When it comes to elite performance, data doesn’t always tell the whole story.
You might be a three-time world champion with a perfect record and all the stats to back up your superiority, but there is always that chance of something going wrong. The Team GB canoeist David Florence has exactly these attributes, but two basic errors in the final left him a long way behind the pace. He was one of GB’s biggest gold medal hopes, but he crashed and burned (or maybe that should be drowned). Likewise, in the men’s gymnastics team final, the most precise of sports, our world-class gymnast Louis Smith fell off during his pommel horse routine. Shock, horror, the historic data does not always predict the result.
This is the argument that the detractors of Big Data will use…. It is not a perfect science, and there are enough occasions when the result is entirely different. Why invest so much in the use of data when it can’t guarantee perfection?
Well, this is one of the big fallacies of the industry. Too many CEOs expect Big Data to offer every answer, but the moment that it gets something wrong, they start to doubt it entirely. They assume that because there is a huge amount of information being analysed that the chances of mistakes should be infinitesimally small.
In some cases that is true, but especially when there are human factors involved, Big Data has to be deployed with a healthy amount of caution. Its predictive powers may still get 95% of the results right, just as you can probably predict the vast majority of the medalists at the Rio Olympics, but what colour medal they win or who will miss out entirely seems to be one step too far.
Whenever there is a Big Data conversation with senior executives, expectations have to be set correctly, and it is at this junction between statistics and the real world that misconceptions often occur. Big Data isn’t perfect, but it is a lot better than the more superficial methods of making a judgment.
I suppose that the ultimate proponents of Big Data in sport are the bookmakers, and it is a perfect justification of my argument that they do “win” in the majority of cases. However, every now and again there is a sporting shock, and they lose an awful lot of money. If your business cannot afford to make this level of mistakes, it is worth understanding that Big Data will get you much of the way there, but it won’t unfailingly provide you with all of the answers all of the time.
As with many things in life, even with the seemingly most perfect things (like Louis Smith on the pommel horse), there is always a margin for error.
Big Data does not rule the Olympics, but it gets close enough.