[Note: this is from my experiences in computer architecture and systems research. Your mileage may vary when applying this blog post to other fields.]
Earlier, I wrote about how my PhD unexpectedly provided a good foundation for entrepreneurship. It is almost a year later, and I still feel good about that blog post. Much of it remains true.
However, not everything carried over well from my PhD. As I’ve gotten further into entrepreneurship and the startup world, I’ve begun to realize two big differences that have been tough for me to adjust to.
(1) Time scales are much longer in entrepreneurship.
If you look at publication records these days, it is common for a great graduate student to publish 2+ top-tier conference papers per year. It is common for great professors to publish 5-10 or even more top-tier conference papers a year.
Think about this. Each paper requires a peer review, and top-tier conferences have fairly low acceptance rates (5-20%). Let’s assume a great student experiences a 50% accept rate. In order for a great grad student to publish 2+ top-tier papers a year, they are most likely working on 4+ papers a year, or at least one every 3 months.
A paper is a full production, requiring ideation, implementation, experimentation, and writing. Completing a full round in a few months is aggressive, but possible. I personally have done it, and know most of my friends with PhDs have.
This means that within academia, you are used to entire projects which turn around in just a few months. Once that one is done, it is on to the next! Things move quickly, and you get this awesome feeling of accomplishment each time you close the loop.
Startups and entrepreneurship work on a much, much larger time scale. You don’t get that feeling of accomplishment every few months. You may reach failure within a few months. But you will rarely reach success.
Finding product-market fit can take years. A great content marketing strategy can take years. Growing and scaling a product can take years.
A quick search easily confirms this. Pinterest was founded in 2009. Lyft was spun out of Zimride, which was founded in 2007. Snapchat was founded in 2011. It is now the end of 2013 and although these startups are fairly big, there is much room for growth.
Managing this difference requires managing your expectations. Understand that building a startup takes time. You better be in it for the long haul.
(2) Developing a new optimization function
Academia and entrepreneurship require completely different optimization functions.
In academia, you ask: what is novel and publishable?
In entrepreneurship, you ask: what do people want?
Being able to answer these questions requires a combination of knowledge and gut instinct (others may call it vision). Building the knowledge takes time. So does building a good gut instinct.
For an ex-academic, this difference is deadly. You spend years building your knowledge, and then years publishing. At the end of this, you believe you are smart! You think you know your stuff!
This is a huge trap. If you follow your academic instincts into entrepreneurship, you are most likely doomed for failure.
(Note: Stanford kids seem much better at this than most, and it must be because the culture is just different).
Managing this difference requires understanding this difference in optimization function. From my experience, it sounds easy in theory, but is very difficult in practice. Ignoring a trained gut instinct is tough. Developing a new optimization function is tough. Combine this with the first point, and realize it will just take time.
To you ex-academic entrepreneurs out there, good luck! I would love to hear how you are doing, and how you’ve managed the transition.
P.S. This today’s step as post 3/100 in a 100 day blogging challenge. See you tomorrow!
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