A lot of it is related to a very favorable macro environment with low interest rates and a long bull cycle over the last few years (if not the last couple of weeks).įrom a founder perspective, the compression of the hype cycle reinforces the temptation to raise as much money as possible during the boom phase of the cycle, in part because the bust may follow pretty quickly. The system is flush with money, with billion dollar early stage funds and multi-billion dollar late stage funds with “kingmaker” strategies. Previous waves of innovation (social networking, mobile) have subsided, and investors are anxious to find the next big thing. We live in a hyperconnected world, where everyone around the globe now reads the same press and social feeds in real time. The reasons for this compression of the hype cycle are not hard to figure out. Naval Ravikant nicely captured the velocity of the latest gyrations (for cryptocurrencies and the underlying blockchain ecosystem) in this recent tweet: Deep learning, vertical farming and autonomous vehicles could very well be next in line.Īs to crypto, the current industry darling, it seems to have already gone through several booms and busts (just blips as part of a broader hype cycle, true believers will say). Fast forward to today, and it is generally difficult to get companies in those spaces financed.
On-demand, online lending, food, consumer IoT, VR, drones, bots, AR: they were all the rage for a bit. If you think about what has got VCs (and founders) excited about the last few years, all cycles have been very short.
#Gartner hype cycle iot 2015 series
Occasionally, you see a category going through a series of mini-hype cycles, with quick ups and downs. The category then goes cold quickly, and everyone moves on to the next shiny object. After just a few months, the space feels over-crowded and every investor interested in it has “made their bet”. As soon as a category shows early signs of promise, founding activity accelerates dramatically and investor money flows in very rapidly. They’re also more pronounced, with sharper spikes that feel like instant bubbles. They’re much faster, with the time between boom and bust going from years to mere months. Recently, hype cycles have become even harder to decipher and “time” correctly. Investing right before the crash, in comparison, may seem foolish with 20/20 hindsight, but feels a lot better at the time, as one gets a lot of external validation (press, markups).
Easier said than done of course, because it is exactly the moment when things look the most uncertain. Hype cycles are a great framework for investors (and founders), because entering the market at the right time is both crucial and very hard.Įverything else being equal, you’d want to invest after the crash, early in the “deployment cycle” (Perez) or the “slope of enlightenment” (Gartner), when competition is comparatively limited but the market shows early signs of actual adoption. Whether you use the Carlota Perez surge cycle (see this great Fred Wilson post ) or the Gartner version, hype cycles convey the fundamental idea that technology markets don’t develop linearly, but instead go through phases of boom and bust before they reach wide adoption.
I spend a lot of time thinking about hype cycles, across industries ( Big Data/AI, IoT ) and ecosystems ( New York ).
