I had the pleasure of being a mentor and judge at Lean Startup Machine DC (#lsmdc) this weekend at GeekEasy. The participants spent the weekend learning to validate hypotheses; the winning team discovered that people would be willing to share their personal genetic data to help fight disease. They got out of the building and asked passers-by to spit into cups. They collected one sample every 3 minutes, taking the first step toward proving the viability of creating a massive genetic database to support research into personalized medicine. As they were learning, so was I. Here are a few things I learned along the way:
- Lean is hard, and not everyone will succeed.
- Small teams of experts are more prone to confirmation bias.
- The market you know is not the only market.
- You are not your target market.
Especially not in one weekend. But it’s also not a binary state. An organization can be varying degrees of lean, and the more I learn about lean startups, the more I can apply it in my own work.
If you know the space well, you need to be even more careful that you test your hypotheses with real data. Make sure people on your team can call you out. If you’re working solo or with one partner, set time aside to take a reality check with someone outside your team.
It’s tempting to sell to startups because you are one, lots of people you know work for one, and you like thinking about startups. Most startups don’t have money, so think twice. There are other markets that might have the qualities you are looking for but actually have money. For example, if you are targeting startups because you are looking for companies without entrenched policies, consider embattled companies who have hired turnaround consultants instead.
Make sure other people share your problem. It’s great to build something you want to use, but if no one else wants it, it’s a hobby, not a business.