New technologies get invented and new products are created daily, but only some of them succeed long-term. But can success be predicted and can a product’s life cycle be planned for maximum benefits? Gartner’s hype cycle metrics can help you with that, find out how.
Table of contents
- What is Gartner
- What is Gartner’s Hype Cycle
- A bit of history
- Phases of Gartner’s Hype Cycle
- Accurate, yet controversial
- Future of the Hype Cycles
New technologies mean new expectations and new promises. Both media and entrepreneurs keep looking for ways to analyse their life cycles and to identify the key moments that define their futures. The fundamental challenge is foreseeing the future that is not shaped yet. Can we guess whether something completely new on the market is worth investing in? Or whether a new service is worth supporting or it would be better to shut it down before it generates losses? Scientists are constantly looking for universal ways to answer these questions. Some of them claim that they already did. Let’s see what analysts from Gartner, a leading research and advisory company have concluded.
What is Gartner
Gartner was founded in 1979 by Gideon Gartner, when he realised that his investor insights might be useful for the emerging IT industry. He only employed the most skilled analysts and never feared clearly stating controversial views in his reports. But they were always backed up by solid data. While he left the company he founded after two decades, his legacy remains and the enterprise continues to innovate the research field.
Now Gartner has about 16 thousand associates, operates in a hundred countries and generates over 4 billion USD of revenues annually.
What is Gartner’s Hype Cycle
Gartner’s Hype Cycle is a way of representing the maturity of new technologies in a simple, graphical way. This methodology can give you some solid hints of how your product, technology or app will behave on the market in the future, over time. It can also provide insight into how to manage its deployment in the context of your business goals.
Gartner generates over a hundred of Hype Cycle graphs regarding various technologies each year. Everybody can use their conclusions to plan business strategies. But how did it start?
A bit of history
One of Gartner’s analysts, Jackie Fenn, introduced the concept of a Hype Cycle in 1995. The organisation didn’t manage to promote it to a wider audience for several years, but kept using it to measure various emerging technologies. After some time, it appeared to be surprisingly accurate and if we go back and check the old graphs, we can clearly see that it actually worked in many cases, for example in the cases of mobile devices, such as tablets and BPM.
Phases of Gartner’s Hype Cycle
Each Hype Cycle graph is divided into 5 key phases.
- Technology Trigger
The moment when a potential new, hit technology emerges. No usable products are needed on this stage, just media coverage and significant publicity.
- Peak of Inflated Expectations
Now, a technology gets major media attention and some success stories. Some companies actually get excited, but most are skeptical.
- Trough of Disillusionment
Interest in the new thing drastically drops, because it was too hyped up (as it usually happens). However, manufacturers shake out of the initial failure and satisfy early adopters.
- Slope of Enlightenment
Both technology providers and its users start understanding the new technology and keep finding new, exciting ways to use it. New generations of products show more and more refinement.
- Plateau of Productivity
The technology goes mainstream. There is some competition on the market and criteria of how to choose a vendor are clear. If on this stage the technology is more than a niche, it will most likely succeed and continue to grow.
Taking a look at a graph created for a technology you are interested in may help you make crucial decisions. The main benefits are: ability to separate hype from an actual commercial promise and reducing risk in technology related decisions.
Gartner’s Hype Cycle – accurate, yet controversial
Gartner’s Hype Cycle is not perfect, though. First of all, it’s not really a cycle, as it doesn’t have anything to do with a trend coming back to where it was at the beginning and repeating the phases it went through – so it’s just a brand name of the methodology. Another criticism is that it depends not on the technology that it is trying to research, but on its economic performance. But is it actually a serious fault? After all, it’s all about the market adoption and technology’s life.
Some critics also say that it is not very helpful at planning and predicting how new technologies will behave in the future, because it actually comments on pre-existing trends. In fact, some experienced investors, for example Michael Mullany have done exhaustive studies on the subject and presented evidence 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.
Mullany, in his great article from 2016 identified a number of examples of technologies that Gartner was excited about, but they failed miserably:
- Ultrawideband: a short range radio technology
- RSS Enterprise
- Desktop Linux for businesses
- Mesh networks
He also makes some mistakes in his predictions, though, especially when he’s writing about FinTech. Internet micropayments are actually a thing right now, yet he was worried that this technology will not become a standard in near future, only being restricted to Apple devices.
In general, we’re bad at making predictions. Out of the more than 200 unique technologies that have ever appeared on a Gartner Hype Cycle for Emerging Technology, just a handful of technologies – Cloud Computing, 3D Printing, Natural Language Search, Electronic Ink – have been identified early and traveled even somewhat predictably through a Hype Cycle from start to finish.Michael Mullany, General Partner at Icon Ventures Europe
Future of the Hype Cycles
Gartner will keep publishing their research and new graphs. With the advancements of the methods, let’s hope more and more of them will be accurate, so we can have a deeper insight into the future. But will it prove more successful? We can only hope!