The Compression of the Hype Cycle

I spend a lot of time thinking about hype cycles, across industries (Big Data/AI, IoT) and ecosystems (New York). 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. Hype cycles are a great framework for investors (and founders), because entering the market at the right time is both crucial and very hard. Everything 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. Easier said than done of course, because it is exactly the moment when things look the most uncertain.