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The top marketing executive at a sizable US retailer recently found herself perplexed by the sales reports she was getting. A major competitor was steadily gaining market share across a range of profitable segments. Despite a counterpunch that combined online promotions with merchandizing improvements, her company kept losing ground.

When the executive convened a group of senior leaders to dig into the competitor’s practices, they found that the challenge ran deeper than they had imagined. The competitor had made massive investments in its ability to collect, integrate, and analyze data from each store and every sales unit and had used this ability to run myriad real-world experiments. At the same time, it had linked this information to suppliers’ databases, making it possible to adjust prices in real time, to reorder hot-selling items automatically, and to shift items from store to store easily. By constantly testing, bundling, synthesizing, and making information instantly available across the organization—from the store floor to the CFO’s office—the rival company had become a different, far nimbler type of business.

What this executive team had witnessed first hand was the game-changing effects of big data. Of course, data characterized the information age from the start. It underpins processes that manage employees; it helps to track purchases and sales; and it offers clues about how customers will behave.

But over the last few years, the volume of data has exploded. In 15 of the US economy’s 17 sectors, companies with more than 1,000 employees store, on average, over 235 terabytes of data—more data than is contained in the US Library of Congress. Reams of data still flow from financial transactions and customer interactions but also cascade in at unparalleled rates from new devices and multiple points along the value chain. Just think about what could be happening at your own company right now: sensors embedded in process machinery may be collecting operations data, while marketers scan social media or use location data from smartphones to understand teens’ buying quirks. Data exchanges may be networking your supply chain partners, and employees could be swapping best practices on corporate wikis.

All of this new information is laden with implications for leaders and their enterprises.¹ Emerging academic research suggests that companies that use data and business analytics to guide decision making are more productive and experience higher returns on equity than competitors that don’t.² That’s consistent with research we’ve conducted showing that “networked organizations” can gain an edge by opening information conduits internally and by engaging customers and suppliers strategically through Web-based exchanges of information.³

Over time, we believe big data may well become a new type of corporate asset that will cut across business units and function much as a powerful brand does, representing a key basis for competition. If that’s right, companies need to start thinking in earnest about whether they are organized to exploit big data’s potential and to manage the threats it can pose. Success will demand not only new skills but also new perspectives on how the era of big data could evolve—the widening circle of management practices it may affect and the foundation it represents for new, potentially disruptive business models.

Five Big Questions About Big Data

In the remainder of this article, we outline important ways big data could change competition: by transforming processes, altering corporate ecosystems, and facilitating innovation. We’ve organized the discussion around five questions we think all senior executives should be asking themselves today.

At the outset, we’ll acknowledge that these are still early days for big data, which is evolving as a business concept in tandem with the underlying technologies. Nonetheless, we can identify big data’s key elements. First, companies can now collect data across business units and, increasingly, even from partners and customers (some of this is truly big, some more granular and complex). Second, a flexible infrastructure can integrate information and scale up effectively to meet the surge. Finally, experiments, algorithms, and analytics can make sense of all this information. We also can identify organizations that are making data a core element of strategy. In the discussion that follows and elsewhere in this issue, we have assembled case studies of early movers in the big data realm (see “Seizing the potential of ‘big data’” and the accompanying sidebar, “AstraZeneca’s ‘big data’ partnership,” on mckinseyquarterly.com.)

In addition, we’d suggest that executives look to history for clues about what’s coming next. Earlier waves of technology adoption, for example, show that productivity surges not only because companies adopt new technologies but also, more critically, because they can adapt their management practices and change their organizations to maximize the potential. We examined the possible impact of big data across a number of industries and found that while it will be important in every sector and function, some industries will realize benefits sooner because they are more ready to capitalize on data or have strong market incentives to do so (see sidebar, “Parsing the benefits: Not all industries are created equal”).