Tried and tested. Seems like a great sentiment, right?
There are plenty of businesses that have dominated their industries by simply promoting that they do what’s expected, because, well, it’s worked before.
But as we know, times are changing.
And with this change comes simpler and better ways of doing things. Unexpected ways. And sometimes the people who find these better ways aren’t the people you’d expect. Their skill-sets may lie in a completely different field, but these are people unafraid to poke and prod at the methodologies of old and find elegant new ways to revolutionise industries.
Let’s look at the horseracing industry. You know, the one that brings fancy people in fancy hats to lavish events at the track every year? Well, there is big money to be made through predicting the greatness of a horse. For centuries, hundreds of millions have been spent by enthusiastic buyers purchasing champion racehorses, based solely on pedigree and heritage. If the horse was sired by a champion whose father was a champion, he’ll likely be a champion himself, right?
As it turns out, having a good history won’t necessarily win you gold. In 2006, a colt named The Green Monkey sold for a staggering $16mil, based solely on his family’s history of winning. Unfortunately for the new buyer, he never saw his return on investment, with the colt failing to win a single race.
Jeffrey Seder, a Harvard-educated lawyer and rising analyst, was new to the field of horseracing, but decided to use his knack for collecting and understanding data to delve a little deeper. Seder quickly deduced that The Green Monkey had a snag in his running pattern, which resulted in his poor performance.
Continuing to collect data and apply statistics, he concluded that a horse’s heart, lungs and gait were the true factors in identifying a future champion. And the proof of the pudding is in the eating. His research is behind the careers of dozens of Stakes winners, most notably American Pharoah, winner of the Triple Crown and the greatest horse in recent memory. Did we mention American Pharoah was dismissed by experts due to an inferior bloodline? Oops.
And so, unexpectedly, a lawyer reshaped the horseracing industry.
Arguably even more steeped in tradition is the wine industry. Before a wine is fully aged, connoisseurs need to predict how the wine will develop and improve over time and this prediction heavily influences the price of the vintage.
Prof. Orley Ashenfelter, an economist, noticed that these predictions were not particularly good. Armed with the weather data of the Bordeaux vineyards and their wines’ eventual auction prices, Ashenfelter set out to find some better predictors of quality. Using one of the base techniques in a statistician’s toolkit, “multiple linear regression”, he came up with the following formula for a wine’s price:
Price = e^(12.145 + 0.00117*winter rainfall + 0.0614*average growing season temperature - 0.00386*harvest rainfall)
Nothing says good wine like a good equation, right? Needless to say, the Bordeaux wine industry’s response to his findings was not positive. But, as it turns out, the formula works. Ashenfelter took a skill acquired in 1st year stats and pointed it at an industry traditionally untouched by statistics.
Even our very own Elon Musk attributes his success to his experience in so many different industries. From PayPal and Tesla, all the way through to Space X, his learnings in each field have given him a unique approach to creative problem solving that is quickly changing the world.
At Naked, we like to think that we have our own unique version of “cross pollination” that is helping to shake up the insurance industry. Instead of relying on the outdated structures of yesteryear, we’ve delved into the world of behavioural economics, technology and AI to create a solution that works better for our customers. But that’s just us.
What about you?
What skills do you have stored away that could be the starting point of revolutionising an industry you’d never dreamed you’d be a part of? Opportunity may be staring you right in the face.