8. Hype Cycles (Growth curves with hype)
The hype cycle is a change curve model for the social attention to, investment in, and the adoption of potentially disruptive new ideas or technologies. It was developed by Gartner, the market research and advisory firm behind the Magic Quadrant marketing category model described earlier.
The hype cycle as Gartner depicts it has five stages (see picture below), as follows: First, a Technology Trigger (potential breakthrough) occurs, and first-generation (expensive, customized) products or demos are produced. Eventually this breakthrough gets popularized in industry or general press, and a Peak of Inflated Expectations (“PIE in the Sky” thinking and action) occurs. Entrepreneurs, evangelists, journalists, investors and impatient future-thinkers can all have strong social and economic incentives to portray the near-future state of the science, technology, or product to be much more than it is or can be at its current stage. This is the hype phase, after which the cycle is named. Third, we see a Trough of Disillusionment, where various scientists, engineers, journalists, investors, and public react negatively, sometimes strongly, to the previous hype, and their stories create their own negative counterhype, sometimes pushing social expectations below where they deserve to be. Until or unless the product improves itself, market interest wanes, investment capital dries up, first-round competitors run out of startup funding, and slow-moving R&D initiatives may at this stage be prematurely terminated by short-sighted managers.
Gartner calls stage three the Slope of Elightenment, but we should call it the Slope of Exponential Performance, as it is typically an upslope in product performance and adoption. It starts when the product enters a second-generation, usually much later than hype predicted, and starts to climb beyond early adopters (5-10%) into larger market share. Gartner calls stage four the Plateau of Productivity, but is usually not a plateau in either expectations or productivity, but rather further exponential growth followed much later by market saturation, the familiar S-curve of product and technology adoption (after the hype subsides, growth can turn out to be one of our other curves, but the S-curve is the most commonly seen). As real growth gets started, various professionalization, standardization, and best practices begin to take hold, and third-generation products and services emerge. These are finally good and cheap enough to move the product into its highest growth phase, followed later by market saturation, for that particular product at least.
The hype cycle attaches itself to a special class of potentially disruptive growth curves, where various self-interested actors unconsciously work together to overhype the story and timescale of new product or service development, and capture value as soon as they can plausibly do so, typically well before the technology is ready. The sexier the technology’s potential seems (3D printing, genetic engineering, brain-machine interfaces) the more overoptimistic and accelerated the hype. Predictably then, human greed and unconscious or conscious dishonesty, in the form of overclaiming and lack of critical evaluation are always part of the modern story of disruptive new technology attention, investment, and adoption.
A better model for tracking technology development (first-gen, second-gen, etc.) than the hype cycle is the technology readiness level (TRL) model, originally developed by NASA and the US Department of Defense for use in technology assessment, transfer, and management programs. TRL models tend to disregard socioeconomic factors that incentivize overpromotion of immature technologies, so they should be combined with the hype cycle model to forecast social attention, investment, and adoption cycles.
For good tips on how to manage these classic attention, investment, and adoption patterns, see Fenn and Raskino’s Mastering the Hype Cycle (2008). Both authors are Gartner Fellows. When your team is aware of a hype cycle, they can use countercyclical (contrarian) strategy wisely. For example, in R&D and startup situations with great new technology it is usually wise to stay in stealth mode as long as possible to avoid triggering inflated expectations, which will attract competition. Conversely, if you don’t believe a technology yet has enough engineers or money working to make it real, you might yourself trigger or jump on a hype bandwagon. Some competitors engage aspirational promotion, but are careful not to overinvest too early themselves, and instead wait to buy others assets once they enter the trough of disillusionment. If you are a large company considering acquisitions, purchasing a company at end of its trough of disillusionment, just as second-generation technologies are nearing market, or waiting until third-generation and the start of exponential growth, may be the wisest strategy.