Hype

The Gartner hype cycle is a graphical presentation developed, used and branded by the American research, advisory and information technology firm Gartner to represent the maturity, adoption, and social application of specific technologies. The hype cycle claims to provide a graphical and conceptual presentation of the maturity of emerging technologies through five phases.

Hype

Hype (in the more general media sense of the term "hype"[2]) plays a large part in the adoption of new media. Analyses of the Internet in the 1990s featured large amounts of hype,[3][4][5] and that created "debunking" responses.[2] A longer-term historical perspective on such cycles can be found in the research of the economist Carlota Perez.[6] Desmond Roger Laurence, in the field of clinical pharmacology, described a similar process in drug development in the seventies.[citation needed]

There have been numerous criticisms[7][8][9][10] of the hype cycle, prominent among which are that it is not a cycle, that the outcome does not depend on the nature of the technology itself, that it is not scientific in nature, and that it does not reflect changes over time in the speed at which technology develops. Another is that it is limited in its application, as it prioritizes economic considerations in decision-making processes. It seems to assume that a business' performance is tied to the hype cycle, whereas this may actually have more to do with the way a company devises its branding strategy.[citation needed] A related criticism is that the "cycle" has no real benefits to the development or marketing of new technologies and merely comments on pre-existing trends. Specific disadvantages when compared to, for example, technology readiness level are:

An analysis of Gartner Hype Cycles since 2000[10] shows that few technologies actually travel through an identifiable hype cycle, and that in practice most of the important technologies adopted since 2000 were not identified early in their adoption cycles.

Despite the hype, blockchain is still an immature technology, with a market that is still nascent and a clear recipe for success that has not yet emerged. Unstructured experimentation of blockchain solutions without strategic evaluation of the value at stake or the feasibility of capturing it means that many companies will not see a return on their investments. With this in mind, how can companies determine if there is strategic value in blockchain that justifies major investments?

The insights from our analysis suggest that, beyond the hype, blockchain has strategic value for companies by enabling both cost reduction without disintermediation as well as, in the longer term, the creation of new business models. Existing digital infrastructure and the growth of blockchain as a service (BaaS) offerings have lowered the costs of experimentation, and many companies are testing the waters. However, fundamental feasibility factors delimit what can be scaled and when as well as the realistic time scales for return on investment on proof of concepts.

These indicators are widely ignored, in partbecause we are distracted by information appearing to carry a more positivemessage. The number of patent applications and patent awards has increased about sixfoldsince 1984, and over the past 10 years the number of scientific papers hasdoubled. The stock market has tripled in value since 2008. Investments by USventure capitalists have risen about sixfold since 2001: the total invested in2018 exceeded the peak of 2000, the last big year of the dotcom bubble,and the number of start-ups valued at more than $1 billion is now in thehundreds, compared with a handful just a decade ago. Such upward trends areoften used to hype the economic potential of new technologies, but in factrising patent activity, scientific publication, stock market value, and venturecapital investment are all poor indicators of innovativeness.

Hype and its amplification come from many quarters: not only the financial community but also entrepreneurs, venture capitalists, consultants, scientists, engineers, and universities. Venture capitalists have convinced decision-makers in national and local governments, as well as universities, that venture capitalist funding and start-ups are the new measures of their success. Professional and business service consultants hype technology for both start-ups and existing firms in an effort to make potential clients believe that new technologies make existing strategies, business models, and worker skills obsolete every few years. With a fivefold increase in the number of such consultants since 1970, the number of people who have an incentive to hype new technologies continues to rise.

Universities are themselves a major source of hype. Their public relation offices often exaggerate the results of research papers, commonly implying that commercialization is close at hand, even though the researchers know it will take many years if not decades. Science and engineering courses often imply an easy path to commercialization, while misleading and inaccurate forecasts from media outlets such as Technology Review and Scientific American make it easier for business schools and entrepreneurship programs to attract more students by claiming that opportunities are everywhere and that incumbent firms are regularly being disrupted.

Sometimes the beliefs behind political and technology hype merge. Think of libertarians who love cryptocurrencies, defense hawks who love new fighter jets, adventurers who think space travel is human destiny, train buffs who love hyperloop, health care professionals who love any technology that might prolong lives, anticorruption crusaders who love blockchain, social entrepreneurs who love financial technology (fintech), and environmentalists who love renewable energy and electric vehicles. Many of these special interest groups often believe their overall goals are far more important than more practical issues such as cost, performance, economic feasibility, and profitability, a problem made worse by the increasing polarization of the American public along ideological lines. As these special interests push their technologies on social media sites such as Twitter, LinkedIn, and Facebook, they create echo chambers in which people repeat the same message until it becomes an unquestioned mantra, even though few economic details are presented.

There is muchthat managers, investors, journalists, policy-makers, and others can do toassess the economics of emerging technologies and reduce the surrounding hypein order to determine where their support should go. To begin, they can inquireabout existing implementations. Has the technology been implemented, what arecustomers saying, what is the financial status of the suppliers? Are there one,ten, or one hundred implementations, and what do their experiences (includingthe customer feedback and supplier financials) indicate about future ones? Arethere large numbers of similar applications just waiting to be implemented inthe future, or only a few niche ones? Computers playing chess seems relevant tojust a few niche applications, while successful examples of machine learningthrough Watson, for example, would be more relevant to the overall field ofhealth care.

For instance, returning productivity to the highgrowth years before 1970 will require more science-based technologies to becommercialized, as they were in the glory years of the 1950s and 1960s whentransistors, integrated circuits, lasers, magnetic storage, nuclear power, andLEDs were implemented. Falling research productivity likely means that thereare fewer of these technologies being commercialized. But the current hype aroundnew technologies prevents many people from acknowledging the decline, therebypreventing us from reversing it by doing things differently. For instance,perhaps the decline of the major corporate R&D labs in the past 75 years,and the expectation that universities would take up the slack, is a reason forfewer science-based technologies being commercialized. This change has drivenincreases in the number of scientific papers, but not the emergence of many newscience-based technologies. 041b061a72