Data goes on being the hot topic that the brand managers are craving for. They ask for some more data, always. They believe that a huge amount of information about whatever they can find, will help them to navigate their brand to success. Or perhaps, and I will tend to go more in that direction, they want to accumulate data to cover themselves and deliberately proving that their decisions are backed up with information that you can’t contradict.
And then came their bedside book. This data fever was actively inspired by the book ‘Freakonomics – A rogue economist explores the hidden side of Everything’ by LevittDubner. But what most of the brand leaders missed dramatically, this book is not about data. This book is about is about how to use data to make some useful and disruptive conclusions. And you don’t need to accumulate them, you need to nurture the talent to select them, deepen them, analyse them and correlate them. And, now, we have Tyler Vigen (not Durden) who is the proof that data should be taken with precaution and professionalism.
This Harvard Law School alumnus just claimed what nobody could really explain ‘Two sets of data might appear to be strongly linked but correlation does not equal causation’. In summary, two bunches of data might look correlated but they have nothing to do with each other. But the media and some professionals may take some harmful shortcuts to highlight what does not really exist. A month later Tyler Vigen launched his blog ‘Spurious Correlations’ (http://www.tylervigen.com/spurious-correlations), he saw a study that reported a strong correlation between Atlantic hurricanes with female names and number of fatalities. The authors were claiming that hurricanes with females’ name are more deadly because we don’t take them as seriously. These are interesting conclusions that might not reflect an obvious reality.
Here, you can enjoy some of the graphics he put together to warn people (with a pinch of deadly humor) about the delicate utilization of data. Some of them are out of this world.
If you have to lead your brands and make some conclusions, you have to be careful with data and select/understand them wisely. The conclusions are more important than the amount of them. Too much data kills data. And can kill your thinking.