Singapore is nice, but it’s not enough – The Naked Startup

Singapore is nice, but it’s not enough

April 6th, 2010 by Andy Croll

Filed under Chat

I watched Sneha’s e27 interview with Adeo Ressi, and one of the things he said troubled me. Like it troubled me before.

“Any startup that is outside the US and not in a large market… faces the challenge of too narrow a focus. We met some Singapore companies that are focussing on Singapore and that is a very small market.” Adeo Ressi, thefunded.com.

Singapore is a good place to live, it has it’s faults but where doesn’t? It’s basically clean, efficient and the sun mainly shines. And the food is amazing. Plus as a place to travel to and from it’s pretty much unbeatable.

The lifestyle, plus friends, plus a feeling that the web industry is on the verge of something and good local developers are all the reasons I stayed here and teamed up with Arun to start building the best sports league software ever (take that link Google-bot).

This is an interesting commentary post about an interesting interview discussing Singapore as a startup location. Especially what this poster has to say is quite relevant to HK as well, although our local market is about twice the size, but still similar on the order of magnitude level in comparison to global markets.

For me, I see HK (and similarly Singapore and other Asian startup locations) as being potentially a good place to build a business foundation. Looking at my own work, I’m looking at if I can get 1-2k local customers, that would be enough to keep going perpetually. And, for me, local customers would include businesses that are in the region, not just HK directly.

Would I want to stop there if I got the local customer base, no, but I think it is a unique opportunity to do customer development within a community that is physically accessible like HK. In most locations, you would be hard pressed to connect up with your customers that easily.

Minimum Desirable Product and Lean Startups (slides included!) | Andrew Chen (@andrew_chen)

Minimum Desirable Product and Lean Startups (slides included!)

Comments

(if you don’t see the slides, go here to Slideshare)


Recent slides for a talk in Steve Blank / Eric Ries’s class on High-Tech Entrepreneurship

Yesterday I had the pleasure of giving a talk at Steve and Eric’s class at Haas on the topic of Minimum Desirable Product – if you haven’t read the original article, it provides some useful context. I included an set of slides above on the topic, updated from my talk yesterday, which you can peruse at your convenience.

After you’re done, you can read my extended remarks below on some stuff I learned along the way. Frankly, any of these could probably be its own blog post but I’ve been feeling lazy lately so you get a couple sentences apiece instead :-)

This is a good read, based on a presentation given to Steve Blank’s class at Stanford. Check out the slide deck and see the additional comments as well.

Lessons Learned: Learning is better than optimization (the local maximum problem)

Learning is better than optimization (the local maximum problem)

Lean startups don’t optimize. At least, not in the traditional sense of trying to squeeze every tenth of a point out of a conversion metric or landing page. Instead, we try to accelerate with respect to validated learning about customers.

For example, I’m a big believer in split-testing. Many optimizers are in favor of split-testing, too: direct marketers, landing page and SEO experts — heck even the Google Website Optimizer team. But our interest in the tactic of split-testing is only superficially similar.

Take the infamous “41 shades of blue” split-test. I understand and respect why optimizers want to do tests like that. There are often counter-intuitive changes in customer behavior that depend on little details. In fact, the curse of product development is that sometimes small things make a huge difference and sometimes huge things make no difference. Split-testing is great for figuring out which is which.

Another excellent post by Eric Ries about how there is a need to balance metric testing with reasonable design sense to overcome getting stuck in a particular direction.