More than the Hype: Beyond Gartner’s Hype Cycle
Gartner publishes hype cycles across different technologies and sectors. Here we conduct detailed analysis of Gartner’s Hype Cycles.
By Craig Armour.
My dad has a saying he regales us with from time to time: “Human beings are funny things, I’m glad I’m not one…”. For the most part, we would just nod and smile, perhaps with a little eye rolling action. In that message lies a very good point: Humans are an irrational, emotional bunch who somehow seem to think each of whom behave in a completely unique way. The reality is of course very different with decades if not centuries of research showing very clear behavioural patterns among society, including the way we adopt and accept technology.
In 1995, Gartner started publishing Hype Cycles across a number of different technologies, and now publishes over 90 hype cycles for just about every market segment Gartner covers. How and where Gartner places technologies on the cycle is kept a closely guarded secret, but with a little understanding of what’s going on behind the scenes, it would not be hard to guess.
If you look into Gartner’s own explanation, the cycle comes as a blend of two curves: to the left is all about social hype, and the right, engineering capability. How items are placed on the curve then becomes in theory a measure of visible hype vs engineering capability over time. If hype exceeds capability then it sits on the left, and if it matches it, then it sits on the right. Despite what the curve may suggest, how technology moves through that cycle has less to do with technology maturity and with all reality, everything to do with how we behave as humans. Understanding this behaviour can help guide the delivery of the technology strategy and projects more effectively throughout your organisation.
Figure 1 A comparison of human change models
You see, there’s a surprisingly high correlation between Gartner’s hype cycle to many of the accepted models for human change (Kubler-Ross) and team performance (Tuckman) many of us would have been introduced to in one form or another through corporate life. But why is that important? and how is it relevant to your company or project?
A little hype goes a long way
Like it or not and for good or bad, we are all carry our own biases towards certain outcomes. One of the best-known cognitive biases in technology and innovation is Amara’s Law, simply put as a tendency to overestimate the importance of technology in the short term, and a tendency to underestimate it’s importance in the long term. There’s a lot going on behind Amara’s law but basically, we like to get excited about new technologies and the possibilities they bring but ultimately, are really bad at predicting the future. Excitement can be infectious which leads to hype, which leads to more hype, finally ending in the nice little hype bubble you see at the start of Gartner’s cycle.
Figure 2 Hype cycles are everywhere, NASDAQ scores included (Source: Macrotrends)
A little hype is a good thing. Without it, there would be no emotional or social attachment to new ideas and investment in those ideas would be limited or potentially, non-existent. Too much however, isn’t. If the hype exceeds reality by too much you have a hype bubble. As with any bubble, when that bursts, the fall from grace can be a significant and potentially painful thing. Should the trough of disillusionment be too deep to climb out of, the innovation will be written off as a flash in the pan before ever really giving it a chance to mature.
Delivering to the hype
Generally, in business we at least try to be a little more measured in our assessments and strategies. We try to be impervious to the hype if you will, even if we usually fail to do so. As with any analyst’s report, there’s a grain of salt to be had, however Gartner tries to help us with this assessment through their hype cycle. The cycle provides a guide to the state of emerging technologies across a 5 to 10-year envelope: What’s hot, what’s not, and how long before it’s realistic going to reach maturity. Whether you agree with the location of a particular technology or not, it does serve as a healthy checkpoint. Will this technology represent real world business value? or have I just been suckered in by the hype? If you can’t confidently answer that question, then it may be time to dig a little deeper before making an investment
Figure 3 Gartner’s hype cycle of emerging technologies (Source: Gartner)
There is a simplistic view here which we briefly mentioned earlier: For anything to the left of the trough of disillusionment the hype is currently exceeding actual capabilities. The value proposition is high risk or immature and should be managed as such. Overinvestment in technologies in this phase is ripe as business rush to join the band wagon or out of fear from getting caught behind their competition. In recent years, Big Data and Business Intelligence has (arguably) been a classic example.
Addressing technologies to the right of the trough presents as less of a challenge. The business case for those technologies has become clear, the technology has become mature, and the whole proposition less risky. The question becomes less about if those technologies will represent return on investment, but how.
Figure 4 Hype vs Engineering Capability
Like any good principal, the same concepts apply internally to your organisation as on a global scale. This is where the commonality with the Kubler-Ross change curve really starts to show; As you introduce technologies into your organisation, the level of excitement and hype must match the value those solutions are going to bring. If it doesn’t you could be heading for a hype bubble and your own little trough of disillusionment. Failure to climb out of the trough will be a death for your strategy or project.
Given the way most organisational budget, investment, and project cycles work, if you want to see investment in your project or strategy beyond the initial stand up, you will have a little under 12 months to get a project off the ground and start showing real Return on Investment (financial or otherwise). It’s worth considering this before you start investing heavily in early hyped technologies. Ultimately, it’s a value vs risk thing: Can you confidently state the value this technology will bring within your current investment cycle? Again, if you can’t answer this, then perhaps it’s time to take a step back, or even scale down your strategy or project before you bite off more than you can chew.
Global hype aside, by specifically limiting the peak and trough of hype internally to your organisation, you are more likely to see consistent, even accelerated investment in that strategy over time. Create or embrace too much of the hype early and you had better hope you can deliver, or any future technology investment might be met with cynicism, or dry up completely.
Back to Gartner’s Curve
Regardless of what you might think about Gartner’s analysis, the ideas behind the concept aligns with the very real science behind current thinking in change and organisational psychology. It’s worth considering this as you go about delivering your technology strategy or project; Is what we’re doing, representing real world value to our stakeholders, or have we simply been caught up in the hype? Moreover, are we fueling a hype and expectation with our strategy or project we simply can’t deliver to? Understanding Gartner’s curve will help you with the former. Understanding the mechanics of it will help you with the latter.
Don’t let go of the hype, it is ultimately what will help you get adoption of your technology strategy or project. Make sure though that no matter where your head is at, your feet are heavily grounded in business value. Tools like Gartner’s Hype cycle will at least make sure you’re pointing in the right direction.
Original. Reposted with permission.
Bio: Craig Armour is a Technology and Innovation consultant, focused on Empowering your business to thrive in an ever changing digital age.
- Forrester vs Gartner on Data Science Platforms and Machine Learning Solutions
- Machine Learning overtaking Big Data?
- Gartner 2015 Hype Cycle: Big Data is Out, Machine Learning is in
Top Stories Past 30 Days