What's luck got to do with it?

Tech success is there for the taking. And luck has absolutely nothing to do with it. Or has it?

Definition of luck: “Success or failure apparently brought by chance rather than through one’s own actions”

Whilst discussing the part luck plays in tech success, an old friend who works in the film industry claimed that most tech founders/CEOs were there almost due to random luck. That Zuckerberg had simply made a website at a very fortuitous time. [It turns out he had been drinking before he tweeted this so he is forgiven.]

But for argument’s sake, let’s just pause there a second…

But clearly this is my experience so I reached out to entrepreneur Nicholas Russell about what part he feels luck plays, and this is what he had to say:

In terms of the balance of luck and probability, there are three quotes that are useful to explore:-

1) “Luck is probability taken personally”

2) “The harder I work, the luckier I get”

3) “Always bet on the butcher… never bet on the pig”

“Luck is probability taken personally”

When startups / entrepreneurs cite ‘luck’ as a factor, the read is that they’re generally attributing some part of success to chance. Every entrepreneur knows that the likely outcome is failure. Therefore, when one is successful, to what does one attribute the success? It’s impossible to localise one discreet reason for winning, given the total population. Great startups fail. Smart people fail. An entrepreneur can do everything right, and still fail.

When an entrepreneur fails?—?as is the probability?—?there’s little to be said, because failure was the most probably outcome. When an entrepreneur succeeds, either in a specific individual moment, or in exiting the company for a life-changing amount of money, they’ve beaten the probability in essence. Perhaps it comes from the casino, when beating the odds is attributable to ‘luck’. Regardless, a hypothetical entrepreneur has beaten the odds, and wins. To what do they attribute the win?

If the entrepreneur is being interviewed and asked, “Why did you win?”, any answer the entrepreneur gives will be bounded and made irrelevant by the probability distribution.

“We won because we worked hard,” doesn’t explain it, because the probability will say that someone worked harder and still failed.

“We won because we were the smartest,” doesn’t explain it, because the probability again says that someone was smarter and still failed.

“We won because we were not the smartest,” doesn’t explain it, because the probability ensures that there was someone less smart that failed.

The human brain *loves* binaries and singular examples. Hence the rise of Tinder. Rather than reviewing potential matches based on a large dataset of comparable factors, Tinder appeals to the most basic function of the mind, in or out. Similarly, when entrepreneurs win, they want to designate that to something?—?to a quality, to a moment, to a decision. That is the equivalent of attempting to pull one instrument out of an orchestra and say, “It’s the second flute that makes this a truly unique Rachmaninov.” Any answer given is an oversimplification.

Thus the truth, which is that the entrepreneur doesn’t really know why they succeeded, because success is not assigned by the entrepreneur, but rather by the market. The reason entrepreneurs win is clear?—?best product-market fit, and then best defensibility. So if the market assigns the winner, that means that the factors which led the entrepreneur to victory were external, while the win is very much internal. The market chooses the winners, and then we celebrate the winners. Thus, a winning entrepreneur got a huge numbers of decisions right and beat the odds. It’s such a complex probability equation, that when asked why they won, many will say, “It was hard work, a great team, and good luck.” Good Luck standing in as a variable meaning ‘there was an intensely complex system that delivered this result that is generally unknowable, and its outcome favoured me.”

“The harder I work, the luckier I get”

If luck is chance, then how can one work for luck? It goes back to the old riddle about the three doors and the goat. If you don’t know it, it’s quitefamous. The interesting thing about probability is that the probability of underlying systems can generally be measured and predicted, only it’s very difficult to do that. Blackjack is easily won if one knows the system and practices the make?—?as the MIT Blackjack team proved. It’s possible to beat the system, but one first must know as many variables as possible from within the system. The first challenge is determining the boundaries of the system, and what the variables are.

When an entrepreneur says, “The harder I work, the luckier I get,” it means they’re coming closer to achieving the non-probabilistic outcome from Point 1 through a constant process of testing the system and refining the understanding. An entrepreneur who pitches 100 VCs will have a better understanding of How To Win At Raising Capital than an entrepreneur who pitches 50, or 10 because beyond the straight up moment of the pitch, and the outcome, there’s a deep understanding as to the process of pitching; how the system works; what feedback means; what’s important to pay attention to and what’s not.

Better knowledge of the system enables better decision making in the moment. Hence, the harder an entrepreneur works to know the system, the luckier they get. This mean that as they uncover the probabilities of the system, and the key variables, the better their chances of winning.

Peter Thiel has a great point on this in Zero to One, when he says that there are two ways to play the entrepreneurship game. One is to bet on random chance and go for a large portfolio that will naturally de-risk individual companies. He does not agree with that. His view is that by best understanding the system, you can take a view on which companies will be successful and instead of having the standard VC portfolio of three that fail, four that are zombies, two that return capital, and one that is a superstar, you can fill the portfolio with just the companies that will return capital and are superstars?—?if you know what you’re looking for.

In Moneyball : The Art of Winning An Unfair Game?—?a book about how the Oakland Athletics baseball team used sabermetrics to win the Baseball World Series?—?the data says that the most important factor for a baseball player is not to get out. That is the underlying key variable that is overweight in winning games. Similarly, in blackjack, the key is to use the double down, as that’s the only moment in the whole casino when the player can modify their bet after having new information. Given that the odds of blackjack are weighted 55% to the house and 45% to the player, if a player plays perfect straight rules, eventually they’ll lose. Using the double down tool enables the player to increase their return potential after having new information.

It’s all about the information coming from the system, and Thiel’s point is that the better you know the system, the more intelligent bets can be placed. So, if “luck” means that an unlikely positive outcome came from a system too complex to understand intuitively, the next maxim then is “The harder I work, the luckier I get”, which means that the more I work to understand the specific systemic dynamics of a system, the more likely ‘the unknowable system’ works in my favour.

“Always bet on the butcher, never bet on the pig”

Consider the fallacy of a British startup winning?—?when the most oft-used quote is that 1% of startups achieve VC funding (say there are e.g. 600,000startups launched), and of those 50% fail, then you potentially have only 3,000 which may succeed (clearly not all businesses launched are “startups”). So the startup will say, “Wow I got lucky because I was the 1 in 3,000”. But the reality of that has to do with so many other factors for example, the failure rate in some categories?—?marketplaces for example are much higher than the failure rate in other categories such as SaaS. Further, those odds are patently incorrect because they’re not continuous. Once a startup has achieved initial VC funding?—?being 1 in 3,000 - well, that race has been run and therefore the numbers change again.

It’s all about localising the probabilities. Because the entrepreneur thinks “It’s me vs all other entrepreneurs” when the better comparison would be “It’s me vs all those entrepreneurs doing a medical SaaS platform that interfaces with the NHS and was funded in 2013.” All of a sudden, it’s a much smaller universe. It’s easy to see the system underlying that. Then, perhaps instead of “I was lucky,” the entrepreneur can distill it to a specific feature or decision?—?like when Mark Zuckerberg decided to pause everything at Facebook and take the ad platform to mobile. In the pantheon of technology companies, that may or may not have been the correct decision. Among social networks, it turned out to be extremely prescient yet to Zuckerberg, it probably didn’t seem like he got lucky. It probably seemed like he’s spent the best part of 10 years understanding the space, customers, decision makers, and so on. Or, in other words, understanding the system.

I like Nicholas’ thoughts on luck but I would also like to add the following. As far as I can see, “luck” is largely dependent on three further factors:

1. One’s own definition of luck
2. One’s environment?—?those who fought hardship view luck very differently to those who didn’t
3. How humble one is
   
   

Further to point 2, Does hardship create as much “luck” as privilege? I have interviewed enough entrepreneurs in my time to see that those who had very difficult childhoods can quite often be those who have the deepest drive to succeed. Look at Elon Musk, Dame Stephanie Shirley, Tony Robbins, Duane Jackson. Even Steve Jobs was said to have been driven by his initial rejection as a child.

Take a chance on me

Marc Andreessen also looked at what role luck played back in 2007 when he discussed Chase, Chance, and Creativity: The Lucky Art of Novelty on his blogand especially interesting was his summary of the book:

The fact is there are many factors affecting success/failure of startups. Paul Graham even lists some startup mistakes which, as he points out, you can put into reverse to work out what factors might actually lead to success. He lists 18 but one could probably find more.

So, in summary: timing, team, funding, competition, adversity, opportunity, background, economic climate, courage, confidence, environment, gender, privilege?—?all these factors play a part but whether you can accelerate serendipity or not, one thing is for sure. It is all about chances.

In fact, life, like startups, is all about chances. Whether you were brought up with the confidence and encouragement a safe, well-resourced household affords, or brought up with a toughness that demanded a better life. Each of us take chances, and some of our chances will fail, and some might well succeed. But the hardest choice of all is working out which chances are ours for the taking. And I think now, possibly for the first time, one thing is certainly true?—?we will all have chances, and there has never been a better time in history to take them.

So, in closing, and in the words of Hunter S. Thompson, I recommend you…

“Buy the ticket. Take the ride.”

Thanks to Nicholas Russell, Alex Depledge, and Joshua Newnham.

Further reading:
The Luck Factor as recommended by Malcolm Earp