Persistent Forecasting of Disruptive Technologies (2010) / Chapter Skim
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2 Existing Technology Forecasting Methodologies
2 Existing Technology Forecasting Methodologies
Pages 17-32
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1 This chapter does not specifically address disruptive technology forecasting but addresses instead the most common methods of general technology forecasting in use today and in the past. A forecast is developed using techniques designed to extract information and produce conclusions from data sets.
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In the late 1940s, the RAND Corporation was created to assist the Air Force with, among other things, technol ogy forecasting. In the 1950s and 1960s, RAND developed the Delphi method to address some of the weaknesses of the judgment-based forecasting methodologies of that time, which were based on the opinions of a panel of experts.
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It is, unfortunately, possible to generate poor forecasts based on credible data. The data are an input to the forecast, and the conclusions drawn from them depend on the forecasting methodologies.
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TECHNOLOgY FORECASTINg METHODOLOgIES As was discussed earlier, technology forecasting methodologies are processes used to analyze, present, and in some cases, gather data. Forecasting methodologies are of four types: • Judgmental or intuitive methods, • Extrapolation and trend analysis, • Models, and • Scenarios and simulations.
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A potential disadvantage of the Delphi method is its emphasis on achieving consensus (Dalkey et al., 1969)
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Experts then rate how similar the analogies are to the target situation and match the outcomes of the analogies with possible outcomes of the target. An administrator would use a set of predefined rules to derive a forecast from the experts' information.
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The technique lends itself to forecasting in that it provides a structured process for projecting the future attributes of a present-day technology by assuming that the technology will change in accordance with the Laws of Tech nological Evolution, which may be summarized as follows: • Increasing degree of ideality. The degree of ideality is related to the cost/benefit ratio.
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Arthur mentions that people have proposed sophisticated techniques from qualitative dynamics and probability theory for studying the phenomenon of increasing returns and, thus, perhaps to some extent, disruptive technologies. Chaos Theory and Artificial Neural Networks Clement Wang and his colleagues propose that there is a strong relationship between chaos theory and technology evolution (Wang et al., 1999)
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This model is useful because chaos is very sensitive to initial conditions. The basic methodology for applying artificial neural networks to technology forecasting follows these high-level steps: (1)
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By using the decision nodes and informational arcs as signposts, they can also use influence diagrams to help track potentially disruptive technologies.
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Early efforts to forecast the future of new technologies such as the personal computer, the cell phone, and the Internet missed the market because forecasters did not imagine that falling prices and network effects would combine to increase the value of the technology. These failed forecasts resulted in enormous business losses.
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The committee suggests considering the following techniques for forecasting disruptive technologies. Prediction Markets Prediction markets involve treating the predictions about an event or parameter as assets to be traded on a virtual market that can be accessed by a number of individuals (Wolfers and Zitzewitz, 2004)
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Prediction markets may benefit from other forecasting techniques that generate a signpost, such as backcasting and influence diagrams. Describing the signpost that appears when a particular point has been reached in a prediction market may help to encourage market activity around a prediction (Strong et al., 2007)
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Online Forecasting Communities The Internet makes it possible to create online communities like prediction markets engaged in continuous forecasting activities. Techcast, a forecasting endeavor of George Washington University, a research project led by William E
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The range of forecasting methods has grown and includes rigorous mathematical models, organized opinions such as those produced by the Delphi method, and the creative output of scenarios and war games. While each method has strengths, the committee believes no single method of technology forecasting is fully adequate for addressing the range of issues, challenges, and needs that decision makers face today.
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1999. Chaos theory in technology forecasting.
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