The promise of big data is large, and, for the most part, it’s delivering. From granting faster insight into a wider array of problems, demographics, variables, and more, businesses are learning in a week’s time what it used to take a year to uncover. That being said, today’s bigger and better data doesn’t provide businesses with a built-in and guaranteed Grand Slam. Like all tools, it’s only useful if properly applied. The goal of big data isn’t simply knowing more; it’s knowing what to do once more is known. If you’ve boarded the big data train, but you aren’t sure where to take let it take you, here is a little help on how to make better business decisions with big data.
Make It Visual
One key to the better utilization of big data is to make it visual. With reporting software from companies like Windward, you can not only gain more information, but you can also ensure that that increase in information is ascertained by you and your employees, quickly and meaningfully. When data is only encountered in lists, files, or spreadsheets, it can be too unwieldy — even if the information it contains is sophisticated. Don’t leave your big data so big you can’t see it. Invest in tools that will make it easy to visualize. You’ll not only understand it faster and with more nuance, but your ability to move into the decision-making phase regarding what it reveals will be faster and more nuanced, too.
Let’s say you’re in the business of selling T-shirts, and you’ve just discovered through analytics that shirts in robin’s egg blue are selling like hotcakes on a competitors’ site. If you’re a bit overeager, you might be tempted to order up 10,000 t-shirts in robin’s egg blue, so you, too, can capitalize on the emerging trend. The trouble with that approach is that data doesn’t always tell the whole story.
Perhaps a celebrity tweeted about a very particular brand of shirt and color, and that’s what’s driving sales on the other site. Maybe that site is doing a fundraiser with all the proceeds from those shirts going to charity. Either way, by jumping in with only part of the story, your company ends up with thousands of t-shirts it won’t have an easy time selling. Big data requires good balance. Don’t jump on trends for the sake of jumping on trends. Keep a hold of your overall mission and values, and look deeply into the data to uncover the real story of what’s going on.
Don’t Forget the Customer
Because big data offers such seemingly god-like capabilities, it can be difficult for some businesses to remember that sales only happen because of customers. In other words, don’t get so data-centric that you forget the human element that’s a part of every business deal you make. Your customers need to remain the centerpiece of your efforts, or all the knowledge in the world isn’t going to help you. Good decisions are focused on meeting customer needs and expectations — not just capitalizing on big data.
Big data can’t tell you everything, and, while it seems like it’s capable of predicting the future, it really can’t. Stay realistic about what you’re actually able to know. The future is unwritten, which is why — even in the age of analytics — human wisdom and caution are still essential in business. Without being overly stodgy in your approach, practice a realism that lets big data inform what you’re up to without expecting it to take all the risk out of running a business. Yes, you can know a lot, but you’ll never know everything.
Examine Your Biases
Sometimes, insights gleaned from big data can end up shoring up preconceptions that aren’t actually correct. Whenever you encounter a data set that makes you want to exclaim, “I knew it!” pause and consider your biases. For example, you may think pumpkin is the best flavor of everything from granola bars and pie to lattes and beer. So, when big data reveals pumpkin-flavored hot chocolate is all the rage at your downtown hot chocolate bar, you assume it always will be. That’s a conclusion drawn because of a bias. November taste profiles probably won’t apply in January. Without good insight into your own biases, your decisions — even if they seem to be based in data — will be faulty.
Better data can lead to better decisions, so long as you practice an approach that takes big data with at least the grains of salt listed here.