (Hacki and Ligh-
ton 2001). In their journey to becoming more effective network organizations, colleges
and universities thus explicitly cultivate these network orchestrators, people immersed in
ensuring that the platform for analysis and data needed for assessing inputs and out-
comes of the education process are available to all stakeholders. This person “evaluate[s]
what information is needed at each stage of the value chain and when . . . and present[s]
that information in a clear and consistent way,” functioning as both facilitator and enabler
(Hacki and Lighton 2001, 35).
Leadership that moves institutions toward a network way of functioning is key to moving
institutions toward greater transparency and cost efficiency, and it is, in no uncertain
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Evolving Higher Education Business Models
terms, an enormous task. It requires presidents and other institutional leaders to have a
simple means for understanding their business model and a networked organization way
of thinking to actively sponsor and oversee specific initiatives that mature the financial
transparency of their own institutions (and between institutions), while empowering
frontline staff, faculty, and administrators to make informed decisions that serve the
institutional mission. College and university leaders will need to engage in the hard work
of extracting actionable information from the data in their information systems, leading
their faculty and staff to understand and articulate the real relationships between their
inputs and outputs as an organization, and then executing informed decisions driven by
mission, quality, cost, and revenue considerations. The construction of such a network
will ultimately allow leaders and their institutions to realize the benefits of efficient,
cost-saving measures and pursue business model innovations that could meaningfully
improve affordability, accessibility, learning outcomes, degree production, and institu-
tional health.
ACE/TIAA Institute September 2015 Convening and Other
Sources of Inspiration
In September 2015, ACE’s Center for Policy Research and Strategy (CPRS), in partnership
with the TIAA Institute, convened a small group of college and university presidents,
provosts, and chief financial officers (CFOs) to explore ways to improve the decision-mak-
ing models pertaining to finance and innovation in higher education. Two central themes
emerged from this discussion and inspired this paper: 1) the pursuit of financial data
transparency, and 2) the need for data-driven leadership at all levels of the institution. (See
Appendix A for other convening themes.) Leaders expressed a need for more members
of the campus community to be able to understand the costs and benefits of educational
delivery as a means to better decision making, hence the need for financial data in more
accessible forms. With regard to leadership, participants agreed that such data were
needed to honor and incentivize the strengths of the shared governance model of higher
In conjunction with the September convening, CPRS commissioned three background
papers on financial data and change in higher education (see Appendices B–D):
In a paper titled What Do Higher Education Leaders Need to Know About Insti-
tutional Finance? And What Can Available Data Tell Them?, Donna Desrochers,
Matthew Soldner, and Thomas Weko of American Institutes for Research explore
availability and limitations of institutional and public financial datasets to inform
management and innovation initiatives.
Financial Data at the Crossroads of Cost Containment and Educational Innovation,
by Dennis Jones from the National Center for Higher Education Management
Systems, unpacks available institutional financial data to suggest key financial
measures and conventions for productive educational program delivery and also
theorizes about the application of these conventions to innovative models such as
online and competency-based education.
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Evolving Higher Education Business Models
In their paper Key Challenges in Higher Education: An Economic Models Perspec-
tive, authors Jacalyn Askin and Bob Shea of the National Association of College
and University Business Officers build on their work in the New Economic Models
project to identify key leadership issues as the financial model of higher education
transforms in response to changing economic and policy environments.
The convening and commissioned papers further pushed us to seek out fresh insights on
how financial transparency and leadership could be aligned to enhance higher education
academic and business models. For this, we looked to the business literature, particularly
business model and networked organization theories and analysis. A business model
frame provides a simple means to abstract from the complexity of education delivery into
four categories—value proposition, resources, processes, and profit margin—that allow
us to see where financial transparency can be helpful. The networked organization frame
posits a way to align incentives in distributed value chains to encourage participants to
deliver value that serves consumers and leverages each other’s strengths. This seemed
well aligned with a need to improve upon shared governance for a time of financial con-
straints and innovation imperatives.
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Evolving Higher Education Business Models
BACKGROUND
Understanding how institutions can evolve as networked organizations requires a deeper
look at the conflicting priorities and driving pressures U.S. colleges and universities face
in the current landscape.
The Demand for More
Public policymakers, students, and their families are pressuring colleges and universities
to do more, and to do more for a more diverse population of students. Demand for higher
education continues to grow—enrollment immediately following high school continues
to rise, adults enroll or re-enroll in college later in life, and people seek out more training
throughout their careers. Higher education is under pressure to cost-effectively educate
this increasingly diverse and growing population of students. There is pressure at one end
of the spectrum to continue to fulfill higher education’s role in preparing students to think
critically and express themselves through a traditional liberal arts curriculum, and pres-
sure on the other end of the spectrum to provide students with professional and market-
able skills, with an emphasis on employability. While the spectrum is at some level a false
dichotomy, colleges and universities are nonetheless under pressure to fulfill both.
In order to serve more students, particularly students who come from disadvantaged
backgrounds and who are underprepared for college-level work, institutions make invest-
ments to expand the capacity of their institutional infrastructure. Among other decisions,
institutional leaders may choose to invest in online or virtual presence technologies that
allow them to serve a greater number of students, or they may invest in physical class-
room or laboratory space, student services, or in the size and quality of the faculty who
deliver instruction. All of these avenues for increasing institutional capacity require both
upfront investments and ongoing costs.
In addition to the demand for capacity building, postsecondary institutions face per-
formance criteria by policymakers and the public alike, who want to see more students
completing their degrees and to see those degrees translate into career opportunities.
Students and families expect that the educational investments they make, including any
debt they may incur, will yield a degree with intrinsic and market value that justifies this
investment. States are also zeroing in on performance. For example, instead of allocating
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Evolving Higher Education Business Models
budget dollars based on enrollment, many are using budget models that reward institu-
tions for degree outcomes. Experts say this trend is expected to continue as the number
of states proposing to tie funds to performance grows each year (National Association of
State Budget Officers 2013). Last and certainly not least is attention to access and student
success by the federal government. The Obama administration, for example, has put forth
various efforts to incentivize institutions to contain costs and keep prices down while
also demonstrating the benefits students realize through their educational programs. The
momentum for performance accountability at the federal level enjoys bipartisan support
and is unlikely to subside in its pressure on institutions to be more productive and effi-
Beyond catering to a growing student market and meeting the performance expecta-
tions of policymakers, colleges and universities are still expected to continue other
mission-related functions; for example, research and development growth or workforce
and economic development. In this environment, institutions themselves are the arbi-
ters of contending expectations among students, their families, governments, taxpayers,
voters, donors, corporations, academic associations, faculty, and staff, and the viability
and success of the institution itself as an enterprise. Colleges and universities are rightly
expected to serve multiple and diverse missions, including ensuring learning and prog-
ress for underrepresented students or returning adults. In the context of these various
aims, colleges and universities make decisions—actively or passively—about how their
operations fund, cross-subsidize, and produce their institution’s specific mix of outcomes.
By extension, they decide the distribution of the benefits of those outcomes across a range
of stakeholders. These decisions are easier to make in periods of revenue expansion when
all stakeholders can become at least a little bit better off. But with declining revenues—as
has been the case in recent years—institutions are forced to make choices that require
unpopular tradeoffs.
Shrinking Revenues
The Great Recession dramatically curtailed the growth of government funding for higher
education. From 2006 to 2011, the vast majority of states decreased per-student spending
in real dollars. While federal funds offset some of that loss, little remains, and institu-
tions have sought out other creative sources to “refill” the revenues (Tobenkin 2013). The
Center on Budget and Policy Priorities reports that states are funding higher education 20
percent less today per student than they did in the 2007–08 academic year (Mitchell and
Leachman 2015).
Declining public appropriations per student are not a new trend. Over the past three
decades, college enrollment has continued to rise while the public funds per student for
higher education have not kept pace in real dollars (see Figure 1). A series of Moody’s
Investors Service analyses (Gephardt 2015; Ortiz 2015; Osborn 2015; Sharma 2015) suggest
that despite seeing general improvements in the financial health of the 500 Moody’s-rated
universities, certain institutions will continue to face financial challenges. Analogous to
the phrase “the rich get richer while the poor get poorer,” the rated universities that have
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Evolving Higher Education Business Models
previously demonstrated more financial stability—those with Aaa and Aa Moody ratings
and classified as global/national universities—will demonstrate financial stability due to
diversified investments and less reliance on tuition for revenue. Regional colleges and
universities—those that are often smaller and with less liquidity in their funds to invest
in areas that will draw new students (e.g., academic programs, student life, facilities)—are
more likely to lag behind.
Figure 1. Total and Per-Student State Funding for Higher Education in
2014 Dollars, and Public FTE Enrollment, 1984–85 to 2014–15
$120 $12
STATE FUNDING PER FTE STUDENT (IN THOUSANDS) IN 2014 DOLLARS
Public FTE Enrollment (Millions)
Funding per FTE Student (Thousands)
TOTAL STATE FUNDING (IN BILLIONS) IN 2014 DOLLARS
$100 $10
PUBLIC FTE ENROLLMENT (IN MILLIONS) AND
$80 $8
$60 Total Funding (Billions) $6
$40 $4
$20 $2
$0 $0
Source: Trends in College Pricing 2015. The College Board.
84-85 87-88 90-91 93-94 96-97 99-00 02-03 05-06 08-09 11-12 14-15
ACADEMIC YEAR
Compared to the significant complexity of cost analysis and the uncertainty of its poten-
tial benefits in an education enterprise, institutions often choose much more immediate,
readily available solutions with stronger certainty of success, such as raising tuition or
fees, enlisting differential pricing or fee strategies, or issuing a 100-year bond like The
Ohio State University did in 2012 (Burne 2011). The preference for financial strategies that
focus on the “top line” of revenues rather than on the operational costs that produce the
bottom line for colleges and universities is also driven by the social expectations that staff
have of themselves and of each other in the processes for financial planning, budgeting,
and analysis.
The predominant business models in higher education reward spending rather than
efficiency as it relates to student outcomes. The real but relatively intangible qualities
of educational outcomes provide ample room for faculty and instructors to disagree
with each other, administrators, and other stakeholders on the measures of educational
success, their meaning, and their value, which highlights the challenge of approaching
student outcomes from an efficiency-minded perspective. The revenue-focused business
model and the pliable definitions of success lead to cultures in higher education skepti-
cal about the intellectual reliability of cost analysis and resistant to dedicating energy to
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Evolving Higher Education Business Models
these efforts. In this way, institutional culture reinforces the bias for revenue-enhancing
strategies, rather than margin and productivity strategies.
Nevertheless, colleges and universities need to do more with less. Decreased revenues
and increased consumer and policymaker aversion to rising sticker prices continue to
press campuses to be more productive. Moody’s most recent bond credit rating of the
higher education sector (which was recently positive for the first time in over two years)
highlights that the key financial risk to the sector over the next few years is not further
declines in revenue, but large growth of expenses, which must be mitigated by cost con-
tainment (Bogaty and Smith 2015). To provide quality education and services to students,
colleges and universities will need to continue to offset growing expenses with higher
prices, or navigate the road of cost containment and innovation in new ways.
Rising Prices and Where They Lead
In the face of more demands and diminished revenue sources, higher education leaders
have been constrained to respond to revenue gaps by shifting costs over to students
and their families. In the last 30 years, published tuition and fees have increased by 114
percent in 2015 dollars. While these figures represent published prices, average net tuition
and fees have for the most part risen over the last 30 years as well (see Figure 2).
Figure 2. Net Tuition, Fees, and Room and Board Prices in 2015 Dollars,
Full-Time In-State Undergraduate Students at Public Four-Year Institu-
tions, 1995–96 to 2015–16
Published Tuition and Fees and
Room and Board (TFRB)
Net TFRB
Published Tuition and Fees
$5,000
Net Tuition and Fees
$0
95-96 97-98 99-00 01-02 03-04 05-06 07-08 09-10 11-12 13-14 15-16
ACADEMIC YEAR
Source: Trends in College Pricing 2015. The College Board.
Eventually, the trend must break down. Students will become more cost sensitive as
education takes up a larger portion of their income, choosing institutions that offer the
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best price. This will in turn be most challenging for small regional public universities
and small private nonprofit institutions that have a greater reliance on tuition revenues
(Bogaty and Smith 2015). According to Moody’s credit research, over the next few years
“stress will be highest at smaller, regional public universities with less than $500 million
in revenue, and at small, private universities and colleges with less than $200 million in
revenue” (Bogaty and Smith 2015).
Perhaps the most troubling effect of using tuition and fees
hikes in response to revenue loss is its negative impact on
those most underrepresented in higher education—low-
income students, those from racial minority backgrounds,
and first-generation college students.
Perhaps the most troubling effect of using tuition and fees hikes in response to revenue
loss is its negative impact on those most underrepresented in higher education—low-
income students, those from racial minority backgrounds, and first-generation college stu-
dents. These populations are less likely to access certain types of grants and loan aid, or
to have the liquidity to finance cost increases. The long-term impact can only yield greater
inequity in access to postsecondary opportunity, entrance to graduate and professional
pathways and positions of leadership, and a generation of lost talent. Despite the system’s
built-in bias toward revenue replacement strategies, some institutions are making the
effort to focus on institutional performance by experimenting with an array of innovations
in how they structure, deliver, and assess education both inside and outside of the class-
room. We turn to such institutions next.
Innovation Is Underway
Independent of the financial pressures and increasing accountability for performance out-
comes facing higher education, forward-looking individuals and teams have been harness-
ing engagement in change and innovation to make higher education more relevant and
more efficient. Entrepreneurs and innovators have already disrupted twentieth-century
models of instruction by creating increasingly sophisticated alternative educational expe-
riences that are potentially more engaging and/or cost-efficient. The rise of the Internet
broke the geographic link between teachers and students and enabled instruction to come
to students, rather than students physically coming to class. The emergence of search
technologies, such as those that power Google, made information retrieval and research
activities performed by students as part of their course work exponentially quicker and
more relevant. These disruptions will continue to play out in higher education, as virtual
reality, telepresence, speech-recognition, and other emerging technologies make their way
into the mainstream of instruction. As Eli Noam (1995) shares:
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Evolving Higher Education Business Models
Scholarly activity . . . consists of three elements: the creation of knowledge and
evaluation of its validity; the preservation of information; and the transmission of
this information to others. Accomplishing each of these functions is based on a set
of technologies and economies. Together with history and politics, they give rise
to a set of institutions. Change the technology and economies, and the institutions
must change, eventually. (para. 2)
The proliferation of these information technologies necessarily affects the internal oper-
ations of colleges and universities. But even more significantly, technology has altered
the flow of information and knowledge throughout society and alters higher education
institutions’ relationships with other sectors in relation to the overall knowledge economy.
As Noam (1995) further notes:
The system of higher education is in the process of breaking down. The reason
is not primarily technological; technology simply enables change to occur. The
fundamental reason is that today’s production and distribution of information are
undermining the traditional flow of information, and with it the traditional univer-
sity structure. . . . (para. 23)
The traditional model of higher education is indeed transforming. Take the University
Innovation Alliance, for example. It is a partnership of 11 public research universities
committed to quality education and improving completion and retention rates for low-in-
come students. They are leveraging the predictive analytics and course advising/mapping
(EAdvisor) tools of lead institutions—Georgia State University (GSU) and Arizona State
University (ASU)—to redesign their own business models. Taken together, GSU and ASU
estimate that academic and business process changes enabled by these technology tools
have saved their institutions and students over $16 million (University Innovation Alli-
ance 2015).
Brick-and-mortar institutions such as Southern New Hampshire University are spinning
off both traditional credit-bearing online programs as well as competency-based models
such as College For America, which is designed to provide a low-cost associate degree
equivalent through engagement with employers. Each one of these spin-offs is intended
to create value for distinct types of learners. The traditional online programs for college-
ready yet time-strapped students, for example, and models like College For America are
aimed at students not on a college track but needing to upgrade workplace skills.
Common approaches across the innovations above include course redesign to embed
high-tech and high-touch solutions, data-driven decision-making tools, use of open
courseware to reduce curricular costs, rethinking credentials with competency-based edu-
cation and stackable modules, scaling the use of online education, and integrating robust
community/industry partnerships to augment and inform academic delivery. These con-
stitute changes to the core processes of higher education delivery as described in the next
section on business models.
But traditional institutions are not the only type of player developing new approaches.
Take General Assembly, a so-called “boot camp,” designed to deliver intensive col-
lege-level skill development. General Assembly is combining practical business training
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Evolving Higher Education Business Models
BUSINESS MODELS IN PRACTICE
Activity-Based Costing
When considering financial data and decision-making processes, some
business experts have posited the importance of moving beyond the
annual budget cycle to more time-effective and responsive practices such
as activity-based costing (Worley and Lawler 2006).
The activity-based costing (ABC) approach to budgets and planning is
being adopted by the community college sector and elsewhere in the face
of both financial and accountability pressures and the need to know what it
truly costs to deliver an education. At its core, the ABC approach provides
higher education leaders with an opportunity to make spending decisions
based on activities rather than broad units or functions. Most of higher
education does not have granular information on what the costs of par-
ticular activities are in the production of a course or degree, or how costs
vary for different types of students. Some institutions have taken on ABC
approaches with the goal of aligning their spending in ways that maximize
outcomes for students. One useful guide to implementing ABC notes that
the approach has its limitations, but the benefit is campus engagement
in illuminating spending and possible cost savings of scarce resources in
alignment with campus goals (Hurlburt, Kirshstein, and Rossol-Allison
Campus leaders can drive the activity-based costing maturity of the college
or university through a combination of information system upgrades, talent
upgrades for finance staff, high-touch training for staff and faculty on the
practice of ABC, and sponsorship from the president, in terms of priority of
ABC maturity relative to other projects on campus.
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Evolving Higher Education Business Models
with software coding preparation and close ties to employers to prepare liberal arts grad-
uates for success in fast-paced technology-driven businesses. As such, they are competing
with both career services in traditional undergraduate institutions and, at least partially,
with graduate schools. A final set of disruptive organizations are those exploring ways to
document what individuals know and can do in ways that could challenge the traditional
credentialing process that colleges and universities have fulfilled. Degreed and LinkedIn
are each attempting to document learner competencies regardless of what institution they
attended. Again, these models have close ties to employers seeking skilled staff.
These examples are meant to illustrate that the different resources and processes col-
leges and universities use to deliver education are evolving within traditional institutions
and facilitating the rise of alternative education providers. Yet, little is known about the
financial implications of these new delivery models. In fact, the value proposition for
higher education is evolving beyond the place- and time-based, faculty-led experience
that people usually associate with college. Institutions will likely need to adapt at least in
some ways to prosper in this emerging ecosystem in order to remain relevant and seize
opportunities such as:
• Understanding the nature of change and the potential to closely reexamine
current practices and make significant change.
• Using data to significantly strengthen support and service to all aspects of the
learners’ life as they engage with the institution.
• Understanding the potential big data has to redefine the meaning of lifelong
learning from an institutional to a personal service.
• Redefining the meaning and the structure of career and professional develop-
ment and support through life.
• Dramatically customizing services to individuals at a scale unimaginable 10
years ago.
• Dramatically improving learning in the humanities, math and science with
learners who have not been able to access high-quality opportunities in the
traditional system. (Smith 2013)
The value proposition for higher education is evolving beyond
the place- and time-based, faculty-led experience that people
usually associate with college. Institutions will likely need
to adapt at least in some ways to prosper in this emerging
ecosystem in order to remain relevant and seize opportunities.
Students, their families, industry, taxpayers, and voters are pressing colleges and universi-
ties to deliver more, better, and cheaper educational and research services to their com-
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Evolving Higher Education Business Models
munities and beyond. At the same time, higher education is running up against society’s
unwillingness to incur incremental costs for higher education—both as private citizens
and as government entities.
The shift of the financial burden of paying for college from governments to students
and their families is not sustainable, and has negative impacts on the broader mission
of higher education to improve social equality and justice. With their ability to replace
declining revenues largely tapped out, many institutions will need to embrace innovation
in their operations and their business models in order to thrive in the new century. To do
this effectively, they will need greater visibility into the interplay between activities, costs,
and educational outcomes within their own institutions in order to evaluate and adopt
innovations that significantly enhance their performance. Effective leadership will require
greater levels of financial transparency than are currently typical in higher education.
In the next section, we briefly introduce a business model framework to help us simplify
making sense of the evolving value propositions and attendant academic innovations
described above.
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Evolving Higher Education Business Models
BUSINESS MODEL BASICS
As information and communication technologies have become increasingly integrated
into the economy, academic business scholars have noted that the pace at which firms
reorganize and redesign their use of resources and processes to deliver value to their
customers has been increasing. The term “business model” first emerged from the work of
Norwegian business researcher Erik Brynjolfsson, in the early 2000s, as a way of framing
how new resource and process approaches could be “modeled” for research, simulation,
and analysis purposes. In the United States, the term business model was popularized by
business school professor Clayton Christensen as part of his broader theory of disruptive
innovation. Christensen’s theory, at its core, provides a way of thinking about how new
technologies can impact the way resources and processes are used by firms to deliver
value to customers.
In Disrupting College, Christensen and co-authors (2011) laid out how disruptive inno-
vation theory could apply to higher education by looking at the specific case of online
education as a technological enabler of business model change (see Figure 3).
Figure 3. Workings of a Business Model
the value proposition resources
A product that helps customers do People, technology, products, facili-
more effectively, conveniently, and ties, equipment
affordably a job they’ve been trying
to do
profit formula processes
Assets and fixed cost structure, and Ways of working togeher to address
the margins and velocity required to recurrent tasks in a consistent way:
cover them training, development, manufacturing,
budgeting, planning, etc.
Source: Christensen, Horn, Caldera, and Soares. 2011.
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Evolving Higher Education Business Models
Figure 3 illustrates that a simple definition of a business model is a blueprint for creating
and delivering value and generating revenue needed to continue doing so. While many
experts have different lists of the key components of business models, Christensen and
co-authors’ (2011) formulation includes value proposition, resources, processes, and profit
formula. These are each described below:
• Value proposition. How an organization addresses the targeted customers’ needs
through its products and services and how those will be accessed and priced.
In postsecondary education: Meeting the needs of traditional and post-tradi-
tional students, from liberal arts education for the 18- to 24-year-old to licensure
preparation for a returning adult.
• Resources. The value proposition, in turn, helps determine the mix of people, tech-
nology, products, partners, facilities, and equipment necessary to meet customer
needs.
In postsecondary education: Faculty and staff delivering on recruitment and
outreach, admissions, financial aid, student support services, on- and off-campus
housing, athletics, career services, etc.
• Processes. Resources, in turn, are applied in certain ways to deliver on the value
proposition. Over time, these recurrent ways of working together become formal
processes.
In postsecondary education: Processes that control general education and
program-specific curriculum, credit transfer, academic advising, student life,
cross-subsidy, shared governance, tenure, etc.
• Profit formula. How the organization generates enough revenue to cover the costs
of delivering its services, including the associated pricing strategy. This includes
sufficient revenue to cover fixed and variable costs and a sufficiently robust operat-
ing margin so that it can invest in new products, processes, and markets.
In postsecondary education: The combination of pricing (tuition and fees), pub-
lic financial aid and loans, student enrollment, and estimated time to degree.
In the case of higher education, the business model lens can provide a new way of think-
ing about the mix of resources and processes used to deliver a quality, affordable higher
education. Add to this the financial and performance information discussed in the next
section, and we begin to find new and effective ways to make colleges and universities
academically vibrant and financially sustainable. In addition, by simplifying the processes
used in the business model, college and university leaders are able simulate unbundling
and rebundling academic delivery in different ways. When linked to financial data, these
are powerful tools to help institutions understand costs and revenues of new approaches.
At the risk of radically simplifying the way we approach the higher education business
model, let’s unpack how we get at the financial data embedded in higher education pro-
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BUSINESS MODELS IN PRACTICE
Using a Business Lens
Using a business model lens can provide higher education practitioners,
even those with varying perspectives, with new ways of thinking about and
using resources, which allows for a focus on outcomes while facilitating
cost savings.
Within the value proposition of a public research university, the University
Innovation Alliance is introducing metrics that can measure the effec-
tiveness of course delivery and advising processes that can both increase
outcomes and save resources. For example, implementing eAdvisor has
allowed Arizona State University to help undergraduates select majors
sooner, significantly reducing the number of freshmen enrolled with explor-
atory majors. The average per student cost savings is $31,000 per year
(University Innovation Alliance 2016).
College for America, although still using a business model lens, provides an
entirely different value proposition by using different mixes of highly tech-
nology-enabled resources and processes to meet the needs of employed
students seek to upgrade employer-related skills.
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Evolving Higher Education Business Models
ILLUMINATING THE “BLACK BOX”
OF COLLEGE SPENDING
The current business model of higher education is often analogized to a “black box” in
which spending decisions are often made without linking revenue and output data to
expenditures. Jon McGee acknowledges this challenge:
Unlike a manufacturing industry, which can readily measure and evaluate outputs
per unit of input, higher education has a much less certain production function.
Colleges and universities often struggle with ideas of efficiency and effective-
ness because they lack well-understood or definitive metrics for evaluating either.
(McGee 2015, 138)
William Massy notes that the “black box” of college and university spending is further
exacerbated because of the concept of Bowen’s Law (Massy 2004). Bowen’s cost theory
suggests that as any revenue source comes to the campus (whether through public sub-
sidy, benefactors, or philanthropic organizations), the need for continuation of that stream
of revenue is anticipated and then expected in the following year’s budget (Bowen 1980).
In order to make changes that lower costs and improve
performance, professionals (and students themselves)
should be equipped to understand how different activities
occurring within the institution are related to each other,
and how each drives spending and revenues, with an eye
toward student success.
In short, many institutions will spend all the money they raise and raise as much money
as they can in order to continue enhancing practices deemed valuable. Jon McGee further
posits that Bowen’s revenue theory of cost “sets in motion a never-ending money chase
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Evolving Higher Education Business Models
that at some point may become unsustainable when revenue can no longer be raised
quickly enough to support growing expense needs and wants” (McGee 2015, 131). This
current business model, operating in a market that tends to prioritize revenue generation,
is not sustainable.
Many colleges and universities are at a crossroads, at a point where relying on continued
tuition increases with a backdrop of decreased state support is not viable. Leaders rec-
ognize that revenue growth cannot alone determine spending; rather, spending, revenue,
and output must be linked to facilitate cost containment balanced with performance. This
necessitates the illumination of the “black box” of institution spending decisions; greater
transparency is needed. In order to make changes that lower costs and improve perfor-
mance, professionals (and students themselves) should be equipped to understand how
different activities occurring within the institution are related to each other, and how each
drives spending and revenues, with an eye toward student success.
The Challenges and Needs for Financial Transparency
True business model analysis—information about the linkages between the cost of
campus activities and the quality of educational outcomes—is not gleaned from public
financial disclosures by a given institution. More useful is information pertaining to the
“efficacy of a proposed intervention . . . [and] an accurate estimate of the resource cost
of implementing the treatment.” (See Appendix B, Desrochers, Soldner, and Weko 2016.)
Yet the latter is at odds with the standards for public accounting by higher education for
strategic and practical reasons.
Strategically, institutional leaders behave rationally and competitively, and thus seek to
maintain the confidentiality of internal activity and its associated costs to avoid losing
market share to competitors and to avoid losing their bargaining positions with the
governments, foundations, students, and families who are their suppliers and customers.
Practically, institutions must incur a high cost of time, effort, and trust to capture internal,
financially meaningful measures of activities within an organization. It is also true that
public accounting by higher education is most often driven by the information needs
of stakeholders external to a given institution, not by the information needs of decision
makers within it.
Yet despite these challenges, postsecondary leaders do recognize their need for a different
view of the information that couples the data in their financial systems with information
on the educational outcomes of their programs. According to recent analysis, univer-
sity CFOs in particular anticipate that their institutions’ business models will undergo
significant change in the next 10 years, with only 13 percent of CFOs expressing strong
confidence in the sustainability of their current business models (Jaschik and Lederman
2013). While CFOs understand that business analytics capabilities are an enabler of the
business model innovations they anticipate will need to happen, fewer than half believe
their institutions have the information they need to make informed decisions and are
lacking infrastructure for routine activity-based costing and performance metrics (Jaschik
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Evolving Higher Education Business Models
BUSINESS MODELS IN PRACTICE
Financial Transparency
Some businesses are working toward creating a “lean enterprise,” or one
which an environment of continuous improvement within a company allows
for the distribution of products “with half or less of the human effort,
space, tools, time, and overall expense” (Womack and Jones 1994). A lean
enterprise approach to business necessitates a culture of trust, clarity, and
transparency. Transparent activities ensure “that the upstream and down-
stream collaborators can verify that all tasks are being performed ade-
quately” (Womack and Jones 1994). An example of a business that uses
financial transparency is Whole Foods Market (WFM). WFM provides all
employees with data on company sales and employee salaries; the financial
awareness this creates fosters a “metrics-based culture” that drives pro-
ductivity (Dutta 2009, 29).
To further financial transparency in higher education, Maria Anguiano,
at the University of California, Riverside, proposes a succinct framework
focused on courses as the central unit of accounting. Courses, as the build-
ing blocks of all college programs, are intuitively meaningful to all stake-
holders and are in use by all institutions, regardless of sector or mission. In
Anguiano’s framework, total education spending (amounts taken for the
institution’s financial accounting systems) is categorized into direct and
indirect cost categories that are then allocated to specific courses. The
allocation of costs to specific courses requires the institution to develop
an appropriate model of the relationships between the institution’s educa-
tional activities and its delivery of courses (Anguiano 2013).
With costs calculated by relevant activity, course delivery transforms from
a “black box” with a fixed-cost structure into a set of component parts—a
business model that can be redesigned and improved as a system. Deans and
faculty then have the tools to routinely evaluate the cost effects of changes
and innovations in course delivery, something that can only be accomplished
on a course-by-course basis if activity-based costing practices are not in
place. When deployed across the full network of the institution’s activities,
activity-based costing has the potential to provide leaders with a powerful
perspective for making important strategic and budget decisions.
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Evolving Higher Education Business Models
and Lederman 2013). These CFO perspectives, as well as identified data-point gaps, were
considered by Maria Anguiano (2013) in her proposed framework for institutions consid-
ering a per course cost methodology.
Inward-looking financial transparency becomes immediately crucial for two main reasons:
first, to support academic innovation at the course level, and second, to support busi-
ness model innovation at the institutional level. At the course level, activity-based cost
accounting coupled with information about outcomes and their quality enables faculty
and instructors to engage in meaningful, substantive improvements in the efficiency and
effectiveness of their work. Conversely, the aggregation of activity-based cost account-
ing across the institution provides leaders with a rational representation of their opera-
tions, including greater insight into the cross-subsidies that occur between departments,
programs, and student-level outcomes. This type of modeling then supports the analysis
of change under different scenarios—growing particular departments, adding particular
programs, investments in particular research capabilities—and enables institutions to
forecast their performance against their mission and strategic priorities. This kind of
insight has the potential to further enable understanding of future demand, pricing, and
needs for external support.
Activity-based accounting next enables governing boards to plan and execute systemic
strategies that improve institutional performance and financial health. Richard Staisloff
(2013) states that “to remain relevant and serve the future needs of students, institutions
must shift their focus from inputs to outcomes, from spending to investing” (34). He rec-
ommends that governing boards focus on mission, market, and margin. A focus on mission
aligns the organization to its purposes and the things it does well. A focus on markets con-
nects the organizational strategy to the needs of the public and its demand for educational
services. The focus on margins reveals future strategic opportunities by identifying those
areas where mission and markets come together to produce net revenue for the institu-
tion. This identification requires colleges and universities to link the activity-based costs
of educating students with a granular view of their motivations for enrollment in order to
understand the true economic margins of an institution’s business model.
Aggregating activity-based cost accounting across an
institution also reveals the patterns of cross-subsidy that an
institution has employed in order to maximize its achievement
against its competing goals and makes explicit those areas
where the institution is investing in particular outcomes.
Aggregating activity-based cost accounting across an institution also reveals the patterns
of cross-subsidy that an institution has employed in order to maximize its achievement
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Evolving Higher Education Business Models
against its competing goals and makes explicit those areas where the institution is
investing in particular outcomes. The National Association of State Budget Officers (2013)
identified cross-subsidy patterns across research universities and reports: “Over time,
spending on instruction has declined slightly, and administrative and general support
costs have increased. Lower division education (freshman and sophomore levels) has
historically been a source of ‘cross-subsidy’ to upper division and graduate education, a
spending practice that may be contributing to high rates of attrition in the first two years
of college” (iv). (See Table 1.) This research found cross-subsidy evidence at the level of
aggregate outcomes and aggregate spending. Activity-based costing at the course level
would give leaders and other stakeholders a more granular view of the effective cross-sub-
sidies at their institutions so they could make better decisions about resource allocation
to interventions that yield better outcomes.
Table 1. Credit hour distribution and average instructional costs
Average of four-state cost study (SUNY, Florida, Ohio, Illinois)
% OF ALL CREDITS % OF TOTAL SPENDING AVERAGE WEIGHTED
TAKEN ON INSTRUCTION COST/CREDIT
Lower Division 38 23 1
Upper Division 48 44 1.42
Grad 1 12 23 2.88
Grad 2 4 9 4
TOTAL 100 100 1.55
Source: State Higher Education Executive Officers (2010).
The Need for Understanding Activity Costs
Greater transparency of the cost drivers and revenue engines within an institution
enables higher education leaders to execute strategies in support of mission through the
very practical, relevant exercise of the annual budgeting process. In considering course-
level activity costing, William Massy (2016) posited:
Activity-based costing (ABC), the methodology used in course redesign, offers the
best approach for campus-wide, quality conscious cost measurement and cost con-
tainment. It avoids the serious problems associated with rations, such as cost per
credit hour, and opens the way to better design of course portfolios for departments
and degree programs. (220)
Absent activity-based costing linked to outcomes and their associated revenues, most
higher education institutions construct their annual budgets using across-the-board incre-
mental increases (or decreases) for expenses administered centrally; formulas that set
department budgets based on rates of enrollments or outcomes; or responsibility-centered
budgeting, which delegates out to departments the matching of costs against revenues
(Curry, Laws, and Strauss 2013). As Askin and Shea note in their paper (see Appendix
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Evolving Higher Education Business Models
BUSINESS MODELS IN PRACTICE
Responsibility Center Management
Responsibility center management (RCM), also referred to as reve-
nue-centered budgeting, is essentially a budgeting method whereby units
of responsibility (such as departments) have control over revenues and
While the RCM approach to budgeting is not widely used, a growing num-
ber of institutions have moved toward it or are using a hybrid model that
includes RCM principles. This type of budgeting “transfers revenue own-
ership and allocates all indirect costs to units whose programs generate
and consume them respectively . . . [using] centralized resource redistri-
bution—to achieve balance between local optimization and investment
in the best interest of the university as a whole” (National Association
of College and University Business Officers 2013). In part, the growth in
popularity may be explained by its relevance to innovation as this approach
has built-in incentives to be entrepreneurial. For example, when Temple
University (PA) was in the process of transitioning to the use of RCM, one
faculty member commented that this model “can empower academic lead-
ers of colleges and schools to guarantee that their budgets will follow rather
than lead their academic mission” (Halbert, Huffman, Wager, and Scott
2012, 7; italics added for emphasis).
While RCM has limitations in practice, it represents a direction that is in
line with a networked organizational approach to costs. For example, the
budget process under RCM would require departmental units to discuss
revenues and be transparent about sources, understand the indirect cost
items in their budgets, and debate the priorities of their spending. If the
units are unsuccessful in keeping their budgets neutral or saving overages,
then they must revisit the decisions at the next budget cycle and adjust.
Engagement in this conversation, given the availability of the appropriate
data, could yield substantial innovation at the unit level. It is, however, lim-
ited in its ability to engage the wider college or university and other centers
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D) “traditional budgeting and planning methods” tend to “treat the future merely as an
extrapolation of the past” (3).
Each of these common methods has drawbacks. Budgets constructed using the incremen-
tal method are likely to rely on one-time changes to close gaps between revenues and
expenses, such as outsourcing business services like dining halls or IT support, or across-
the-board budget cuts in areas that are not mission-critical like travel, rather than through
deliberate changes in the budget areas closest to their mission (American Association
of State Colleges and Universities and SunGard Higher Education 2008). An example of
such nonstrategic changes used by one institution include:
. . . across-the-board salary freezes, a 50 percent reduction in travel, and a one-time
window for staff early retirements in addition to an adjusted incentive to an existing
faculty early retirement incentive program. The university did not reduce employer
contributions to employee retirement plans or increase employee health-care
contributions. To avoid further staff reductions, the board decided to draw from
reserves. (Hignite 2010)
Budgets constructed using formulas that rely on enrollment or degree completion metrics
are susceptible to unintended consequences whereby institutions are induced to reduce
quality and “to pass on degrees to students without paying attention to learning results”
(National Association of State Budget Officers 2013, 14). And while responsibility-centered
budgeting has the advantage of pushing the responsibility for financial management
deeper into the organization, it leads to local optimization whereby better institutional
strategies that span departments are ignored, since the delegation model does not
support the emergence and approval of those strategies. And responsibility-centered
budgeting wastes organizational energy on debates over allocation of charge-backs for
centralized services (such as facilities, utilities, etc.) that neither improve overall revenues
nor decrease overall costs (Curry, Laws, and Strauss 2013). While the responsibility-
centered model produces better budgets, it is prone to the same inattention to innovation
in delivery of core education services, just at the department level rather than the institu-
tional level.
The focal point of evolving higher education finance and business models should include
greater visibility into the actual activities and associated costs for the value created by
higher education to meet its key mission: producing educational outcomes for students,
increasing the store of the public’s intellectual capital through research, and achieving the
wider benefits that spill over to local, state, national, and global communities. Institutions
regularly use a broad set of criteria to make decisions about curriculum, instructional sup-
ports, student support services, developmental education, and online delivery that have
significant implications for cost efficiency and program effectiveness. However, few ana-
lyze the financial and performance impact of these changes by evaluating the expected
improvements to student outcomes and institutional missions across alternative courses
of action, and few assess the actual cost savings of the changes that they make. For
instance, one survey of state colleges and universities indicated that more than half of the
participating institutions cut costs through the use of adjunct faculty and online courses,
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Evolving Higher Education Business Models
though almost none record the results of their cost savings efforts. This makes it difficult
to determine effectiveness and/or share results with others in a useable format (American
Association of State Colleges and Universities and SunGard Higher Education 2008).
The next era of higher education finance can and should be concerned with the internal
management accounting practices that empower decision makers within colleges and
universities to make choices that improve the economic performance of their institutions,
and evaluate the ways in which choices relate to institutional mission, especially student
success. When adopted across a college or university, the activity-based cost and outcome
measures discussed above will give institutions the capability to make better decisions
about efficiency, innovation, and strategic growth. In addition, analyzing this type of data
at the activity level allows for these measures of cost and output to be balanced with the
consideration of outcome quality to avoid what many fear, which is a “sacrifice [of] quality
in the interest of saving money” (Massy 2016, 112). Institutional vision is in fact grounded
in internal operations. A clear understanding of how an institution is financed—down to
the course level—provides not only presidents but faculty, staff, and other on-the-ground
stakeholders with a powerful tool for achieving that vision.
The next era of higher education finance can and should
be concerned with the internal management accounting
practices that empower decision makers within colleges
and universities to make choices that improve the
economic performance of their institutions, and evaluate
the ways in which choices relate to institutional mission,
especially student success.
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NETWORK LEADERS NEEDED:
Unlocking the Value of
Financial Transparency
Leadership that is mission-driven and fosters engagement by a wide network of campus
stakeholders beyond executives and managers is by definition network leadership. The
Corporate Executive Board describes network leadership as one that “involves establish-
ing strong network performance by building, aligning, and enabling broad networks both
internal and external to the organization. Network leadership is more about influence than
control; it is also a more indirect than direct form of leadership, requiring leaders to create
a work environment based on autonomy, empowerment, trust, sharing, and collaboration”
(Corporate Executive Board 2014, 11).
A conventional leadership framework involves transformational and transactional leader-
ship. Network leadership expands on this and “requires leaders to drive a broad spectrum
of performance: setting the agenda, leading individual employees and work teams, and
establishing the networks required for enterprise contribution” (Corporate Executive
Board 2014, 12). As facilitators of network leadership, and in the context of institutional
finance, presidents and CFOs expand the discussion of financial data and budgets to all
individuals who are directly responsible for student and other outcomes central to the
institution’s mission. In short, the full community understands how money moves, what
things cost, and how this information is tied to campus mission and goals.
Endeavoring to be a networked organization is not an end to itself, but a pathway to
improving performance outcomes for the organization. The foundation of this organiz-
ing principle is achievement of the educational mission of the institution through the
empowerment of stakeholders at the front line who are in the best collective position to
achieve it. In the 1980s, U.S. businesses and other organizations aggressively adopted
the practices of Total Quality Management with the goal of creating organization-wide
changes that ensured continuous improvement through “consistent efforts to achieve the
objective for a customer through systemic efforts for the improvements” (Thamizhmanii
and Hasan 2010, 204). In the case of higher education, empowering individuals to engage
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BUSINESS MODELS IN PRACTICE
Prioritize Organizational Learning
to Improve Frontline Operations
Within networked organizations, leaders need to “value and nurture orga-
nizational learning” (Mukherjee 2009, 26). This means that leaders within
organizations need to facilitate learning by creating processes in which
pertinent information on productivity is collected, analyzed by those with
the skills to do so, and then shared in accessible formats with employees
throughout the company. This “plan-and-execute” process with embedded
“sense-and-response” practices requires effective collaboration among all
network partners.
This organizational learning dynamic can be seen, for example, in busi-
ness practices such as those at Zingerman’s, a deli in Ann Arbor, Michigan
(Spreitzer, Porath, and Gibson 2012). Zingerman’s “uses open book man-
agement to share information in a transparent way through the organiza-
tion. . . . Leaders of the operating units outline the company and the unit’s
numbers on a white board and then discuss performance issues. Employees
need to ‘own’ the numbers and offer a plan on how to get back on track
when the numbers indicate a deviance from the plan” (160).
Higher education leaders should place a priority on the college or uni-
versity’s need to learn as an organization in ways that empower frontline
staff, such as providing training and incentives for participation, to improve
student success outcomes. In the higher education context, leaders can
facilitate the use of data about student success to inform deliberations and
decisions about the curriculum and other institutional priorities. Campus
leaders should ensure collaborative learning opportunities between aca-
demic and student affairs staff and faculty and tighten the philosophical
and operational linkages between academic and student affairs (Kezar
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in analysis of inputs, outcomes, and their relationship to cost would create an opportunity
for collaboration towards the goal of student success. Kezar (2005) argues that higher edu-
cation stakeholders need to come to a shared understanding about their mission and that
collaborative, shared leadership is instrumental to achieving student success. A network
leadership approach is the ideal approach for facilitating that shared understanding and
the engagement around it.
Networked Leadership and Organizations
Cultivation of network leadership at all levels of a college or university can serve to
empower and awaken the community to unlock the value of financial transparency for
themselves, their students, and their stakeholders. Networked organizations are ones in
which leaders focus more on teams and not on linear management. Leaders “adopt strate-
gies that promote collaborative action . . . and learning” and create technologies that allow
for analysis by any and all stakeholders (Mukherjee 2009, 26). According to Hacki and
Lighton (2001, 34–35) some key principles for the networked organization include:
• Uniform standards governing the exchange of information.
• Rigorous performance standards maintained mostly through customer
evaluations and partner incentives built into the network.
• The sharing of benefits generated by the network with all partners.
• An online presence for all key business processes.
• The development and dynamic testing of new opportunities with network
partners.
Networked organizations link network partners (various departments and functions
within a college or university) through an established communication paradigm, have
rigorous expectations (which are less likely to be held in a centralized structure), and
provide benefits to all partners and the network as a whole. This structure functions
through the use of standardized communication and technology, utilizing the strengths
of network partners, and facilitation of collaboration (Hacki and Lighton 2001).
Within this framework, it is the network orchestrators who design and monitor the net-
work’s communication and performance standards, keeping the needs and experiences of
the customer (students and other stakeholders) paramount. Orchestrators are immersed
“in the underlying software that makes it possible to construct an information standard,”
“evaluate what information is needed at each stage of the value chain and when,” and
“present information in a clear and consistent way” (Hacki and Lighton 2001, 35). They
function as facilitators and enablers, allowing network partners to benefit individually and
to benefit the entire network. It is not difficult to imagine a scenario where institutional
research offices provide both a platform and training for various campus stakeholders
to utilize system data to conduct analysis of any kind—and in fact some universities are
already implementing this approach.
If a college or university wanted to establish opportunities for engagement around edu-
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Evolving Higher Education Business Models
cational inputs, costs, and outcomes, it could adopt the principles outlined by Mukherjee
• Embed sense-and-response capabilities in normal plan-and-execute process.
• Adopt strategies that promote collaborative action among network partners.
• Value and nurture organizational learning.
• Deploy technologies that enable intelligent adjustment to major environmental
shifts (26).
Yet merely providing the opportunity to engage as a network is unlikely to be sufficient
without both training and incentives for college and university employees to engage in
the work. This is where the shared understanding of mission becomes important, and
incentives for engagement are needed. In turn, this level of engagement should be paired
with clear performance metrics for the expected outcomes the network of engaged faculty,
staff, and other contributors should produce for students. College and university leaders’
task is to balance the importance of empowering individuals with using standards and
metrics to drive the performance of the entire network or value chain of academic deliv-
ery. This creative tension holds the promise for a shared governance model for today’s
institutional realities.
Yet merely providing the opportunity to engage as a
network is unlikely to be sufficient without both training
and incentives for college and university employees to
engage in the work. This is where the shared understanding
of mission becomes important, and incentives for
engagement are needed.
Rationale for a Networked Approach
Higher education leaders well understand the potential value of innovation, as discussed
in the earlier section; however, the process by which ideas are generated, tested, and built
into the formal structure of the college or university may be unintentionally hindered
by hierarchal processes and structures focused on maintaining the current organization
rather than inventing the new. Absent a network approach, decisions in an organization
are made by senior leaders operating with limited and/or outdated information. This
traditional model lacks the flexibility and responsiveness that continuous improvement
requires and lacks the capacity and incentives to nurture more substantial innovations in
educational programming.
Some would argue that not only do hierarchical structures squelch innovation, they make
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BUSINESS MODELS IN PRACTICE
Data Analysis and the Front Line
Knowledge management (KM) is a practice initially used in the business
sector as a framework to “illuminate and address organizational obstacles
around issues of information use and access” (Petrides and Nguyen 2008,
2476–2477). In practice, KM encompasses the interactions among people,
processes, and technology and how these interactions facilitate gathering
data, turning data into information, using information to build knowledge,
and allowing knowledge to guide action.
Research in the higher education sector, specifically research conducted
at the community college level, has indicated that institution members at
different levels (including department heads, faculty, and staff) both want
and need data to use for decision making (Petrides 2004).
This desire to use data for decision making creates an opportunity for
leaders in higher education. Leaders can construct opportunities for fac-
ulty and staff to engage in data analysis—specifically, cost analysis. First,
to do this, there must be significant opportunities for sharing information,
exchanging ideas, and communicating institutional priorities. Second,
leaders need to work with institutional research and budget offices to
identify ways to make data regarding those institutional priorities available
for analysis. Their objective is to create a platform, guided by mission, that
enables frontline employees to understand the impact of their own role on
the institution’s priorities and to co-develop plans for working toward goals.
Within a networked organization that is guided by the use of data for deci-
sion making, the campus culture should encourage all institution members,
including students, faculty, and staff, to think about and discuss student
outcomes for success, how money moves through the college or university,
and how the two are related.
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BUSINESS MODELS IN PRACTICE
Formalized Networks
Informal and social networks are more representative of information
exchange and knowledge that facilitates day-to-day work than are organi-
zational hierarchical structures; leaders within organizations can capitalize
on this by formalizing informal networks (Bryan, Matson, and Weiss 2007).
One way to visualize business place networks is to picture the office water-
cooler, the cliché informal office networking location. Here, organization
members informally discuss, among trivial topics, information related to
daily business operations. Some companies have worked to create more
formal means to facilitate the communication flow through the network.
For example, when working toward more lean processes, one of the steps
Jefferson Pilot Financial took was posting company performance results,
including hourly productivity rates, alongside company expectations.
Initially, some employees “feared that the posted results would be used to
assign blame or punish low performers” but “the displays became rallying
points for celebrating successes and encouraging the team to set net per-
formance records” (Swank 2003).
In a higher education context, leaders can create practices in which existing
ad hoc networks of mutual self-interest are formalized so that the institu-
tion can capitalize on its idea generation and information exchange. This
can be done by naming a leader, focusing the network on specific topics
(and providing network members with needed data on these topics), and
putting in place an infrastructure that supports an ongoing exchange of
ideas (Bryan, Matson, and Weiss 2007). This process can facilitate both
data transparency and employee empowerment. First, as informal networks
are made formal, pathways for the exchange of knowledge, including key
financial data, are created. Second, as faculty and staff—those on the front
line of the institution—are provided with essential institutional data and
information, they are empowered to make informed decisions in line with
the college or university mission and performance expectations.
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