Big data and analytics have rocketed to the top of the corporate agenda. Executives look with admiration at how Google, Amazon, and others have eclipsed competitors with powerful new business models that derive from an ability to exploit data. They also see that big data is attracting serious investment from technology leaders such as IBM and Hewlett-Packard. Meanwhile, the tide of private-equity and venture-capital investments in big data continues to swell.

The trend is generating plenty of hype, but we believe that senior leaders are right to pay attention. Big data could transform the way companies do business, delivering the kind of performance gains last seen in the 1990s, when organizations redesigned their core processes. As data-driven strategies take hold, they will become an increasingly important point of competitive differentiation. According to research by Andrew McAfee and Erik Brynjolfsson, of MIT, companies that inject big data and analytics into their operations show productivity rates and profitability that are 5% to 6% higher than those of their peers (see “Big Data: The Management Revolution”).

Even so, our experience reveals that most companies are unsure how to proceed. Leaders are understandably leery of making substantial investments in big data and advanced analytics. They’re convinced that their organizations simply aren’t ready. After all, companies may not fully understand the data they already have, or perhaps they’ve lost piles of money on data-warehousing programs that never meshed with business processes, or maybe their current analytics programs are too complicated or don’t yield insights that can be put to use. Or all of the above. No wonder skepticism abounds.

Many CEOs, too, recall their experiences with customer relationship management in the mid-1990s, when new CRM software products often prompted great enthusiasm. Experts descended on boardrooms promising impressive results if new IT systems were built to collect massive amounts of customer data. It didn’t turn out that way. Too many C-suites were blind to the practical implications of new CRM technologies—namely, that to capitalize on them, organizations would have to make complex process changes and build employees’ skills. The promised gains in performance were often slow in coming, because the systems remained stubbornly disconnected from how companies and frontline managers actually made decisions, and new demands for data management added complexity to operations. To be fair, most companies eventually managed to get their CRM programs on track, but not before some had suffered sizable losses and several CRM champions had lost career momentum.

Given this history, we empathize with executives who are cautious about big data. Nevertheless, we believe that the time has come to define a pragmatic approach to big data and advanced analytics—one tightly focused on how to use the data to make better decisions.

In our work with dozens of companies in six data-rich industries, we have found that fully exploiting data and analytics requires three mutually supportive capabilities. (See the exhibit “How to Benefit from Big Data.”) First, companies must be able to identify, combine, and manage multiple sources of data. Second, they need the capability to build advanced analytics models for predicting and optimizing outcomes. Third, and most critical, management must possess the muscle to transform the organization so that the data and models actually yield better decisions. Two important features underpin those activities: a clear strategy for how to use data and analytics to compete, and deployment of the right technology architecture and capabilities.

Equally important, the desired business impact must drive an integrated approach to data sourcing, model building, and organizational transformation. That’s how you avoid the common trap of starting with the data and simply asking what it can do for you. Leaders should invest sufficient time and energy in aligning managers across the organization in support of the mission.