Don't make this big mistake in big data boom

To understand anything in business, you need to track it. That's because knowing how you're doing — regardless of whether we're talking about sales, logistics, customer service or anything else — is the first step in understanding how to do it better. Unfortunately, simply tracking data won't get you very far. To make it worthwhile, you've got to be able to derive meaningful insight from it.

And therein lies the challenge. While gathering data is easy enough, being able to cut through the noise and zero in on what matters most isn't.

That's why, instead of making our lives easier and enhancing our productivity, in many cases data actually just creates more work.

Artificial intelligence Big Data
Andrea Danti | Getty Images

You know what I mean. These days, we spend more time and effort aggregating, analyzing, interpreting and explaining than ever before. In fact, employees are putting more energy into preparing data for analysis than actually articulating the results. Worse yet, in some cases, organizations are sitting on treasure troves of data that could be turned into new revenue opportunities, and yet they aren't doing anything with it, because they simply lack the time and resources to put it to use.

Is big data overrated?

In an ideal world, data would work for us. We'd be able to quickly glean insight to foster new product development, deliver relevant information to our customers and ultimately make more informed business decisions. Unfortunately, we don't live in an ideal world, and big data isn't always what it's cracked up to be.

Don't believe me? I'm not the only one to have suggested that when it comes to big data, our seemingly blind optimism may be misplaced. Consider the following:

● According to a recent Gartner report, 60 percent of big data projects will fail to go beyond piloting and experimentation and will be abandoned. Other Gartner research suggests that demonstrating value from big data is the No. 1 challenge for those planning to invest in it.

● The CEO of Pneuron, a platform that enhances system development and business processing for organizations, shared that 70 percent of an enterprise project is spent identifying, aggregating, moving, storing and optimizing data before a single penny of value is created.

What this and other research suggests isn't that big data is a bad thing. On the contrary. If you can derive meaningful insight from it, you'll no doubt improve your business. The trick is, you've got to be smart about it. While gathering high-quality data is extremely important, the companies that will win the big data race are the ones that figure out how to use it effectively. The inherent danger in big data is that people tend to see patterns where none actually exist.

So how can businesses make better use of their data? And how can they strike the balance between using data to improve their business while not getting stuck in the too-much-data-too little-time trap?

The answer is that before you ever begin tracking and managing any data, you need to understand the business challenge that you're trying to address.

Let me give you an example.

We recently worked with a credit card company. Since it has access to a lot of data — it gathers and analyzes tons of information about merchants' activities, along with when, where and how their customers make purchases — it's effectively also a data company.

The company's challenge was communicating all of that data in a meaningful way in its monthly merchants report. Historically, those reports were pretty basic and contained simple findings, such as average customer spend per month, conveyed in graphs and charts. Because the reports were based on all of the available data rather than a subset of deeper insights, they were pretty generic and offered no meaningful insight. Not surprisingly, readership and utilization of the reports were quite low.

Better, not bigger

The company needed to zero in on the data that matters most to their audience by answering key questions important to its merchants, like:

  • What segment of customers spend the most money at my store?
  • What time of day do they shop?
  • What additional promotions could I be doing at this time of day to strengthen my relationship with them?"

Through this approach, they could zero in on the data that matters most. Not only would the merchants' reports be much more insightful, the analysis would also be a lot more manageable.

Getting big data right isn't easy. Many companies fail to recognize that data alone isn't the answer and, as a result, think that the more data they collect, the better. The reality is that you need to use data selectively. Start with the business challenge and home in on the information that will give you the most valuable insight. Fortunately, while too much data has certainly become a problem, it has also been the catalyst for new technologies that have emerged to overcome these challenges. Technologies such as predictive analytics, advanced natural-language generation or smart data discovery solutions can help you attain true value from your data. Then it's not too big, it's just better.

By Stuart Frankel, CEO of Narrative Science

Narrative Science was a CNBC Disruptor 50 company in 2015.