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Persistent Forecasting of Disruptive Technologies – Report 2
Experts may not catch the full range of alternative solutions from fields outside their areas of expertise or from the reapplication of technologies developed to solve a different problem. Paradoxically, the specificity of knowledge required to achieve expert status can invalidate forecasts generated by experts alone (Johnston, 2003).
The term “disruptive technology” describes a technology that results in a sudden change affecting already-established technologies or markets (Bower and Christensen, 1995). Disruptive technologies can be defined beyond Christensen’s market-based conception as technologies and applications of technologies that can significantly influence the balance of global power. Disruptive technologies cause one or more discontinuities in the normal evolutionary life cycle of technology. This may lead to an unexpected destabilization of an older technology order and an opportunity for new competitors to displace incumbents. Frequently cited examples include digital photography and desktop publishing, as well as older innovations such as the automobile and the telephone.
Other disruptions can be caused by “reverse innovations” that can bring well-established technologies to markets and societies that previously did not have access to these technologies or could not afford them (Govindarajan, 2009). These innovations could be the result of breakthroughs in pricing, accessibility, distribution, business models, manufacturing, research and development (R&D), resource use, or ease of use. Many of these innovations are built around what has been labeled the Gandhian engineering concept of more (social value) from less (low technology, resources use, and cost) for more (dissemination) (Giridharadas, 2008). For disruption to take place, many of these innovations rely not just on low cost and affordability, but also on distribution to developing countries. Emerging markets can be sources of disruptive innovations (Bhan, 2010). Tata’s Nano, the One Laptop Per Child computer, and India’s AirTel are notable examples.
Disruptive technologies can impact society both positively and negatively. The nature of such impacts is greatly dependent on an individual’s point of view—a disruption that is harmful to some will benefit others. Given the ability of disruptive technologies to dramatically alter a competitive environment, displace incumbents, and impact society, there is a great need for technology forecasts (1) to help identify potentially disruptive technologies and (2) to contribute to the understanding of their potential disruptive effects. These two forecasting outputs are fundamental to producing a useful forecast.
This report is the second of two reports produced under the auspices of the National Research Council’s (NRC’s) Committee on Forecasting Future Disruptive Technologies, sponsored by the Office of the Director of Defense Research and Engineering (DDR&E) and the Defense Warning Office (DWO) of the Defense Intelligence Agency (DIA). This committee was established at the request of the sponsoring organizations to provide guidance on how to conduct long-term forecasting of disruptive technologies. The statement of task for the study is provided in Box S-1.
In its first report, Persistent Forecasting of Disruptive Technologies, the committee discussed how technology forecasts were historically made, assessed various existing forecasting systems, and identified desirable attributes of a next-generation persistent long-term forecasting system for disruptive technologies (NRC, 2010). In this, the second report, the committee was asked to attempt to sketch out high-level forecasting system designs that could satisfy the key design criteria of the forecasting system concept developed in the first report. The sponsor also sought further evaluation of the system attributes defined in the first report, and evidence of the feasibility of creating a system with those attributes. Together, the reports are intended to help the Department of Defense (DoD) and the intelligence community (IC) identify and develop a forecasting system that will assist in detecting and tracking global technology trends, producing persistent long-term forecasts of disruptive technologies, and characterizing their potential impact on future U.S. warfighting and homeland defense capabilities.
The committee identified three broadly defined goals for addressing its statement of task: to develop further the structural framework for how to approach the problem of developing a long-term persistent forecast of disruptive technologies, to create alternative models of what such a system might look like, and to define actionable steps toward development. To meet these goals, the committee held a one-day workshop with invited experts from related fields (see Appendix C for a list of participants), followed by a one-day closed meeting to analyze the