How to Use Your Endless Stream of Big Data as an Asset Every company has data but this information isn't valuable until it's positioned as a tool for insight and progress.

With billions of data points being generated every day, some companies don't know what to do with big data -- and that's understandable. It's difficult to manage all of it, but it's impossible to ignore. This obvious opportunity leaves a large percentage of executives concerned that their information isn't correctly represented and entrepreneurs struggling to find a way forward.

But big data is worth the struggle. It can help business owners understand how their business functions and how it serves their customers. It can help companies reveal new opportunities, dig up unknown problems and even make more money.

Related: Decoding Big Data for Business Growth (Infographic)

Big data is an asset to any company that takes the time to position it the right way -- but it's up to each company to take theinitiative to do so.

First, consider big data within the context of the customer. What kind of interaction does the customer have with the company and how can those individual touch points be used to paint a complete picture? Then, the business needs to figure out creative ways to repurpose that information.

Data assets might look different in each industry, but the real value of the data lies not in its type but in whether it can help you increase your value or retain customers. According to Jeff Tanner, professor of marketing at Baylor University, the information you get from your customers empowers you to deliver better value over time and create more opportunities for your business.

While it may be possible to assign a cash value to big data, those numbers aren't likely to make it onto the balance sheet. The data's real value is revealed when it's positioned in the context of the following three questions:

How will it make the business more predictable?

The most impactful data will help a company predict and anticipate what will happen in a few months. Focusing on early-indicator data will stabilize and reduce the number of fires a company needs to fight each day.

For example, customer-service data and subjective help desk feedback are good for training. However, strategically positioning this data might also reveal early indicators of customer dissatisfaction, allowing you to intervene and prevent it. This is a pattern my company uses to uncover data our team otherwise would've caught too late to save the relationship.

Related: How Analytics and Data Can Undermine Leaders

How will it help replicate success for the future?

New startups can easily hit a cluster of success and then experience a period of difficult sales. If this happens to you, take the opportunity to analyze the data and re-engineer your product or service accordingly. The proof point for your data is that you can use it to develop a realistic financial plan that funnels into a higher-level organizational plan.

In retail, it's common practice to track your customers' behavior online and offline to capture recency, frequency and monetary value. However, RFM isn't a true benefit until you position it in a way that allows you to replicate the success of these customers and tweak your business plan accordingly.

How will it enhance customer engagement?

Data may show important trends but what brings customers back to a product or service is their individual experience. Data becomes more valuable when it's used to further customize and personalize the customer's experience.

Yahoo is one such company doing new things with data to personalize the customer experience. If a reader clicks on a soccer story, that reader will be served more articles on soccer as they navigate the site. This is a sophisticated way companies use data to engage their customers.

Every company has data. But this data isn't valuable -- or an advantage to the company -- until it's positioned as a tool for insight and progress. Entrepreneurs and executives looking to put their data to work need to organize the information in a way that unveils insights and opportunities for the future.

Related: Look for These 7 Characteristics Before Hiring a Data Scientist