![]() They don’t like the solution to be imposed on them. They need to be convinced, they want to be part of the creation of the solution. People don’t think in the same way that data behaves. For instance, knowing that email follow-ups to sales calls are the most time efficient is nice, but that fact is unlikely to convince a salesperson who has always picked up the phone to change his approach, especially if his approach has always worked for him. I like right answers as much as the next guy, but in my experience those answers are just not enough to motivate people to action. In that world, there is nothing to learn the right answer is given. Big data gives you the answer to whatever problem you might have (as long as you can collect enough relevant information to plug into your handy supercomputer). In fact, there is no room for imagination, for serendipitous connections to be made, for learning new things that go beyond the data. That means that big data is, by necessity, backward-looking you can only analyze what has happened in the past, not what you can imagine happening in the future. Unfortunately, analysing data to identify patterns requires you to have the data. Since the number of observations - the size of the sample - is by definition huge, the laws of statistics kick in quickly to ensure that significant relationships will be identified. If you’re not sure, just measure everything you can get your hands on. It is inherently a theoretical exercise, one that requires minimal thought once you’ve figured out what you want to measure. Analysing the attributes and characteristics of anything is guaranteed to find some patterns. One that seldom gets notice: in a world where massive datasets can be analysed to identify patterns not easily identified using simpler analogue methods, what happens to genius of the Einstein variety? Yet I don’t need to re-read George Orwell, or scan the latest headlines about the massive snooping of personal communications orchestrated by the National Security Agency in the United States to feel at least some discomfort with big data’s side effects. The benefits of big data are so, well, big, that there’s no going back. It is in those ideas - the ones that make us conjure up the image of Albert Einstein - that lead to breakthroughs. Big data can help predict what songs are likely to be hits, which wine vintages will taste better and whether chubby baseball pitchers have the right stuff.īut big data should not be confused with big ideas. Big data helps pharmaceutical companies identify the attributes of their best sales people, so they can hire, and train, more effectively. The power of big data goes far beyond figuring out what we might want to know. Indeed, the entire advertising industry has been transformed by its ability to use data to target individual consumers in ways unimaginable in the Mad Men era. Amazon, too, barrages email inboxes with book recommendations, among other things. A friend of mine recently remarked on the uncanny ability of Netflix to recommend movies that he almost always finds interesting. ![]()
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