The start of a new year is always an exciting time for forecasters and those who eagerly consume their work in the form of an annual deluge of trend reports (conveniently collected en masse here). That also makes right about now a particularly good time for us to share once again an invaluable reminder from our friend and colleague, the well-known Silicon Valley forecaster Paul Saffo: “Never mistake a clear view for a short distance.”
Put another way, timing is still everything.
With today’s super abundance of trend data, widely available information on the flows of VC investment, and the relative transparency that initiatives like arXiv.org allow into even the academic & deep tech research environments, it’s not particularly hard to see what’s coming in the way of emerging technology or even to make semi-reasonable projections about the associated social and economic impacts likely to accrue over time.
Seeing the train, however, is one thing; catching it is something else. The tricky part (and the key to winding up on rather than under a train) is the timing, a challenge of futural imagination that Roy Amara usefully captured in his famous observation that we tend to overestimate the impact of a new technology in the short run and underestimate the impact of the same technology in the long run. This maxim, commonly cited as Amara’s Law and perhaps the most accurate thing anyone out of Silicon Valley has ever said about the future, forms the backbone of one of the stickiest and most popular mental models for understanding the trajectory of emerging technologies: the hype cycle.
As an example of succinct visualization, Gartner’s hype cycle wave is fabulous in its simplicity. While the specific trajectory of an emerging technology in an evolving market might be determined by an incredibly complex interplay of sheer technical capability with a range of other social, environmental, economic, and even political factors that create enabling/disabling contextual conditions, the hype cycle distillation nails something essential about the characteristic mismatch between our expectations post-innovation trigger and the actual path a new technology takes to market viability in support of goods, services & platforms.
That said, the map is never quite the territory, is it? The hype cycle model isn’t intended to convey a consistent scale, so the elapsed time between the initial innovation trigger and the eventual plateau of productivity can differ dramatically from one technology to the next (e.g., think virtual assistants vs. smart dust). Gartner represents differential timelines with plot points that designate a technology’s time-to-productivity as less than 2 yrs, 2 to 5, 5 to 10, or more than 10 years.
We’ve addressed some aspects of timing market opportunities for emerging technologies at length in previous Briefings 0017 and 0025, but there’s another piece of the timing puzzle that often goes unremarked: the identity of whomever is trying to get the timing right. A lot of when (and how) to engage with an emerging technology in order to make the most of a new opportunity comes down to knowing who you are. [Note that an accurate assessment of who you are is helpful here.]
If you’re a crypto investor, your timing considerations for blockchain development are very different from those of someone who is building a blockchain-based social network or tracing and validating the supply chains of food products. Similarly, the window for maximizing opportunities related to advanced autonomous vehicle technology is going to be much different for an auto manufacturer, a shipping & freight company, and a retailer with a significant annual expenditure devoted to shipping costs.
We can further illustrate this idea by thinking in terms of a set of ready archetypes related to timing emerging opportunities.
Explorers are the vanguard. They’re risk- and novelty-seeking researchers, artists, inventors, and deep tech investors. They might be visionaries; they might be crazy. But make no mistake: their forays into the unknown significantly define the scope of our possible futures.
Pioneers follow when- and wherever the Explorers seem to have found something worth pursuing. They see the opportunity and the possibility of massive upside. These are early adopters, entrepreneurs, and founders. Most will miss the mark, but a few (like the merchants of Gold Rush-era California or the monopolies Peter Thiel envisioned for founders in the tech world) will secure incredibly advantageous positions.
After the bewildering array of possible futures has resolved itself into a more manageable range of probable futures (and the opportunities therein become significantly clarified), the early Settlers move in with additional tools, processes, and more refined insight into what is real and what isn’t – often reaping the benefits of the hard work that the Explorers and Pioneers have done before them. Alas, some of the thrill is gone and so might be some of the extraordinary upside. The name of the game for the Settlers is efficiency, effectiveness, and structured process.
All three of these familiar archetypes – Explorer, Pioneer & Settler – play essential roles in turning the latent potential of the future into our shared present, and each archetype stands to realize significant rewards (in relation to risks and strategies pursued) if they get the timing right.
But the metaphor suggested by these archetypes from California history is also useful in something else that it hints we might be missing amid all the hype: the people who already exist in and around the territories that these emerging technologies promise to transform. Sticking with the example of autonomous vehicles, we should ask also what the future that the technologists and innovators are eager to create offers for established stakeholders such as the driving labor force. What new partnerships and perspectives might allow for the creation of shared value and technologies and systems shaped with moral imagination?
So as you survey the forecasts and opportunities of the new year, take a moment to remember that timing is still everything and self-awareness (especially awareness of self within a larger ecosystem of actors and values) is everything else.
Jeffrey and the be radical team
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