When we talk to customers, fellow entrepreneurs, or others in the Miami startup community I frequently encounter some form of the following question:
“How did you decide to make the jump from a comfortable salary, benefits, and a predictable career path to get Flomio off the ground?”
Well, being accepted into TechStars was a big part of it (more on that later).
The other part of the story – contrary to what most folks think – wasn’t impulsive. Instead it was a highly calculated move that approached the question from a few different perspectives. This post is my attempt to disect that process and illustrate how such a seemingly huge decision became rather obvious with the right approach.
1-3 Drag Coefficients
Finding a framework to assess my tolerance for risk was a critical first step before making the startup plunge. How much financial risk could I realistically take on at this point of my life? How will that change with time?
(spoiler alert: it decreases substantially)
Jason Freedman has a great post outlining a scoring system for drag coefficients. 1-3 drag coefficients mean you’re ready to be a startup founder (with the epic risk, huge potential upside, and all the responsibility that entails). 4-6 for early seed stage employees (company has traction already, you have a guaranteed salary, but you only own 1-5% of the company), and 7+ for later employees post Series A (revenue! the most stable bucket – with potential for a nice pay day but probably no riches).
I applied this method to my current circumstances:
- 1 point: For every 5 years after the age of 20
- Nope
- 1 point: Ring, fiance or spouse
- Nope
- 1 point: Mortgage
- Nope
- 1 point: Undergraduate loans
- +1 Drag Coefficient
- 1 point: Graduate school loans
- Nope
- 1 point: Each kid
- Nope
No mortgage, no wife, no rings, and no kids. I did take a few student loans – about $6,000 which is pretty small compared to the national average but technically this caused me to pickup one point there. Still with just one drag coefficient it’s clear my risk tolerance was quite high at this point in my life. It was also equally clear that this won’t be the case for too much longer – I hope to have some of the other factors (like kids) in my life at some point.
Conclusion: My tolerance for risk was probably close to an absolute maximum and would decrease over time.
Rapidly Increasing Opportunity Cost
I knew I wouldn’t be earning the same salary or benefits in the startup world. Pre-funding we’d barely have enough money to cover expenses so I’d expect to earn about 25% of my previous salary level. Post-Funding things would get better but still probably top out in the 50-60% range, a pretty big difference.
On top of this I’d forfeit a sizable stock grant I was given as a signing bonus. The vesting schedule was set to a five year period and I’d only completed a year and a half – I’d be leaving 80% of it on the table.
Losing money sucks, but what’s worse is losing a lot of money.
The compensation structure at most Big Tech firms is setup to incent you to stay put. Each year you earn additional options or grants set on a multi year vesting schedule. This starts to compound after three or four years, quickly getting to the point where a departure is just too expensive.
Conclusion: Walking away would become increasingly painful and eventually reach a point where it didn’t make financial sense anymore.
Learning from the Index is Free
I’d always wanted to move into a more business oriented role. I’d considered going back to school but obtaining an MBA from a top tier b-school can run as high as $300k when you account for tuition, cost of living, and foregone wages. I imagine I’d pickup some skills and build a strong network but the additional debt would hike up my drag coefficients and severely limit my flexibility.
Meanwhile, entering startup life would expose me to life-and-death decisions on venture financing, marketing strategies, sales projections, distribution techniques, strategy, etc. It would be invaluable hands on experience that would prepare me for the next startup. All at the fraction of the cost of a traditional MBA program.
“We learn from the index, not the table of contents”
Conclusion: Learning from the index is efficient, effective, and cheap.
Minimizing Regret
And finally, I found Jeff Bezos’ Regret Minimization Framework to be appropriate:
[youtube=https://www.youtube.com/watch?v=jwG_qR6XmDQ]
My favorite part:
I wanted to project myself forward to age 80 and look back on my life – looking back on my life I wanted to minimize the number of regrets I had.
I knew that when I was 80 I was not going to regret having tried this. I was not going to regret having trying to participate in this thing called the internet that I thought was going to be a really big deal. I knew if I failed – I wouldn’t regret that.
But I knew the one thing I might regret is not ever having tried. It knew that would haunt me every day.
And so when I thought about it that way, it was an incredibly easy decision.
It’s a powerful approach to take because it uses our mortality to help silence some of the short term noise that might distort your thinking. One day you’re going to expire, so why not make your time count? It’s the ultimate long view.
Conclusion: Years from now you won’t rerget failure. You regret not trying.
Conclusion
Just like software engineering, when faced with a big decision it’s important to approach it with a number of different frameworks before moving forward. They help minimize errors, inject a dose of objectivity, and reduce noise. If you do it right an otherwise daunting decision becomes rather obvious.