'We find no evidence, by contrast, that experts can effectively assess the commercial potential of venture ideas in non-R&D-intensive sectors such as consumer web and enterprise software. Finally, we find that industry-specific and scientific expertise is not critical to experts’ collective ability to predict ventures’ commercial viability.'
We're probably moving in to near tautological territory, here. If your venture doesn't depend in genuinely novel technology with significant R&D investment, then... its success probably depends on fundraising, marketing, and luck. All of which don't require industrial or scientific expertise.
Plenty of examples exist such as Uber, Basecamp, etc. Although the success of these ventures is dependent on fundraising and marketing, these are certainly not the only factors and these factors apply to research-heavy startups as well.
Sounds like they're including evaluation by VC-types, not just industrial or scientific expertise. Point being that R&D intensive work is more predictable in general, and VC predictive ability may be overstated.
Looking at ideas alone is maybe no enough. Most of the 'unicorn' startups started as a yet-another X and many others failed with the same idea.
If even experts like y combinator are playing a numbers game akin to a professional sports better or poker player (playing many hands, happy to lose some but win overall) then I don't think we'll ever find a clairvoyant who can predict if a single team or idea will be successful with any degree of accuracy.
A good team (history, education, friendship, track record, focused, balanced, ...) in a potential huge market is worth the gamble. Ideally the setup (I guess) 'only' needs a lot of money to make the difference. Because money will then be available in large quantities.
They are also working off 652 ventures coming out of MIT. Seems like a small and biased data set.
> Using data on 652 ventures in multiple industry sectors, evaluated over an 8-year period, we find that ideas that elicit more positive evaluations are significantly more likely to ultimately reach commercialization. We further show that these results are driven by venture ideas with documented intellectual capital in research-and-development-intensive sectors, such as life sciences and medical devices. We find no evidence, by contrast, that experts can effectively assess the commercial potential of venture ideas in non-R&D-intensive sectors such as consumer web and enterprise software.
More evidence of why a bunch of tech entrepreneurs (YC) are not the right people to spur biotech (and other hard sciences) innovation: https://news.ycombinator.com/item?id=9997722
What's transferable between different tech ventures (other than connections and money) is knowledge about people and how to sell to (and generally deal with) them - issues that regularly come up long after the venture is formed. But the most important factor in R&D-based hard sciences ventures is deep technical expertise. Once that is in place, it's pretty obvious what needs to happen. And you can be sure that YC isn't getting those 'obvious' inventions.
> ultimately reach commercialization, defined as having recurring revenue and expenses associated with the sale of products and/or services in keeping with the company’s business objective.
How viable something is over the long run and its overall success is different from being able to have it out in the market and get inital paying customers.
Reaching commercialization by this definition and receiving better evaluation from VCs means more funding readily avaiable to get a product out.
This also holds up to other research concluding timing is the biggest factor.
I've seen a number of solid startup teams cash in on recycling good ideas from the past (m&a shutdown) and execute well to satiate similar, modern needs. Novelty can be risky (Pebble / Apple Watch) because the latest entrant can learn and improve on what came before.