Gartner's Hype Cycle Methodology

Gartner Hype Cycles provide a graphic representation of the maturity and adoption of technologies and applications, and how they are potentially relevant to solving real business problems and exploiting new opportunities. Gartner Hype Cycle methodology gives you a view of how a technology or application will evolve over time, providing a sound source of insight to manage its deployment within the context of your specific business goals.

Each year, Gartner creates more than 100 Hype Cycles in various domains to enable clients to track innovation maturity and future potential. Hype Cycles characterize the typical progression of innovation, from overenthusiasm through a period of disillusionment to an eventual understanding of the innovation’s relevance and role in a market or domain.

source: Gartner

History of Hype Cycle

The concept of Hype Cycle was introduced by an analyst called Jackie Fenn in the year 1995. For several years of trying to bring this technology into the industry view, the organization began to use Hype Cycle charts of new and budding technologies. If we now go back and see the growth of old technologies, we will be able to observe and validate the curves and arches in the graphical representation. As an effective example, in the year 2005, a technology called Business Process Management or BPM suites was at the top of the Hype Cycle which means that its hype at that time was at the highest. Now a decade later, BPM has most certainly lived up to the Hype. But it is also interesting to note that the technology of Tablets was at the bottom at that time, but it has now emerged to be very useful all over the world.

If you consider the year 2014, the technology that was at the peak of Hype Cycles was ‘Internet of Things’ and the technology at the bottom is ‘White Cloud Computing’. We know where they both are today.

Hyple Cycle Phases

The s-curve shape of the technology maturity is based on the notion hat the performance or in this case particular maturity of a technology develops only slowly in the beginning. Its fundamentals are poorly understood and investments into pilots and early adoptions may result only into little performance gains. Depending on the technology, at some turning point the technology performance is supposed to take off until a plateau, defined by the technology’s specific limits, is reached. The resulting hype cycle shape is depicted in the figure below. Its path can be divided into five distinct phases: innovation trigger, peak of inflated expectations, through of disillusionment, slope of enlightenment, and plateau of productivity. For each phase some indictors are defined (see figure below) They allow judging the current stage for any given technology.

source: Martin Steinert et al.

• Innovation Trigger: A public announcement or demonstration triggers the cycle. Awareness about the technology starts to spread and attracts first media coverage. Venture capitalists and adopting companies are aiming to capitalize on possible first mover advantages.
• Peak of Inflated Expectations: This phase is characterized by high expectations boosted or hyped further by media coverage. Following a bandwagon effect, companies invest without having a clear strategy or sound business case.
• Trough of Disillusionment: The over-enthusiasm and hyped investments result in commercial adoptions that fail to meet performance and/or revenue expectations. Public disappointments spreads and are again hyped by media, this time negatively.
• Slope of Enlightenment: Some early adopters who continued working with the technology begin to experience net benefits and regain motivation. With more investments, the contextual understanding of the technology grows, resulting in increasing performance. The technology begins to be socialized.
• Plateau of Productivity: The technology is realistically valued. Following successful market place demonstrations, the adoption accelerates.

The time between the peak of inflated expectations and the plateau of productivity has been termed as time-to-value gap. Depending on each technologies performance constraints, integration complexity and penetration potential, this gap may differ. As a consequence, the hype cycle is supposed to vary between two years and two decades. Whereas normal technologies take five to eight years, fast track technologies need only two to four years to maturity (indicators: technology high value, simplicity of use, several powerful vendors, existing infrastructure, rapid transition from B2C to B2B, benefits easily quantifiable). To the contrary, long fuse technologies may go through several troughs and hypes (indicators: science fiction style fascination, complexity and need for basic sciences, skills in short supply, need new infrastructure, regulatory issues, depends on new business models).

Based on the annual monitoring and hype cycle analysis of around 1,500 commercially viable technologies, trends and application in eighty IT, business and consumer markets, Gartner elaborates numerous hype cycle reports for industries, and derives consulting advices for specific client companies.

Why the Hype Cycle Matters: Traps and Opportunities The constant barrage of positive and negative hype often leads organizations to behave in ways that may not represent the best use of their resources. The peaks and troughs of the Hype Cycle exert pressure to adopt risky technologies without knowing the potential value, and also mask opportunities to embrace less-visible technologies that may be highly relevant. This leads to the four traps of the Hype Cycle — adopting too early, giving up too soon, adopting too late or hanging on too long

Criticisms of Gartner's Hype Cycle

There have been numerous criticisms 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. A related criticism is that the "cycle" has no real benefits to the development ormarketing of new technologies and merely comments on pre-existing trends. Specific disadvantages when compared to, for example, technology readiness level are:

• The cycle is not scientific in nature, and there is no data or analysis that would justify the cycle.
• With the (subjective) terms disillusionment, enlightenment and expectations it can not be described objectively or clearly where technology now really is.
• The terms are misleading in the sense that one gets the wrong idea what they can use a technology for. The user does not want to be disappointed, so should they stay away from technology in the Trough of Disillusionment?
• No action perspective is offered to move technology to a next phase.
• This appears to be a very simplified impulse response of an elastic system representable by a differential equation. Perhaps more telling would be to formulate a system model with solutions conforming to observable behavior.

An analysis of Gartner Hype Cycles since 2000 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.

Further Reading

• Gartner 2019 Hype Cycle for Emerging Technologies. What’s in it for AI leaders? Towards Data Science
• What’s New In Gartner’s Hype Cycle For AI, 2020 Forbes
• One thing everybody forgets about Gartner’s hype cycle Scott Brinker