For video game fans of the early nineties, and Internet meme lovers ever since, the phrase “all your bases are belong to us” is legendary. It first appeared in a game called Zero Wing and stands as a testament to mistranslation. For many businesses, big data and analytics is a classic case of “all your bases are belong to us.” You know the data is out there. You also know you should be able to do something with it, because just about every business magazine and marketing expert alive tells you so. Yet, when you get your hands on the data, it leaves you scratching your head.
Volume is a big part of the problem. With the ever-expanding set of opportunities to gather ever more data, it’s painfully easy to lose the financially valuable trees through the nigh infinite data forest. Culling useful knowledge from that vast expanse of information requires a combination of sufficient processor resources, a viable analytics 2.0 program and a sense of what benefits your business. Without that combination of factors, you run a real risk of mistranslating your data.
Now, with any luck, you’ve got a good sense of what matters to your business and your staff knows what information they need from big data. Any good IT person can get you set up with the right technological infrastructure to process all that data, or you can sign on with a cloud-based analytics service that processes it for you. Where things get tricky is the software.
Just because an analytics 2.0 program can show you the data you’re interested in, doesn’t mean that it’s going to show you that data by default. Even with vendor assisted customization, analytics programs often lack an intuitive interface that lets you easily move from a big-picture view to drilling down into a highly selective data set. The less intuitive the program, the less “all your data are belong to you.” The data becomes the software’s hostage and you’re left in the unenviable role of hostage negotiator with your business success on the line.
What’s worse is that un-intuitive programs are likely to lead you to misread the end results of any given analytics function. Maybe you were looking for overall social sentiment about your new product and all you’re getting is social sentiment from Instagram. If you don’t catch that error immediately, it can be disastrous. Regardless of social sentiment on Instagram, you wind up with an incomplete and undoubtedly skewed view of social sentiment regarding your new product. Since you can’t avoid sanely big data and analytics are the inevitable end result of big data, you need to stack the deck in your favor where you can: the software. When you go to make that investment, be sure the software is intuitive to use not only for you, but for your staff as well.