From innovation to productivity Gartner’s Hype Cycle is a branded graphical framework for understanding and tracking specific technologies’ maturity, adoption, and social application. Proposed in 1995 by research and advisory firm Gartner, it has become one of the most well-known models used to characterise the typical progression of emerging technologies from conception to mainstream adoption. The Hype Cycle seeks to provide a snapshot of the relative maturity and adoption trajectory of innovations in the software, computing, and communications domains. The Hype Cycle consists of five key phases: the Innovation Trigger, the Peak of Inflated Expectations, the Trough of Disillusionment, the Slope of Enlightenment, and the Plateau of Productivity.
These phases depict the typical pattern of excitement and disappointment that often accompanies the introduction of new technologies. By understanding where technology stands on the Hype Cycle, organisations can better manage their expectations and make informed decisions about investment and adoption. The Hype Cycle is a valuable tool for technology assessment and strategic planning in various industries. It is significant in enabling more educated examination and discussion of new technologies by investors, vendors, policymakers, and journalists. Broadly, the Hype Cycle outlines five phases that technologies typically go through, from initial launch to productivity. These include the Innovation Trigger, Peak of Inflated Expectations, Trough of Disillusionment, Slope of Enlightenment, and Plateau of Productivity.
Innovation Trigger
The innovation trigger represents the first stage of a technology’s hype cycle, where it is launched or becomes known to the public. It is a ‘trigger’ because it catalyses significant press, interest, and enthusiasm. This initial wave of attention is typically fueled by technology announcements from vendors and organisations, proof-of-concept stories, and media buzz around the innovation’s possibilities. During the innovation trigger phase, discussions focus on the technology itself—how it works, its capabilities, who uses it, and its advantages over existing solutions. At this early stage, the limitations and challenges of successfully deploying the technology at scale are often overlooked or downplayed.
A prime example is the emergence of augmented reality (AR) technology over the past decade. While early forms of AR existed before, the Innovation Trigger is often pegged to the launch and viral spread of AR mobile games like Pokémon Go. The technology dazzled consumers and evoked visions of groundbreaking applications across education, training, design, and more. Early pilot projects provided glimpses into AR’s potential and highlighted technological hurdles.
Peak of Inflated Expectations
The next stage in the hype cycle is the peak of inflated expectations. Following the Innovation Trigger, excitement around the technology surges as early publicity yields several success stories accompanied by widespread failures. The peak represents the height of overenthusiasm and unrealistic projections about how fast the technology can be successfully deployed. During the peak of inflation expectations, a frenzy of activity occurs around innovation. Analysts make bold predictions about adoption rates and market size. Companies rush to implement pilots, often needing to understand the challenges fully. Investors eagerly fund startups, and competitors move quickly to launch rival offerings. The bandwagon effect takes hold as organisations feel the need to experiment or risk being left behind.
A prime example is the rise of internet companies in the late 1990s, following the web going mainstream. The rapid appreciation of internet stocks and a profusion of dot-com startups reflected inflated expectations about how quickly the web would transform business and commerce. Many internet companies lured by the hype failed amidst flaws in their business models and customer propositions. The bubble eventually burst, leading to a period of disillusionment. However, the dot-com bubble taught valuable lessons about the importance of solid business fundamentals and realistic growth projections. Companies that survived the burst learned to focus on profitability and sustainable growth rather than chasing the latest trend. This period of disillusionment paved the way for a more mature and resilient internet industry, with companies like Amazon and Google emerging as dominant players. Ultimately, the dot-com bubble served as a reminder that innovation and experimentation must be tempered with careful planning and a solid foundation to ensure long-term success.
Trough of Disillusionment
The Trough of Disillusionment represents when interest wanes as implementations fail to deliver. The trough refers to the bottoming out of hype, and disillusionment signifies lost interest and cynicism about the innovation’s merits. During this phase, technologies need to meet expectations and become increasingly unfashionable. Companies abandon pilot projects, venture capital flows decrease, and media coverage dissipates. The trough can last months or years, depending on the pace of progress. The overpromising and lack of clarity around use cases during the hype trigger and peak contribute to the disillusionment.
A relevant example is Google Glass, an early augmented reality device with an optical head-mounted display. After great fanfare surrounding its announcement in 2012 and limited beta launch in 2013, it failed to gain traction over the next few years. Concerns around cost, style, privacy, and limited functionality led many initial testers and publishers to lose interest. Google eventually pivoted Glass to focus on enterprise rather than consumer applications. This shift in Google’s strategy further added to the disillusionment surrounding Google Glass. The hype and excitement surrounding the device quickly faded as it became clear that it was not living up to its potential as a consumer product. This disappointment with Google Glass is a cautionary tale for other companies entering the augmented reality market, highlighting the importance of understanding and addressing consumers’ concerns.
Slope of Enlightenment
The Slope of Enlightenment follows the Trough of Disillusionment as momentum improves and a more pragmatic understanding of the technology’s applications and limitations emerges. Enlightenment refers to the growth of practical knowledge and insights based on implementation experience during this phase. The slope represents a stage where organisations begin to understand where and how technology can benefit them and integrate it into their businesses. During this period, advancements in infrastructure, support services, and complementary technologies also helped drive growing adoption. The technology becomes better understood with tooling and best practises established around optimal use cases. For example, the Slope of Enlightenment for cloud computing spanned the 2000s as real-world learning emerged and companies like AWS made progress on maturing the technology and addressing enterprise concerns. Increased clarity on situations where the cloud delivers benefits versus on-premise systems helped gradually tilt the cost-benefit analysis in favour of adoption. As more organisations began migrating their infrastructure to the cloud, they realised the potential cost savings and scalability of cloud computing. This led to a snowball effect, with more and more companies jumping on the cloud bandwagon. Additionally, as technology improved and became more reliable, businesses gained confidence in handling their critical workloads and data. Ultimately, the growing adoption of cloud computing was fueled by cost-effectiveness, scalability, and increased trust in the technology’s capabilities.
Plateau of Productivity
The plateau of productivity represents the point at which mainstream adoption has been achieved, with the technology delivering tangible results and becoming embedded into everyday operations. The plateau metaphor indicates a levelling off of growth and productivity, which signifies that innovation is utilised to provide business value. At this mature stage, use cases are well understood and tied to return on investment. Companies across industries have the infrastructure and skills to leverage technology effectively. Vendors compete on service offerings and pricing within a stable market. The technology has become widely accessible to businesses of different sizes. For example, e-commerce entered its plateau of productivity in the early 2010s, after years of evolution and refinement following the dot-com crash. The proliferation of broadband connections, trusted payment systems, turnkey software, logistics infrastructure, and lower barriers to website creation enabled mainstream e-commerce adoption. By this point, online retail was an established facet of the industry. Consumers were now comfortable making purchases online and had come to expect the convenience and variety that e-commerce offered. As a result, brick-and-mortar retailers faced increasing pressure to adapt and incorporate an online presence into their business models. This shift towards online retail also opened up new opportunities for entrepreneurs, allowing them to start their e-commerce businesses relatively quickly. Overall, the widespread adoption of e-commerce has transformed the market, making it more competitive and dynamic.
Conclusion
The Hype Cycle offers a snapshot of the evolving lifecycle of technologies, helping investors, companies, and individuals form realistic expectations. As illustrated through the different stages, innovations follow a predictable cycle from trigger to peak enthusiasm, disillusionment, growing understanding, and mainstream adoption. Understanding the Hype Cycle can provide valuable insights for decision-making and resource allocation. It can help investors identify potential opportunities and determine the best time to invest in emerging technologies. For companies, it can guide the development and marketing of new products, ensuring they are launched at the right time and with realistic expectations. It offers individuals a framework for managing their expectations and making informed choices about which technologies to adopt and when.
There is one other thing that the Hype Cycle has done for general technology adoption, and that is that it has managed to focus business stakeholders views on investment and when it may be required. Trying to explain to the Chief Financial Officer that its time to invest in one particular type of technology or another is difficult enough at the best of times, but if you can provide a product Life-Cycle/Hype-Cycle approach to your explanations, things tend to get a little easier and the thinking behind decisions can be articulated better.
In conclusion, the Hype Cycle is a valuable tool for understanding the dynamics of technological innovation and its impact on markets and society. By anticipating this progression, organisations can make more informed technology investment and planning decisions aligned to actual maturity levels rather than getting caught up in the hype. Recognising hype as temporary and remaining focused on genuine utility is critical to extracting meaningful value from emerging innovations. By recognising the stages of the Hype Cycle, organisations can better determine when a technology is ready for adoption and avoid investing in overhyped trends. Businesses can concentrate on the genuine utility of emerging innovations and make informed decisions rather than letting fleeting excitement influence them. Ultimately, this approach allows for extracting meaningful value from technology investments and ensures alignment with actual maturity levels.