Thomas Thurston usually charges big bucks for a consultation like the one he gave me this week. But you’re getting it for free here. Of course, maybe it’s a freebie that will make you seek him out for more information. Either way, consider yourself lucky. I do.
Thurston is the founder of Growth Science International, a research and consultancy firm in Portland, OR. If you’re an entrepreneur, startup investor, or just like to play the stock market, you’ll want to know about his work. Thurston has developed a sophisticated mathematical model of “disruptive innovation,” based on principles put forth by Clayton Christensen of Harvard Business School (who spoke in Seattle earlier this week). Using his model, Thurston claims to be able to predict, with 85 percent accuracy, the fates of companies.
Whether or not you believe his model, you might want to listen to his advice. Most of it hinges on the key idea of “disruption” coming from cheaper, lower-performing products that work their way up-market.
“The biggest mistake startups make is assuming the competition will leave them alone when they’re better-performing,” says Thurston, who previously worked at Intel Capital. “Startups always want to be better than their competitors. It’s so ingrained in their fiber. They’re with disruption theory until they have to be worse—but you can’t just be cheaper. Cheaper and better is ‘sustaining,’ not disruptive. Startups want to raise capital, so they want to talk about why they’re better.”
Without further ado, here are a few tips from the startup predictor. Ignore them at your peril:
1. Go non-mainstream.
Of course, there’s an art to pitching a “disruptive” startup to customers and investors. “You don’t go out and say, ‘I’m worse.’ You find non-mainstream customers who value what you’re good at, even though you’re worse at what the mainstream customers want,” Thurston says. “But if you’re making better margins in your competitors’ market, they’re going to want to take your business.” (What’s interesting here is that venture-backed startups usually target the biggest possible market; not so, disruptive startups.)
2. Study failures.
Thurston built his predictive model in part by studying which companies failed and why. “Most people look at companies who survived and try to learn why. Usually it’s random, it’s hard to see. What people don’t do enough is look at failures, because the data is harder to get,” he says. “When you study a lot of failures, you see patterns much more strongly. Startups aren’t spending enough time studying failures.” (This also ties into an interesting cultural discussion about the tolerance for failure in the Seattle innovation community.)
3. Pay attention to narrative—especially when it comes to your competitors.
Surprisingly, Thurston’s research suggests the valuation companies get from investors can vary by about a factor of three based solely on how they tell their story. Assuming a company has real
