The cost of college has skyrocketed during the last two decades, rising by 429 percent, a rate that’s even higher than the rate for health care. To cover these costs students have borrowed ever-larger amounts resulting in an average debt at graduation now exceeding $27,000. Yet only 50 percent of students pursuing a bachelor’s degree—and 21 percent of those pursuing an associate’s degree—complete their college programs.
Clearly, the great challenge facing higher education today is to contain costs while at the same time improving outcomes—in short, to increase productivity.
Information technology has long been seen as a major key to meeting this challenge, but the results thus far have been disappointing. In this brief we argue that the fault is not with the technology but rather in the ways it has been deployed. Drawing on the work of eminent Harvard Business School professor Clayton Christensen and others, we explain the need for parallel innovations in higher education’s business models and “value networks.” We also urge policymakers to facilitate such innovations by funding more applied research in these and related areas, including higher education’s regulatory and standards environments.
Concerns about college affordability have grown so serious that President Barack Obama issued a warning about the rising cost of higher education in his most recent State of the Union address. At the same time his administration is encouraging innovation in higher education through such initiatives as First in the World and Race to the Top: College Affordability. While we applaud such initiatives it is important to note that these initiatives are far more likely to succeed if they are informed by an understanding of the differences between sustaining and “disruptive” innovation and the roles that new business models and value networks play.
The theory of “disruptive innovation”—the notion that certain innovation can improve a product or service in such a way that it creates new markets that displace existing ones—was developed and advanced by Christensen in the 1990s. According to Christensen, who has studied the evolution of many industries, disruptive innovation occurs when sophisticated technologies are used to create more simplified and more accessible solutions to customers’ problems—solutions that are often less high performing than previous technologies but whose price and convenience attract whole new categories of consumers. The first generations of transistor radios, desktop computers, and MP3 players are examples. These new solutions—innovations to existing technologies deployed through new business models—gradually improved to the point where they displaced the previously dominant solutions. Christensen’s key point, however, is that new technologies like these cannot achieve their transformative potential without compatible changes in their industry’s business models and value networks, which in turn may require shifts in the standards and regulatory environment.
Innovations in business models have occurred in most sectors of our economy, from manufacturing (Nucor Corp.) to music (iTunes) and from health care (Minute Clinics) to retail (Amazon and eBay). In each, technology drove new ways of doing business to create more value for customers. Recent reports have highlighted emerging business models that may have similar potential in higher education, including those represented by Western Governors University, MITx, Carnegie Mellon’s Open Learning Initiative, and the leading for-profit institutions. These business models exhibit many of the features of what experts call multisided, unbundled, and open business models. Some observers believe they have the potential to dramatically change how instruction and research are delivered to expand access, reduce costs, and facilitate degree completion.
Building on CAP’s previous work in “Disrupting College and Guiding Innovation in Higher Education,” this brief begins by explaining Christensen’s analytical framework. It then focuses on one component of that framework, business models, and explains some important types of them. We then explore how new higher education business models could better harness recent advances in information technology and thereby achieve dramatic improvements in learning and credentialing, research and development, and business management. Lastly, our brief examines the policy implications, especially for the federal government’s applied research budget, our objective being to help policymakers understand what works well and what has the potential to be successfully replicated on a large scale—to “go to scale.” Specifically, our policy recommendations include:
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