A lot of companies collect data. But it’s the ability to analyze and strategically act on that data that matters, notes Thomas Davenport, the author (along with Jeanne Harris) of the best-seller Competing on Analytics: The Science of Winning. During a recent visit to Emory University’s Goizueta Business School, Davenport told students and faculty that most companies use data in a supporting role—not as the strategic weapon it can be. Davenport’s lecture was sponsored by The Emory Marketing Institute.

At a time when competing companies offer similar products and have access to the same technologies, observes Davenport, analytical customer-facing processes are some of the only areas where businesses can differentiate themselves. “Analytical competitors,” as he calls them, mine their data for every sliver of information it offers and then utilize that information in strategic ways. Firms like Harrah’s Entertainment, Inc., Marriott International, Inc. and Google that use analytical tools in a strategic manner, says Davenport, are raising the bar in their industries when it comes to things like customer service, supply chain management and marketing.

Last year, global management consulting firm Accenture asked nearly 400 companies if analytical capabilities had been a key element of their strategy in 2006. Fifteen percent of the top performing companies answered, “yes.” Only three percent of the low performers said “yes.”

Companies are taking their metrics—marketing metrics, sales metrics and service metrics—and using them, among other things, to segment, cross-sell, forecast, target and study drivers of satisfaction. Rather than looking at what happened, companies are able to predict more precisely what will happen and to better understand how and why it happened.

Part of the reason it’s getting easier to use data in a strategic way is that companies now have—or have access to—the IT and IT talent necessary to mine company data and use the findings strategically in order to affect positive change in their business. According to Davenport, who is also a chaired professor in information technology at Babson College, measuring and qualifying the effectiveness of a company’s marketing efforts has been a challenge for as long as businesses have been marketing their wares. “How do you make sure your marketing expenditures are devoted to things that actually pay out?” says Davenport, noting that data used and analyzed in the right way can help companies do things like optimize customer relationships and prioritize marketing initiatives. “It’s a sea change.”

Analytics does require a technological investment, but without executive leaders who champion, centralize and enact a well-designed analytics initiative enterprise-wide, a company won’t maximize the value of its data. “It seems to be hard to do this without very strong, analytically-focused leaders,” he says, adding that these leaders are able to instill respect for measuring, testing and evaluating quantitative evidence and establish doing so as a way of doing business. Decisions are based on facts, not hunches or incomplete information. Davenport quotes Gary Loveman, CEO, Harrah’s Entertainment, Inc., who is known to ask his employees: “Do we think this is true or do we know?”

Historically there’s been as much “art” in advertising and marketing as there has been “science.” Davenport argues that science is more likely to be correct than “art,” and adds that science enables a company to experiment on a small scale before committing a slew of resources to a huge marketing campaign or program.

In order to attract and retain customers, Harrah’s uses analytical tools not only to identify profitable customers, but to pinpoint its customers most likely to be wooed by competitors. Through well-designed marketing campaigns—created around information the analytical tools delivered—Harrah’s marketing methods can be strategically aimed at keeping those customers.

Loveman studied the company’s data and realized the company didn’t have a well-defined profile of its best customer. Once Harrah’s captured that information, it could figure out what it would take to get that customer to come to Harrah’s. Loveman knew he needed to link that information between casinos so information could be shared. Analytical tools allowed the entertainment company to do so. The result is a beefed-up customer relationship management system anchored by a centralized data warehouse filled with pertinent information about how Harrah’s customers interact with the company. And given this information, Harrah’s marketing efforts are tailored to attract its different constituencies.

For instance, Harrah’s customers who live within driving distance of a casino receive different offers than those who do not. Frequent visitors to the casino in New Orleans are likely to receive different offers than frequent customers in Las Vegas or St. Louis. Harrah’s only targets customers likely to respond to such offers and it has more than 80 different segments for each marketing campaign.

One of the reasons Harrah’s has been so successful, notes Davenport, is because they focused on “one thing early” when it came to analytics. In Harrah’s case that “one thing” was customer loyalty. “In terms of marketing, companies need to think about target areas and about what they’re trying to accomplish,” adds Davenport. According to information available on Harrah’s website, nearly 50 percent of the company’s revenue is driven by marketing and the company’s analytical efforts have helped boost the company’s bottom line.

Marriott has a method for establishing the optimal price for its guest rooms, better known in the hospitality industry as “revenue management.” But Marriott used analytical tools to expand the reach of its “Total Hotel Optimization” program, explains Davenport. For instance, if a frequent guest tends to spend money on food and beverage available in the hotel’s restaurants or via room service, his or her room rate might be lower than a guest who rarely enters the establishment’s restaurants.

The New England Patriots NFL team uses analytics to optimize player selection and, as Davenport describes, “get the best player at the right price.” The Boston Red Sox hired a famous baseball statistician to help build the best possible team at the best possible price. The book Moneyball by Michael Lewis chronicled the Oakland Athletics ability to outperform other MLB teams on half the budget due to its use of analytics. “Baseball has been dramatically changed by new metrics,” notes Davenport.

Analytics are also being utilized in less likely scenarios. At Gallo Wineries, winemakers are experimenting with the chemical composition of wines to see how customers respond. Through analytics, Progressive Auto Insurance discerned that drivers with good credit scores are less likely to get in accidents. They were also more likely to pay and to pay on time.

In studying companies that use analytics successfully, Davenport crafted what he calls “The Ladder of Analytical Marketing Targets”—essentially a best practice guide. First up, build a centralized customer database so that the company can get a comprehensive idea about its customers. The company can then treat “different customers differently” and respond appropriately to a customer’s activity. Companies can keep track of who got what and better manage their marketing campaigns—to the point of personalizing them. Via predictive modeling, companies can answer with much more certainty what customers are likely to do next given what they’ve already done. As a result, companies can make real time, customized offers that make sense to their customers.

Some companies use analytics in their hiring practices. Google discovered through its use of analytics that job candidates who had set a record or led a club or organization turned out to be better employees than those chosen based on GPA. “Those other things actually show initiative,” says Davenport. When NetFlix makes recommendations to its customers, it does so based on analytics. “Do you take their recommendations or your own?” ask Davenport, who adds that surveys reveal NetFlix users rated NetFlix’ recommendations higher than movies they’d chosen on their own.

Graduating from metrics to analytics not only takes strong analytically-minded leadership and a healthy IT investment, but various types of analysts to make it work. “It you want to be analytical, you need analysts,” explains Davenport. Some who are highly sophisticated—the types who can create algorithms—as well as those who can use basic models. But the bulk of the analysts are “analytical amateurs,” says Davenport—folks who know how to use a spreadsheet, or who work with customers on analytically-based recommendations. Making the transition also requires patience.

“I tell companies that this is a long-term journey,” explains Davenport. “Not everything is going to happen overnight.” UPS collected customer data for a while before the logistics company decided to take that data and use it analytically. Once that decision was made, it took several years for the company to get all its analytical ducks in a row, as it were. “It takes time for people to comfortable with it,” says Davenport.

Davenport’s lecture is just one of the many offerings of Emory University’s Emory Marketing Institute (EMI). EMI is a research group that focuses on the advancement of brand-driven business performance. Visit the EMI webpage to learn more and to access free managerial articles.