Hamel and Prahalad (1991) give an example of how a disruptive technology, the video recorder, developed as a commercially successful product: ‘Sony introduced a reel-to-reel video tape player aimed at the consumer market as early as 1965. And its U-Matic VCR, launched in 1971, was also intended for the consumer market… Matsushita, JVC’s parent, likewise made several attempts to crack open a consumer market for video tape players before finally blanketing the world with its VHS standard’ (p. 87). The example suggests disruptive innovations do not simply emerge, prosper and come to dominate. Instead, they are characterised by trial and error, and by repeated iterations. If this approach comprises a pattern for success then the ability of any organisation to reinvent becomes crucial for its success. The authors illustrate the point, ‘Speed of iteration refers to the time it takes a company to develop and launch a product, accumulate insights from the marketplace, and then recalibrate and relaunch. Other things being equal, a company with a 12-month iteration cycle will be able to close in on a potential market faster than one with a 36-month cycle’ (pp. 87-88), and then supply an example in the form of Toshiba’s conduct in the laptop computer industry: ‘by 1991 Toshiba had discontinued more laptop models than some of its flat-footed competitors had launched’ (p. 88).
The success of a disruptive innovation, therefore, is determined as much by market conduct as by technological innovation. Christensen changed his own terminology from disruptive technology (1997) to disruptive innovation (2003) to foreground the idea that disruption is not a technological phenomenon, but an environmental one, in the sense that, if the innovation finds a receptive environment in which to grow and adapt, then it is more likely to succeed. Moreover, argues Christensen, the innovation is most likely to succeed when the innovation is competing against non-consumption.
In terms of how to manage an innovation, therefore, adaptation is crucial, as is a willingness to persist if initial attempts are not successful. Hamel and Prahalad argue, ‘New markets are seldom created by some mysterious process of spontaneous generation’ (p. 82). In addition, a willingness to take an imaginative approach to understanding specific markets is an advantage: ‘In one Japanese company, senior technical officers spend as many as 30 days a year outside Japan talking to customers. The goal is not to solve technical problems nor to close a sale but to observe customers and absorb their thinking… the objective was… to blur organizational and career boundaries’ (p. 86). Setting aside the unclear nature of what is meant by ‘absorb’ here, there is a sense that customers can be trusted to have good ideas and input of their own, and if this bottom-up approach is brought to product development, it is more likely to results in products that engage constructively with customers. Furthermore, the blurring of boundaries enables new insights to be formed, as people adapt the tools at their disposal, and adopt new practices.
Transferring this understanding of disruption to technology-enhanced learning in higher education, the failure of traditional Virtual Learning Environments to generate new approaches to learning and teaching (Blin and Munro, 2008) does not comprise the failure of Technology-Enhanced Learning (TEL). Instead, developers of TEL need to learn from students’ practices and be willing to try out, adapt and reinvent a range of technologies to support and enhance learning and teaching. Moreover, this process of experimentation can be informed by pedagogies suited to TEL, and, in turn, inform the development of such pedagogies. For example, in Engestrom’s expansive learning (2001), the introduction of new technology tools alters the division of labour within a learning community, as students may well have greater proficiency in technologies than their lecturers (Prensky, 2001; Scanlon and Issoff, 2005). Equally, if lecturers can work with the shift from a vertical to a horizontal relationship with their students (from exposition to support), then appropriate pedagogies can emerge to utilise fully the learning and teaching potential of new technologies, rather than cramming new technologies to existing and often uninspiring pedagogies (Christensen, 2011).
References
Blin, F. and Munro, M. (2008) ‘Why hasn’t technology disrupted academics’ teaching practices? Understanding resistance to change through the lens of activity theory’, Computers and Education, vol. 50, pp. 475-490.
Christensen, C. M. (1997) The innovator’s dilemma: when new technologies cause great firms to fail, Boston, Mass., Harvard Business School Press.
Christensen, C. M. and Raynor, M. E. (2003) The Innovator’s Solution: Creating and Sustaining Successful Growth, Cambridge MA, Harvard University Press.
Christensen, C. M., Horn, M. B., and Johnson, C. W. (2011) Disrupting Class: How Disruptive Innovation Will Change the Way the World Learns, New York, McGraw Hill.
Engestrom, Y. (2001) ‘Expansive Learning at Work: toward an activity theoretical reconceptualization’, Journal of Education and Work, vol. 14, no. 1, pp. 133-156.
Hamel, G. and Prahalad, C. K. (1991) ‘Corporate Imagination and Expeditionary Marketing’ Harvard Business Review, July-August 1991, pp. 81-92
Prensky, M. (2001) ‘Digital natives, digital immigrants’ On the horizon, vol. 9, no. 5, pp. 1-6.
Scanlon, E. and Issoff, K. (2005) ‘Activity Theory and Higher Education: evaluating learning technologies’, Journal of Computer Assisted Learning, vol. 21, pp. 430-439.
