The debate of qualitative versus quantiative is unlikely to ever be resolved. It was one of the first things we tackled in my Politics degree; it’s something that I was always concious of whilst I was at Miniclip last year analysing how many extra clicks posting half an hour later on Tuesday produced. With the embrace of “big data” it’s apparently something we’re all going to have to deal with at some point.
Yet weirdly for something that literally all of the cool kids are talking about there’s very little consensus about how far quantiative should be embraced over qualitative or even straight-up whether it should be embraced over qualitative at all.
The most common line you’ll see is some sort of hybrid approach is necessary, and that’s probably right — at least in my experience it’s what’s been most effective. I’m reading Nate Silver’s book The Signal and the Noise: The Art and Science of Prediction at the moment and whilst Nate ers on the side of quantiative he absolutely doesn’t think we should embrace data unreservedly and leave independent creative thought at the door.
Personally I have an immense amount of respect for those able to draw up huge amounts of data-driven formulae which offer a huge amount of insight, I’m just not very good at producing them myself. I’m also wary — mainly from my own experiences — of unreserved faith in the power of big data. If you’re not careful it only traps you into persauding yourself what you’re doing now is as effective as it can possibly be and leaves you blind to different or innovative approaches. It’s also incredibly easy to assume if something can’t easily be quantified it mustn’t be of any value or worth; that’s not true either.
So the answer’s somewhere in the middle. That’s hardly groundbreaking; we all know that, it’s just we sometimes like to forget it sometimes.
Oh, and the title? That’s so this post gets as many viral as possible. It’s using science!