If you wanted to be a great footballer, would it make sense to avoid kicking the ball for the first two minutes of every game?
The intuitive answer is obviously no.
There is no reason to believe that doing nothing could ever be a good strategy.
But surprisingly, we know that Lionel Messi does exactly that.
He quite literally just walks around and watches, which explains why he rarely scores in the first five minutes and in the first two minutes of a game.
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There is, however, method to this madness because not only does Messi use this time to quieten his nerves, but he also uses it to develop his game plan.
Pep Guardiola, who coached him from 2008 to 2012, explained that he’s not being lazy. He is actually incredibly engaged, as he is watching the opposition in order to understand where the defensive weak points are.
Messi provides a unique example of how, by analyzing and then acting on data, we can give ourselves a competitive edge.
And data analysis, when done well, can also help companies unlock huge opportunities by allowing them to make decisions that, like Messi’s, seem intuitively wrong.
Take Yongqianbao, a Chinese financial services provider.
By analyzing consumer behavior, they know that people who type faster are less likely to default, which in turn allows them to provide credit at better rates than their competitors.
Another example comes from the video streaming industry. Conventional wisdom has always been that you should give your customers an interface that provides them with plenty of choices about what to watch. Choice was seen as a key feature if you wanted your app to be successful.
But thanks to TikTok, we have learned that giving consumers a choice isn’t a feature; it’s actually more of a bug.
Think for a minute about how you interact with TikTok on your device.
You just open the app and start watching, right? If you like what you see, you keep watching. If you don’t, you scroll on.
TikTok has ignored the conventional wisdom and removed choice to ensure they collect better data for their algorithms. This, in turn, allows them to deliver incredibly- accurate content based on what we actually want, not what we think we want.
Our taps and swipes have enabled them to create a platform that reportedly has over 1 billion users and average viewing times that are estimated to surpass YouTube by 12 or more minutes a day.
Anecdotes like this showcase why leaders should think less about using their “experience” or “intuition” when making decisions and instead invest more of their time and money into data-led decision-making.
Indeed, when we zoom out, it should not be surprising to learn that nine of the most valuable companies in the world are successful either because of their clever use of data or because they help their clients better use data at scale.
But if data is indeed the new oil, why do the majority of companies seem unwilling or at least unable to monetize it in the same way the top tech firms have?
Historically, cost would have been the obvious answer, but this is less relevant today, as cloud and other related technologies are making it easier and cheaper for everyone to analyze data at scale.
This leads me to conclude that the real barrier to tech- enablement comes down to the organization’s cultural maturity.
If you want to truly embrace the power of data across an organization, you can only do this if you grant more people the authority to investigate and use algorithms to make business decisions in real-time. This means delegating decision-making. Encouraging continual learning. Allowing experimentation. Accepting that mistakes will be made. Not many organizations have leadership teams that are bold enough to truly trust their people with these levels of autonomy.
But those that do have will have a significant advantage because true digitization only comes when you are both tech-enabled and human- empowered.
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