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Big Data: It’s Not How Big it is, it’s How You Use it

The recent rush of businesses to get aboard the big data train is a bit like the folks who stock up on exercise equipment and then congratulate themselves for being fit while the unused treadmill lives out its days as a drying rack.

In other words, it’s one thing to have reams of data at your disposal, but quite another to make effective use of it.


No doubt, the big data revolution has blown wide our view into customers’ preferences, behaviours and brand loyalties and into competitors’ activities and strategies. But until businesses get better at applying analytic insights to their stockpile of info, it’s all for naught. Indeed, a recent study by SAS and the MIT Sloan Management Review identified the ability to translate available analytics into a business action plan as the biggest barrier to success with big data.

The best way to clear the barrier? To approach your data with specific goals in mind.

That means honing in on what you hope your access to this information will do for your company. Do you want to increase market penetration? Boost profits? Find out what people are saying about you? Understand why your customers are leaving you?

In identifying these questions, it’s clever to think in more strategically oriented and forward-looking terms, rather than of questions that are purely operational or historical customer- or product-performance in nature. So instead of taking stock of who your customers are, for example, you might tilt the data to consider who your customers will be.

And always remember the value that technology can lend to your pursuits. The smartest means of parsing your massive stash of data, after all, is to apply the smartest and most sophisticated data-analytics tools to the task.

The gifts big data lays before us are considerable, but only if we make the right demands of it. A study recently conducted by Oracle found that 94 percent of executives heading up companies who use big data are losing money because they’re not leveraging the stuff to the extent they might.

By nominating a list of specific questions about what you hope your data can do for you, you can sidestep joining their ranks.

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