Hybrid Cloud Computing is out, Software-Defined Security is in and Big Data is now in the mainstream. The analysts at Gartner have a bit of a reputation as gurus for the IT industry: when they speak, people listen.
Every August for the past 20 years, the IT and market research consultants at Gartner look into their crystal ball and issues some predictions. The analysts from Stamford, Connecticut undertake a thorough review of more than 2,000 technologies and select roughly 70 of them that they consider especially relevant.
These technologies are then placed along a curve reflecting the phases that each technology takes on its journey to becoming market-ready. The analysts also apply symbols indicating the estimated time frame for significant market penetration. In the past, these so-called Hype Cycles have proved astoundingly accurate. Gartner's selections have also always influenced CeBIT's theme selection. In 2016, CeBIT is being staged under the motto “d!conomy: join – create – succeed.”
The "Hype Cycle for Emerging Technologies 2015" highlights which technologies might well be setting the tone for the coming years and which have their best years behind them already.
The Hype Cycle is broken down into five phases, beginning with the Innovation Trigger (sometimes called the Technology Trigger). This marks the start of the curve. Technologies falling here are often still in the R&D stage. In some cases there may be proof-of-concept products in the wild, but they lack market maturity and realistic economic viability. The prognosis is generally that it will take more than a decade before something sensible emerges from the technology.
Next comes the Peak of Inflated Expectations — a phase of über-hype and sky-high expectations. This is the point when expectations and reality are furthest apart.
The Trough of Disillusionment follows. Technologies that reach this point are on the declining track, headed toward the Valley of Disappointments.
Public interest tails off sharply here since no market-ready products are available. Quite a few manufacturers jump ship here. Those that remain continue to improve their product to make it attractive for Early Adopters.
The next phase is the Slope of Enlightenment/Path of Illumination: technology in this phase has not yet penetrated deeply into the public consciousness, but there is certain crystallization of understanding of the benefits, practical implementation and limits of the technology. Multiple companies have invested in it, and second or third generation products have appeared.
Finally the cycle moves into the Plateau of Productivity and enters the mainstream. Thirty percent of the target audience will have acquired related products by this point.
There is a methodological problem here insofar the Hype Cycle influences the development of the hype itself. If all CIOs were to follow the Hype Cycle, then the hype would develop precisely as forecast. All the same: the Hype Cycle Curve allowed its inventor Jackie Fenn to predict the bursting of the dotcom bubble a half year before it happened.
If you compare the 2015 Hype Cycle for Emerging Technologies with the previous year's version, it's immediately clear what's missing: Big Data, NFC, in-memory computing and cloud computing. There are two potential reasons any of them might have disappeared: a) the technologies have succeeding in their breakthrough and have exited the curve to the right, or b) the much-hyped technologies have lost their buzz, dropping them off the Hype Cycle entirely.
Several interesting pieces of technology stand out in the 2015 Hype Cycle. The term “Smart Dust” appears at the very start of the curve. This refers to swarms of nano-sensors, known as Micro-ElectroMechanical Systems (MEMS), that can measure factors such as light, temperature, vibration, magnetism or specific chemicals and analyze the data. They are not likely to hit the mainstream anytime in the next decade though, Gartner reports.
Citizen Data Science is somewhat further along. It posits that tools and technologies have grown so advanced that anyone of average intelligence at a company can perform data analysis of the kind that once required an army of highly specialized data scientists. This kind of transition to a company-wide focus on data can only have a positive effect on companies, Gartner opines.
Another concept in the high hype phase is Software-defined Security. This involves the uncoupling and abstraction of infrastructure elements in computing centers such as servers, storage and networks. Software-defined Security doesn't mean the elimination of security hardware. It simply means that the intelligence for software-defined security indeed comes at the software level.
Micro Data Centers are approaching maximum hype. With an ever-expanding volume of data arising through the Internet of Things, lower latency times are increasingly important. Micro Data Centers are one way to ensure this.
Two concepts at the very pinnacle of hype, and thus prepped for a rapid descent, are autonomous vehicles and the Internet of Things. Google's self-driving car has appeared in media stories the world over. Advances in sensors, machine processing and communications software tied to advanced software and cloud computing have made autonomous cars more likely, Gartner says. That said, the tasks to be handled by this kind of vehicle are extremely complex and development costs remain very high.
Well on their way into the Valley of Disappointments are wearables, crypto-currencies such as Bitcoin, hybrid cloud computing and augmented reality.
By contrast, Enterprise 3D printing has almost achieved the Plateau of Productivity and thus has strong potential for attaining mass marketability.
Prognoses and reality in the Gartner Hype Cycle
Looking back on the Hype Cycles from 2005 - 2015, it's striking just how accurately the analysts at Gartner have managed to classify many technologies, however obscure they seemed, in an IT landscape that is constantly shifting.
Augmented Reality for example has proven a slow burner. It first joined the curve in 2005, in the first section below Innovation Trigger. It was predicted to hit the Plateau of Productivity within ten years. While it hasn't quite gotten there in 2015, it has made it to the Valley of Disappointment. There are scant few marketable products, and there's still intensive contemplation
of potential business models.
In 2005 the tablet computer was stuck in the Trough of Disillusionment, although its prognosis was good to make it big in the next five years. True to Gartner's prediction, Apple released its iPad in 2010, and tablet computers moved from hyped to self-evident. At that point it left the Hype Cycle entirely.
The era of cloud computing began in 2008 – in the Hype Cycle with a prognosis of five years until the Plateau of Productivity. It almost achieved this in 2014. The technology doesn't appear in the Hype Cycle at all in 2015, given that it's already reached the mass market.
There are however also counterexamples: Big Data was still on the Hype Cycle in 2014 on the way into the Valley of Disappointments, with a prognosis from five to ten years. Cloud computing was assessed as just ahead of the Trough, with a forecast of two to five years before achieving the Plateau of Productivity. Neither is on the 2015 Hype Cycle, as the technologies have in fact established themselves more quickly than expected.
The Hype Cycle for Emerging Technologies isn't the only Hype Cycle being tracked by Gartner.
There's also the Hype Cycle for 3D Printing. It reports that 3D Scanning and Enterprise 3D Printing have both arrived at the Plateau. Consumer 3D Printing is on its way into the Valley of Disappointments, while 3D Printing for medical devices is generating massive buzz.
Another example is the Hype Cycle for Big Data. It reports that Hadoop, Data Warehouse Platform as a Service (dwPaaS) and Social Analytics are out. The next big hypes in this sector could be Data-as-a-Service, Open Data and Big Data Analytics for Fraud and Security.
In terms of networks, the market researchers confirm that WLAN 802.11ad and software-define WAN are flying high, while software-defined networking has already crashed and Fiber Channel-over-Ethernet is now considered obsolete.