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Forecasting the Technology Revolution: Results and Learnings from the Techcast Project Technological Forecasting & Social Change 80 (2013) 1635–1643 Contents lists available at ScienceDirect Technological Forecasting & Social Change Forecasting the Technology Revolution: Results and learnings from the TechCast Project William E. Halal ⁎,1 a Management, Technology & Innovation, School of Business, ISTM Dept, 515 Funger Hall, George Washington University, Washington DC, 20052, USA b Institute of Knowledge & Innovation-SE Asia, Bangkok University, Thailand article info abstract Article history: This research report presents latest results on the TechCast Project, first reported in Received 18 June 2012 Technology Forecasting & Social Change 14 years ago [1]. TechCast is an online Delphi system Received in revised form 26 January 2013 that pools background trends and the judgment of experts around the world to forecast Accepted 3 February 2013 breakthroughs in all fields. Results are presented for strategic technological advances that are Available online 15 March 2013 likely to enter the mainstream and their expected impacts, providing an overview of the Technology Revolution. Aggregating the forecast data then provides macro-forecasts of broad Keywords: timetables for economic and social change. This analysis suggests that the global economy is TechCast Project likely to enter a new economic upcycle about 2015 and reach an advanced stage of Delphi Method development about 2020. We also examine examples of how organizations develop Technology Revolution technology strategy to compete in an era of economic transformation, and conclude by Collective intelligence analyzing the role of forecasting as one of many methods for reducing uncertainty. © 2013 Elsevier Inc. All rights reserved. 1. Introduction notably seen in popular views of a coming Singularity [3]. The goals of this project were defined as follows: This journal (TFSC) published the first results of the TechCast Project in 1998 [1]. Using a Delphi Method [2], 1. Apply advanced foresight and forecasting methods to forecasts were presented of the year when 85 emerging estimate the arrival and impact of strategic technologies in technologies are likely to enter mainstream use, along with all fields on a continuing basis. estimates for probability, market demand, and leading 2. Conduct validation studies to estimate the accuracy of the nations. With early signs underway of a wave of rapidly forecasts and to consider how they can be improved. emerging new technologies, the project was intended to map 3. Study actual cases of technological innovation to better the full range of what is now often called the Technology understand the role of forecasting and other methods for Revolution. History has seen a series of “technology revolu- introducing new products and industries. ”– tions the Agrarian Revolution, Industrial Revolution, Today, this project has become a far more sophisticated – Information Revolution but they can all be considered system for the continuous tracking of strategic technologies. part of a single global transition that has been unfolding for A special aspect of this work is that results are analyzed thousands of years and is now accelerating very rapidly, as annually to estimate errors over the 20 years this data has been collected. Some of the original forecasts are uncanny in their accuracy, with many arriving quite close to the dates forecast in 1993. Note that forecasts are meaningless unless ⁎ Tel.: +1 202 994 5975; fax: +1 202 994 5830. the level of adoption is specified, and these figures are usually E-mail address: [email protected]. 1 Institute for Knowledge & Innovation, SE Asia, Bangkok University, for the 30% adoption level where technology enters the Thailand. mainstream in industrialized nations. 0040-1625/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.techfore.2013.02.008 1636 W.E. Halal / Technological Forecasting & Social Change 80 (2013) 1635–1643 The arrival of “Broadband” was estimated at 2009, and face this common challenge of redefining goals, cultivating actually entered mainstream use about 2008 in advanced new markets, launching new products and services, and nations. “Electronic Banking” was expected to become com- changing how their organizations work. mon by 2009 and reached 30% adoption globally at that exact year. We forecast most sea food would be produced using 2. Forecasting the Technology Revolution “Aquaculture” in 2014 and data confirms 50% adoption in 2012. Another interesting finding is what could be called Based at George Washington University, the TechCast “forecast creep”—the much discussed tendency of experts to Project uses a data-based website (www.TechCast.org)to be overly optimistic in their estimates of when technologies pool the knowledge of roughly 130 high-tech CEOs, scientists mature. The early forecasts in 1993, for instance, estimated and engineers, academics, consultants, futurists, and other that TeleMedicine would be common by 2001, “Virtual experts worldwide to forecast breakthroughs in all fields. The Education” about 2003, and “Optical Computing” by 2007 — TechCast Team constantly scans to define adoption levels, all now seen as demonstrably over-optimistic. driving trends, opposing forces, and other background These examples highlight the strengths and weaknesses information on each technology, thereby providing a signif- of the Delphi technique [4]. In the Research method section icant improvement in the Delphi Method. We also conduct of this paper, we report validation studies suggesting an strategic studies for corporations and governments, which average error band of about +3/−1 years for forecasts ten provides practical understanding of forecasting and strategy years distant. formulation at the leading edge. Prominent cases illustrate vividly the relentless disruption of the Technology Revolution in the rushing change of everyday products. When digital photography became feasible 2.1. Research method a few years ago, the film industry was overturned by digital cameras. Nikon, Kodak, and other famous names that once Because TechCast is basically a system for aggregating dominated photography struggled to adjust, laying off thou- knowledge, the fields of Knowledge Management and sands of employees and replacing product lines. Kodak was Collective Intelligence offer useful perspectives for under- forced to declare bankruptcy in 2012 [5]. standing the rationale underlying this approach. From such New industries soon sprung up as digital cameras views, this is an online “learning system” conducted by a unleashed floods of photos and videos to populate Web 2.0 — “community of practice” that “continually improves” its Facebook, YouTube, blogs, wikis, and more sure to come. In knowledge using “collective intelligence” to approach a turn, digital cameras are being replaced now by smart phones “scientific consensus.” One of our most vivid experiences is with built-in cameras. Ironically, Kodak invented the digital seeing how pooling the tacit knowledge and collective camera years ago, but abandoned the market to smart phones intelligence of 130 good minds can create forecasts that are [6]. remarkably prescient. The same forces of technological change are at work as Unlike most Delphi surveys, this work strives to become alternative energy replaces oil, genetic medicine extends more science-based and less speculative because it draws on lives, artificial intelligence automates jobs, robots serve as empirical data for each technology to guide expert judgments. helpers, and other innovations reach the take-off point. Editors gather information on research progress underway, Individuals and organizations are continually threatened by commercial ventures, adoption levels, and other relevant facts, the failure to adapt to strategic technological change, but which are organized into a succinct analysis of trends driving they also have unparalleled opportunities at the leading edge. each technology. We make a point of including opposing trends And shorter technology life cycles require that managers act that hinder development, such as political obstacles, high costs, quickly or lose product lines. The only safe haven is to remain or social resistance, to ensure that the analysis is balanced. at the forefront of change. Experts are taken through these analyses online and The global recession that began in 2008 poses obstacles, of instructed to integrate the background data and their course, but technological progress is often insulated from judgment to estimate when each technology is most likely economic cycles because R&D projects enjoy long-term to enter the mainstream, the potential size of the economic support from governments, foundations, and universities. market, and their confidence in the forecast. The experts are Entrepreneurs may delay product launches during reces- not all world-renowned, but they represent the leading edge sions, but they also tend to discount downturns in favor of of knowledge on technology. Experts self-select areas they long-term prospects fueled by pent-up demand. In the know best, so sample sizes average about 50–70 responses. depths of the Great Recession of 2008, we saw the success The raw data is automatically aggregated for distribution to of Apple, Facebook, Twitter, Groupon, NetFlix, cloud, and clients over the site in real time. mobile everything. Andy Grove, Chairman of Intel, put it best: More than snapshots in time, this is a continual tracking “Technology always wins in the end.” process that improves as
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