The term "big data" is practically synonymous with large-scale software projects and enterprise-wide implementations. The more you read about it, the more you might believe that such pricey, pain-in-the-neck endeavors are the only path to useful insights. 

But as David Meer points out in a recent article in strategy + business, sometimes "little data" is all you have access to. "For instance," he writes, "point-of-sale register data is not standard in emerging markets. In most B2B industries, companies have access to their own sales and shipment data but have little visibility into overall market volumes or what their competitors are selling."

What, then, can you do as a leader? You'd love the stat-based intelligence that big data can provide, but all that's available to you is little data. Fear not. Here are two ways you can gain detailed insights from data that's already at your disposal: 

1. Take a fine-tooth comb to incoming phone calls. Meer describes a regional health insurance company that mined its own call center for rich data regarding customer pain points. "The company took full transcripts of the calls--not just the summaries entered by service representatives--and applied available text-mining algorithms," he writes.

Using data from the transcripts, the company improved "the format and language of its written communications." It also recognized that the calls were an opportunity to introduce customers to neighborhood store locations. In other words, by studying the phone calls, the company was able to improve not only its phone-based communications, but also its in-store interactions. 

2. Apply basic pattern recognition to your customers' use of social media. Vince Golla, director of digital media and syndication for health-care provider Kaiser Permanente, brilliantly used Twitter to gather data about customer frustrations a few years ago.

As Golla explains in the MIT Sloan Management Review, a Kaiser executive once told him that he did not think Kaiser was "doing the best job in the world at [providing] parking for our members. He had this idea that we, as an organization, were not spending enough attention on how we construct, organize, and orient parking spaces around our facilities so that it is easy and convenient for our members."

The executive wondered whether social media could validate his theory. So Golla and his team measured Twitter for the next 30 days. They searched for tweets with any references to Kaiser and parking. As it turned out, the executive was correct. "The conversations about parking with our organization at that moment were twice as negative as general conversation about our brand," says Golla. 

The insights were quite specific. For instance, the valet parking at some facilities generally received positive feedback, but in some of these cases there were negative comments about the cost of providing the service.

The point is, the Kaiser team used social media to quantify the impact of online conversations about their brand, specific to parking.

Mind you, using Twitter for this purpose wasn't entirely easy. Golla's team need to separate the mentions of their Kaiser (the health-care company) from all the others (the beer, the roll, and even the Kaiser Chiefs rock band). 

Once that was done, Golla sorted the data on a bell curve. "Generally, what we see is that 60, 70, 75 percent of the conversation is pretty much right in the middle, neutral. Tweets like, 'I am at this location' or 'I'm going to Kaiser to get my flu shot,'" he says. "In analyzing 30 days of parking-related tweets, what we saw on that [specific] bell curve was that the negative [regarding parking] was at a level of about twice the negative as the general bell curve.”

As you can see, both Golla and insurance company in Meer's article gained rich knowledge from data sources that were already at their disposal--a call center and a Twitter account.

There's no reason you can't do the same. Remember: Your little data is still data. Study it the right way, and you'll glean insights from it.