Tool to navigate hype cycles, technology readiness levels?
Tool to navigate Hype Cycles, Technology Readiness Levels?
Many pieces of technology don’t make it to the market. Innovation is inherently risky. Product development and innovation pipelines are also full of black swans. When building innovation pipelines and portfolio models, product development teams should focus on the most promising large opportunities, but these big opportunities with their multi billion market potentials are also inherently risky, and there is no way of knowing whether they will make it or not. And then, in addition, the product development teams must combat hype cycles.
Technology hype cycles are some of the riskiest dynamics going on these days. Technology hype cycles can be measured by the 1995, Gartner’s Hype Cycle of Innovation Adoption.
So innovation pipelines don’t merely need to be navigable so that teams can move far enough leftward toward large markets to ride the crest of the next big wave of innovation. Innovation pipelines and Team salary models should be designed so that they can move toward large opportunities leftwards far enough to ride the very broad base of the very big opportunity. And then, after the large opportunity with he multi-billion market potential has been hit, innovation pipelines and portfolio models must continue navigating yet further leftwards toward large opportunities all the way to the peak of inflated expectations and all the way to the trough of disillusionment. Only it has to be performed at a faster pace than the hype cycle because the hype cycle moves faster on the side of the hype.
Quantitative models that anticipate innovation schedules were non-existent until shortly ago. As just one example, the pipeline tools called SaaS see-through-pipeline software from Idea to IPO use that model and a Bodhisattva in a lattice of successive cosmological engines to build the schedules.
Moreover P. Gebert, Chief Wizard at Lifiq, has developed data analytics tools around technology market intelligence and hype data. These data analytics tools can stream technology readiness levels leftward in near correlation with the leftward movement of the hype cycle at a pace faster than the rate at which the hype cycle moves itself.
Is it possible to measure and anticipate the speed of technology hype cycles and their corresponding readiness levels? Hype Cycles are, of course, used in the technology industry and enable consumers and investors to better understand how innovation proceeds and create portfolios accordingly. However, these cycles can be notoriously unpredictable and opaque. Forbes columnists Shally Klahm and Shalin Jyotishi highlight a new tool developed by P. Gebert the Chief Wizard of Lifiq that promises to smoothen out the process by analyzing data around the tech industry.
Leave a Reply