I’ve posted in the past about the Big Data boom and the little data revolution, and the conversation is still relevant. Of course, data in any quantity is an asset—no, a necessity—to the business world, and you’d be hard-pressed to find anyone to argue that point. But Big Data specifically, defined as “the ever-expanding structured, unstructured, and semi structured data that organizations of all sizes generate and collect – then struggle to store, manage and analyze,”—yes, that’s a mouthful—plays an unequivocal role in the enterprise ebb and flow.
Big Data plays a vital role in business
Including machine-generated data and information gathered from social media, Big Data allows companies to effectively connect with customers, navigate markets, and determine the efficiency of resource usage and internal operations. Ok, we all know it’s important. But there’s just one problem: There are so many components, and so many questions about analytics, that it can get very overwhelming very fast. How do you determine what’s relevant? And what do you do with that knowledge once you invest time and money into getting it? It’s clear every business needs to use Big Data to succeed. What’s interesting, though, is just as with most things in life, some of you out there are better at it than others.
Big Data rock stars
Forbes recently reported on some Big Data rock stars. UPS, for example, saves $50 million annually in fuel, maintenance, and time by using route data they collected to minimize the number of left turns drivers had to make. Less time spent waiting at traffic lights for these turns, along with installing specialized part sensors in vehicles, has also reduced carbon dioxide emissions and saved 1.5 million gallons of fuel.
And, as CTOVision.com reports, Costco also collects big data; in their case, on every purchase their customers make. When there was a recent “tainted fruit” recall, Costco was able to connect with every single person who bought that fruit – all within a 24-hour timeframe. Moves like that drive increased customer loyalty and eventually increased revenue.
So, is Big Data powerful? Yes. Can it be overwhelming? Absolutely. Can you spend big in people, tools, and processes to harness the power of Big Data and still come up short? You bet. But there’s a strategy to help you get the most out of your Big Data investment. Rather than drowning in a sea of Big Data, let a targeted, one-at-a-time project approach be your life raft.
A targeted approach can mean more worthwhile results
It sounds like a great idea to run multiple Big Data projects at once to get more robust results with less turnaround time, but that quick-fire approach isn’t always the best move. If you’re not careful, you could end up spending big money on the front end of data analytics projects only to have that “wave of information” opportunity turn into a trickle when it comes time for results. Why? There are so many possibilities for Big Data that it’s easy to get pulled from your focus, lose direction, or change course mid-project. You could end up with several tasks in progress simultaneously and in different stages. The kicker here is that multi-faceted projects aimed to solve the same business problem often rely upon the results of one another; if one slows, every project under that umbrella suffers.
Instead, consider minimizing the number of variables you’re trying to tackle at one time and start with a top-level problem first. Devote your resources to thoroughly gathering and analyzing the Big Data surrounding this issue, then implementing it in a way that has the widest reach. After that, move down to other, less critical business challenges you want to address. This waterfall, one-at-a-time project approach will give you better returns and more meaningful insights.
You want your Big Data to work for you, not the other way around. After all, you’ve invested the time and money into its collection and deserve to reap the benefits; a targeted, one-at-a-time approach can help you get there.
How are you navigating the implications of all that data within your business? Have you adopted a singular approach with Big Data projects, or do you have multiple irons in the fire at once? Either way, I’d love to hear about your experiences throughout the process of learning to master and capitalize on the data influx.
Source (digitalistmag): bit.ly/1Igti1c