The weather is hot and dry in Los Angeles, California and at first sight, not much seems to be going on, on the corner of Patton and Colton Street. There are no cars and no traffic to speak of. People are hard at work with simple tools, little capital and an iron will to succeed. They want to be part of the next big boom in California. Their expectation of success fuels their ambition, which could lead to unimaginable wealth. This makes good for the long hours at work where success and failure are always close to one another, almost connected. Success could not only change these people’s lives but could also have a lasting effect on the rest of the world. Neither a casual onlooker nor an experienced insider could predict the success or failure of this new venture. Such is the way of venture capital.
It is 1892. The start-up venture on the corner of Patton and Colton Street is digging for oil, and the company that springs from this oil well will become the largest oil company in the world by 1920 and eventually become part of today’s British Petroleum or BP with a market value of $125 Billion.
What made this venture run by Edward Doheny, with an initial $400 investment, so successful? Was it the man, the money, skill or plain luck? Why was he even digging for oil when mass production cars would only be made available to consumers some sixteen years later?
Today’s spreadsheet ninjas, Artificial Intelligence algorithm-modelers, and creative geniuses probably laugh at the idea of a start-up using a shovel and a pickaxe. They would argue that there is no narrative to buy into or any numbers to run. They would be right to say that the predictability of such a venture would be near zero. To me, the reality is that there is a lot of digging going on and the holes are big and deep and it is 2016. It might not be with a shovel and pickaxe but with new software and ingenuity. So, how can we predict the winners for start-ups or for established companies?
“Well, well, well (no pun intended), you opened a can of worms here Vincent. Is this not a question for the experts, the financial experts?” you say. Yes, I say, but there is no consensus you see. Look at the expert’s “stock market predictions” for 2017. They are all over the place and even the very experienced “expert” Byron Wien from Blackstone with his yearly 10 surprise predictions for the stock market admits there are ALWAYS things happening in the market messing with his predictions, always.
Ed Doheny knew of oil seeping through the ground in what is now part of Los Angeles. He knew he had a reasonable chance to find oil and had acquired the necessary skill as a digger and driller. Still, he would have been broke after hitting two dry wells, so he got lucky hitting oil on the first one. It produced approximately 7 oil barrels per day making it possible to redeploy cash earnings towards additional drilling wells and grow. Competition came quickly and was fierce but all successful oil ventures at the time were tremendously helped by a huge surge in oil demand because of mass production of automobiles and an overall switch from steam to combustion engines.
You see, you need more than the idea, the stamina, and the skills in order to succeed in a huge way. You also need luck and it is not pleasant to admit because this is something we cannot control. The less predictable a system is, the more luck you need to be successful predicting it. This is why start-up ventures are so hard to analyze and their successes so unpredictable. This is why established businesses are easier to analyze and predict. There is value in the persistence of predictive values. Just look at Michael Phelps, who is undoubtedly the most skilled swimmer in the history of the Olympic games with 23 gold medals. It became easy to predict his wins since the environment he competed in was exactly the same year after year and therefore luck had nothing to do with it.
When analyzing companies, it pays to look for skill and luck as separate factors of success. The more skill you find in a company the easier it will be to predict its long-term success. Simple tests for skill levels are looking at cause and effect of management decisions over time, at an ability to sustain or improve financial outperformance and the overall predictability of companies’ success and financial performance against competitors and challengers.
What are you waiting for? Start digging. You might get lucky!