Often the distinction between high- and low-tech startups is measured by the proportion of technical employees — such as fraction of R&D employees or fraction of R&D spending (i.e. R&D intensity).
Still, tech startups are not homogeneous. Some of the distinctions that have been draw are science- vs. engineering-based startups, or industry-specific startups like IT, cleantech, or biotech.
This week I attended two business plan competitions here in Claremont: Wednesday’s business plan competition at the Keck Graduate Institute (which I organized) and today’s Kravis Competition across all the Claremont Colleges.
![]() |
| Judges at KGI 2013 Business Plan Competition: George Golumbeski, Stephen Eck, Bob Curry. Not shown: Liam Ratcliffe, Paul Grand |
In comparing the KGI plans to the other Claremont projects — or those in our textbook — it seems to me that — at least from a financial standpoint — there are three types of companies: high tech, medium tech and no tech.
What is dramatically different about our students projects was that (with one exception) is that they’re highly capital intensive, requiring $5 to $50 million in outside funding. For example, the winning team — using technology from Children’s Hospital Los Angeles to repair Shortened Bowel Syndrome — estimated it needs $20 million in equity and $5 million in government grants to get to market. This project — like many others — is building on millions of dollars of NIH/NSF/foundation grants already received to develop the basic science. There is a certain minimum scale required to get FDA approval and thus generate first revenues.
| 2013 winning KGI team — Hadi Mirmalek-Sani, Porus Shah, Shrina Shah, Rajesh Pareta — with Bob Curry, chair, KGI Board of Trustees |
Over the years, entrepreneurship researchers (and practitioners) have demonstrated that any new company or product has highest uncertainty and risk up until first customer sale. So from a practical standpoint, I suggest a new metric: how much R&D spending do you need before launching a product? How big a bet — with what scale of outside investment — does it take until the entrepreneur finds out whether (s)he has a viable business?
By this measure, the difference is not the % of the money that goes to R&D but the size of the R&D bet that’s needed to test the marketing hypothesis.
A company that takes 5+ years and $50+ million is fundamentally different from one that can ship a 1.0 (or revenue-generating beta) for less than $1 million. By that standard, after biotech the biggest bets required are for renewable energy. You can start dozens (or hundreds) of software companies for one fully mature biotech, biofuels or solar company.


![[feed]](http://photos1.blogger.com/x/blogger2/6971/993546936938810/1600/z/962294/gse_multipart3851.gif)
No comments:
Post a Comment