Businesses today are awash in data—even if they don’t always realize it. If you use a software program (rather than a paper ledger) to keep your books, access a web-based application (and not the U.S. Postal Service) to email your customers, or count on your website (and not glad-handing at the local Shriner’s club) for leads and sales, then you are already generating massive—yes, massive!—amounts of data. And that deluge isn’t expected to lessen anytime soon. It’s been estimated that there will be a 4,300 percent increase in annual data generation by 2020.
Ignore the information at your fingertips for too long, and you risk getting left in the dust by more data-savvy competitors. But even basic data analytics can help improve your company’s bottom line, better understand your customers, and help you close more deals. Here’s a cheat sheet to moving from data deluge to data insights ASAP. (You’re welcome).
Be honest: Isn’t this something the IT department can deal with?
You might think data analytics is for geeks and number-crunchers, or that data analytics software—and the expensive computers required to house all that data—is for well-heeled enterprises with outsized IT budgets. That’s the wrong way to think about it. Sure, as CEO you might not be the person literally analyzing data sets, but data analytics is a powerful business tool that’s best deployed to steer and refine business strategies. And if you’re waiting for the IT department to bubble up some amazing insight, but you haven’t given them any direction, you’re probably going to be waiting a good long while.
OK, I’m intrigued. But first, are data analytics and big data basically the same thing?
Think of the terms as a difference of scale. Data analytics is the practice of using your company’s data to make smarter business decisions. Managing by gut instinct can get you a long way; data analytics makes sure your gut doesn’t conflict with reality. Big data is a buzzword best understood as the practice of applying data analytics to extremely big and complex data sets: all the foot traffic in a mall over the holiday season, the minute-by-minute weather patterns across an entire region, the behaviors of millions of mobile users.
How do I get access to data analytics tools?
Today, analytics tools are typically baked into a company’s bookkeeping, marketing automation, and web site management tools. More general-purpose analytics tools are often housed in the cloud, delivered as a service, and have simple user interfaces that look more like Facebook than a complex query tool. And if the data your business creates on its own isn’t enough or you want to see how it stacks up to industry numbers, you can buy more data by the byte-load.
I have the data. Now how do I make the leap to data-driven insights?
Data on its own isn’t worth much, but utilizing that data to unlock the answer to a pressing question can be priceless. List the opportunities and challenges your business faces, then phrase those issues as questions: How does my top- and bottom-line fluctuate over time, and how can I improve my cash flow to even out the spikes and valleys? What do my best customers look like, and where can I find more of them? What would be useful to know about my competitors, and how could I leverage that information to improve my own business? Once you know the questions you need addressed, you can start leveraging the data in (and outside) your business and the data analytics tools at your disposal to find strategic solutions.
Do I have to go all-in to make this whole thing worthwhile?
In a word, no. We’d advocate wading, rather than diving, into the “big data lake” (a term you might hear bandied about). Look for analytics capabilities in the applications you already depend on. Google Analytics, for instance, is free to get started and can be applied against any website. Other apps you use likely have tools for analyzing the data they generate. Ready for a deeper dive? More general-purpose data analytics tools—often called business intelligence solutions—await you, costing anywhere from $10 or $20 a month via SaaS application to hundreds of thousands of dollars upfront for an enterprise license. If you decide to expand the team’s data analytics toolkit, try adding just one new tool at a time, so it’s easier to get buy-in and measure the value each one delivers.