Remember the scene from the end of Indiana Jones, where the crate containing the lost ark is rolled through a maze of shelves piled high with equally anonymous crates in an enormous government warehouse, presumably never to be seen again? The vast quantities of data being collected through systems and sensors might not have the mass of that dusty artifact, but for many organizations the effect is much the same. It was an exciting ride deploying the technology to gather and store all of that data, but once the lights dim and the screen fades to credits, the treasure is forgotten.

From customer data to social data to performance data, there's no limit to what companies can collect, track and measure. And we're just at the beginning. Yet many organizations have succumbed to analysis paralysis. They know there's more to be gleaned from the data, but they don't know which questions to ask of it, or even where to begin. The data is shelved, the data warehouses unexamined.

Data and technology alone have limited reach. It's the skill to derive meaningful metrics from the data that will make or break the opportunity for each company. CIOs must begin developing that expertise.

The first step is to expand inward. So far, social analytics -- the integration of social software and big data analytics to create insight from unstructured information -- has been the purview of the marketing and sales departments, where the focus has been on monitoring sites such as Twitter and Facebook to gauge customer sentiment and engagement. But social analytics can do more. Broadly applied across all functions, social analytics can focus attention on a company's most pressing internal performance issues.

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Enterprise social software and sophisticated sensors that track flows of information are letting organizations capture more granular data on internal communication patterns, as well as those that include customers and suppliers. Companies can analyze these flows to quantify their impact on metrics that truly matter to the business.

For example, most business leaders realize that financial metrics, though widely reported, tell us how we did in the past, not how to move forward. Operating metrics, such as customer churn rate or time to market, can be leading indicators of financial performance, but by the time companies accurately measure them it's often too late to change the outcome. In contrast, creating flow metrics based on internal and external interaction patterns can help managers not only anticipate operating performance -- and in turn financial performance -- but also help them take corrective action.

The notion that certain patterns of interaction contribute to higher operating performance while other patterns tend to diminish it is not new. Witness the ongoing interest in workspace configurations and team structures. However, social analytics lets managers, for the first time, really test the validity of these conceptions and act on their insights.

Imagine a development team gearing up to launch a product. Management could monitor communication flows -- on the enterprise social platform, if the company has adopted one, but also from scraping anonymous social data from internal networks, email, phone and Web interactions -- across affiliated teams (product development, marketing, sales, manufacturing) to track the progress and coordination across teams. If prior analysis had revealed that rich interaction flows contribute to compressed product lead times, management could get early insight into the likely operating performance of the team and, if necessary, take action to influence different communication flows. These new leading performance indicators could move management practices beyond "break/fix" or "sense/respond" and help executives anticipate performance problems and opportunities.

If Not The CIO, Who?

IT leaders have an untapped asset. As the custodian of the company's data, it's the CIO's job to tap into it.

Start with a one-time deep dive into the company's social data. See that data warehouse? Dive in. What are you looking for? Patterns of interaction. Make observations about how these patterns influence performance and engage with other business leaders about these insights and about how the patterns identified in social data could be used to create truly predictive indicators.

To fully capture the opportunity of social data requires more than building out the technological tools to capture and analyze vast repositories of data. The real opportunity comes after. Collectors of data must learn which questions to ask of it and which hypotheses to test.

The window of opportunity won't remain open for long. Participating in and organizing big data platforms could soon become a business imperative, and the CIO is in the best position to ready the team. Data will ultimately migrate to where it can create the most value. Those who can't harness the value in their data will find themselves at a disadvantage to those who can.

Has your organization tried to tap into social data for non-marketing purposes? How might social interactions from within or outside the enterprise inform your operations? Which metrics might be developed to anticipate operating performance on an ongoing basis? Please weigh in with a comment below.

Eric Openshaw is the vice chairman and U.S. technology, media and telecommunications leader at Deloitte. John Hagel is director, Deloitte Consulting LLP, and co-chairman of the Deloitte Center for the Edge.

In-memory analytics offers subsecond response times and hundreds of thousands of transactions per second. Now falling costs put it in reach of more enterprises. Also in the Analytics Speed Demon special issue of InformationWeek: Louisiana State University hopes to align business and IT more closely through a master's program focused on analytics. (Free registration required.)