Persistent Forecasting of Disruptive Technologies (2010) / Chapter Skim
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5 Ideal Attributes of a Disruptive Technology Forecasting System
5 Ideal Attributes of a Disruptive Technology Forecasting System
Pages 57-91
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From page 57... ...
Given multidimensional forecasting output, selecting appropriate visualization schemes can also help human analysts to process complex output more quickly and creatively. Finally, as for any complex system, using and maintaining a persistent forecasting system yields a number of postprocessing and system management considerations, described in the final section of the chapter.
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From page 58... ...
Persistence Persistence is one of the most important criteria to consider when designing a system for forecasting disruptive technology. Because most existing forecasts are developed over a short and finite time, they fail to incorporate signals that emerge after their creation and are therefore usable for only a short time.
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From page 59... ...
Allocate resources -- Allocate integrate forecast into planning and resource allocation Review and revise Analyze Feedback sources of Asset New bias and allocation for Reassess priorities implement potential priorities mitigation disruptions techniques FIGURE 5-2 Conceptual process flow for the persistent forecasting system.
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From page 60... ...
. Thus, it is the committee's belief that blending input from experts and crowds will lead to better forecasts of disruptive technologies.
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One useful frame of reference is to consider how disruptive technologies have developed and emerged histori cally. It would be useful to review the life cycle of a specific disruptive technology from concept, development, introduction, and adoption through maturity and obsolescence.
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From page 62... ...
Table 5-1 illustrates how the new system would compare to traditional forecasting models using a puzzle analogy. TABLE 5-1 Puzzle Analogy Type Traditional Forecasting New Forecasting Visual Analogy A single puzzle, pieces are known Multiple puzzles, pieces distributed at random, media is inconsistent, tools required are unknown, assembler is blindfolded Metaphor One-time disruptive forecasting Persistent disruptive forecasting Context A single best guess of a most likely future Multiple alternative futures Collection It is possible to gather all the pieces We don't need all the pieces -- just enough to see emerging patterns or pictures Time There will be time to run a dedicated Processing must be ongoing, as we cannot anticipate disruption processing step
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From page 63... ...
Therefore, it is important that the data prioritization and structuring processes are done before the data are gathered. Persistent and systematic data gathering is an essential step in assembling a persistent disruptive technology forecasting system.
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From page 64... ...
The quality of existing commercial and open source extract, transform, and load (ETL) tools continues to improve, making it increasingly possible to extract information from different (particularly unstructured data)
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From page 65... ...
Nevertheless, one potential measure of relevance is how it affects a potentially disruptive technology, directly or indirectly. Comparative Quantifiablilty Given the massive amount of data that exists and the ever-growing number of tools and methods for analyzing the world around us, there are few realms that are not quantifiable.
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From page 66... ...
The information sources described in the remainder of this section may be of interest and could be useful to a disruptive technology forecasting system. Trade Associations and Magazines According to Wikipedia, there are over 7,600 trade associations in the United States.
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From page 67... ...
Braintrack.com, an online directory of the world's universities and colleges, lists and provides links to more than 10,000 universities in 194 countries. Similar support should be made available for institutions carrying out research in disruptive technologies.
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From page 68... ...
22 It is also the largest photo sharing application. There are 55,000 communities within Facebook, representing different schools, regions, workplaces, and other groups.23 Other social networks include MySpace, which attracts 115 million international users,24 and LinkedIn, a career-oriented site with over 16 million users.25 Xiaonei has 34 million Chinese users26 and 51.com has 26 million Chinese users.
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From page 69... ...
Surveys Surveys are frequently used to collect data on potentially disruptive technologies in different cultures. Yet challenges to cross-cultural surveys abound, including the difficulty of motivating people to engage in such surveys, making survey instructions understandable, and measuring the validity and reliability of responses.
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From page 70... ...
Data Preprocessing One of the biggest challenges for the operators of the persistent forecasting system will be translating data from multiple sources into a single format that permits analytical and visualization tools to mash up data sets and adjust parameters seamlessly. Data feeds will need to be ingested, transformed, and then normalized before further processing and decision making can occur.
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From page 71... ...
There are several techniques that can be used to analyze and index unstructured data, including text data mining, text analytics, and link analysis. Many of these approaches use statistical methods such as latent semantic indexing (LSI)
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From page 72... ...
The committee believes that appropriate scientific and technology ontologies can be created to help reduce semantic inconsistency between bodies of unstructured text collections. These texts can then be analyzed to highlight the appearance of new scientific and technical concepts, the emergence of new applications, and changes in sentiment that can be used as disruptive technology forecasting signals.
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From page 73... ...
Systems theory is the interdisciplinary study of complex systems in science, nature, and society. 43 While many factors ultimately contribute to disruptions, the committee believes that because at least one, if not all three, complex systems are present in most disruptive technologies, the ideal forecasting system should, at a minimum, incorporate robust scanning and monitoring methodologies to detect variations in the rate of change for the following: • Science and technology discovery, • Trends in nature, and • Societal trends (including economics, law, policy, and the arts)
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From page 74... ...
caused resources to be allocated to key technological breakthroughs at the expense of other programs. Shifts in government policies, as well as the policies of nonstate actors such as the Organization of the Petroleum Exporting Countries, can impact the probabilities of disruptive technology events occurring within particular domains.
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From page 75... ...
The persistent forecasting system can utilize contemporary tools to monitor a rich and diverse set of sources such as buzz logs for hot topics, changes in musical lyrics, new topics covered in the press, emerging concepts found in digitized books and periodicals, new postings on crowd-sourced sites like Wikipedia, tag clouds to identify new topics or relationships, and online social networks that uncover original social causes or important trends. Nevertheless, to mitigate bias, it will be important to reach beyond the Internet and digitized sources to include offline sources of information and information from underdeveloped and emerging countries as well as countries that have limited Internet connectivity.
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From page 76... ...
Some examples of early warning sensors are supply factors, demand factors, price/performance ratios, adoption rates, and changes in historical relationships, correlations, or linkages. System operators should also consider social network analysis software, genetic mapping software, and supply chain software as tools for discovering and mapping complex systems.
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From page 77... ...
Some factors, such as raw material or commodity prices, should be easy to monitor, while proxies or qualitative factors may be required in cases where information is not readily available. Demand Factors in Potential Disruptions Identifying demand factors (units, prices, etc.)
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From page 78... ...
Word spotting, standing queries matching, topic clustering, resource description framework (RDF) topic mapping,45 sentiment analysis, and threshold monitoring are approaches that can be used by automated systems to extract signals from unstructured data sources.
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and the power of humans to make judgments, identify patterns, and use intuition. Analysts and forecasters can use search engines, alerting systems, visualization tools, and computer models to generate signals.
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Vision-Widening Tools for Complex Systems With the advent of the Internet, we have seen rapid growth in social networks, online gaming, virtual worlds, and other proxies that closely approximate complex systems. The persistent forecasting system should, accord ingly, consider using proxies of complex adaptive systems (CASs)
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From page 81... ...
Text Mining With almost 80 percent of global information stored in unstructured text (see the discussion on processing unstructured data) , mastery of text mining will be a critical enabler for a persistent forecasting method that reduces the probability of unlikely events.47 Without text mining, it would be extremely difficult and expensive to organize, structure, and load RDBs and RDFs.
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From page 82... ...
Visualization tools help humans to be more efficient and effective in recognizing patterns in massive data sets. The operators of the persistent forecasting system should incorporate a robust set of visualization tools.
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. With forecasting methodologies such as trend analysis, TRIZ, influence diagrams, and prediction markets, visualization tools can produce a graphical model of the progression (both past and potential future)
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These are all examples of indicators that are of interest to particular types of financial advisors. A similar system could be built for forecasters to track signals and signposts of potentially disruptive technologies.
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An ideal persistent disruptive technology forecasting system might include global maps showing patent filings, venture capital investments, natural disasters, raw materials supply chains, and political stability. These indicators might be color-coded to show improving/deteriorating conditions in each of the major indicators.
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FIGURE 5-9 Tag cloud generated for the scientific revolution using the Many Eyes Beta Site for Shared Visualization and Discovery by IBM. SOURCE: Courtesy of Many Eyes.
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From page 87... ...
At that time, the gasoline engine was just an emerging technology, but the increasing facility in drilling for petrochemicals and the advent of mass production techniques would create one of the most disruptive technologies of the twentieth century. Why did forecasters at that time not see how important this battle was and the long-term technology impact of the gasoline engine?
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From page 88... ...
The data system should support the ability to be parsed and analyzed across multiple quantitative and qualitative vectors simultaneously, without compromising the underlying raw data. The technology infrastructure needs to be highly scalable to support a large user base with an adequate amount of bandwidth and processing power so as not to discourage active and ongoing participation.
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From page 89... ...
By tracking the global information characteristics of the data surrounding a potentially disruptive technology, forecasters can assess the maturity of the technology space (how frequently is the technology of interest discussed?
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From page 90... ...
. Resource Allocation and Reporting Once a potential disruptive technology has been identified, key decision makers will want an assessment of the likelihood of the disruption, its probable impact, factors that could accelerate the disruption, and factors that could inhibit it.
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From page 91... ...
Subrahmanian, 2008. "Scalable text mining." Presentation to the committee on May 29, 2008.
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