Buy-In from the Boss

The key factor in successfully competing on analytics in our study was a strong pull from senior executives. Analytical resources such as business intelligence software won't change anything within an organization unless executives insist that analytics drive business strategy. Decision making based on data, facts and complex statistics doesn't just evolve. It requires substantial changes in culture and behaviour that must be driven from the top.

In the companies we found that were competing on analytics, the CEO was not only a supporter, he was a cheerleader. Jeff Bezos at Amazon, for example, states publicly that he and his executives frequently pursue analysis and fact-based decisions. Amazon does detailed empirical analysis on such questions as whether it should advertise on TV (no), or whether it can sell commodities at closeout prices at the bottom of its Web page (yes). Gary Loveman at Harrah's has written articles about the virtues of evidence over intuition. As Malcolm Gladwell points out in Blink, intuition can be valuable - but not when deciding the ideal price to offer on a hotel room to a frequent gambler on New Year's Eve in Las Vegas.

In addition to setting the analytical tone, the CEO also establishes the focus. Several executives told us that it's important to maintain a strategic focus for analytical activity. Capital One flirted briefly with the idea of selling flowers and mobile phones, but using analytics, the bank decided to restrict itself to consumer financial services such as car loans and CDs. Perhaps not coincidentally, it has become the sixth-largest credit card provider in terms of loans, and has grown earnings per share by over 20 percent in each of its 10 years as a public company.

How to Build Demand and Supply

If you believe in the power of analytics but your CEO and executive team just don't get it, there are some ways you can begin to build demand. One is to simply familiarize the organization with the data available. Shaygan Kheradpir, CIO of Verizon, is attempting to increase executive demand in this fashion. He created a scorecard in which hundreds of performance metrics of various types are broadcast to PCs around the company, each occupying the screen for 15 seconds. The idea is to get everyone - not just senior executives - focused on information and what it means to Verizon's performance, and to encourage employees at all levels to address any issues that appear in the data.

Another IT organization in a pharmaceutical company we studied doesn't have much demand yet, but is trying to stimulate it by following up after any hint of interest from executives. For example, a marketing manager discovered software tools that showed how sales data could be displayed graphically in terms of geography on an interactive map. The company's IT executives seized upon his interest and offered him some related geographically oriented analytical capabilities so that he could identify underserved territories and plan the geographical spread of new hires. These IT managers wisely refuse to wait until more analytically oriented senior executives happen to arrive at the company.

The Right Talent Makes a Difference

Supplying the right kind of hardware environment and analytical software is typically easier to address than creating demand, but just as important. While good data from transactional systems is increasingly available and analytical technology has become easier to use, companies that compete on analytics still require people with substantial quantitative skills - either in-house or contracted from outside. The statistical expert, in order to be useful, will also need to be familiar with the business problems in the function and industry; the quantitative skills of a good analyst are rarely equally applicable across diverse businesses. One pharmaceutical company, for example, attempted to use several bioinformatics experts to pursue analysis of commercial problems in marketing and operations, and found that they were neither motivated nor expert at the applications. Similarly, while statistical analysts from India and China are increasingly available from offshore outsourcing vendors, it's unlikely that they will know your business well.

Indeed, several companies we interviewed stressed the importance of a close and trusting relationship between quantitative analysts and decision makers. The need is for statistical experts who also understand the business in general, and the particular business need of a specific decision maker. As one manager at Wachovia Bank put it: "We are trying to build our people as part of the business team; we want them sitting at the business table, participating in a discussion of what the key issues are, determining what information needs the business people have and recommending actions to the business partners."

A consumer products company we interviewed hires what it calls "PhDs with personality" for its analytical group - individuals with not only heavy quantitative skills but also the ability to speak the language of the business and market their work to internal customers. This company believed that the relational aspect of the job made it difficult to outsource or take offshore. To find these people and develop these types of relationships would surely be much more difficult in an outsourcing situation, and virtually impossible with analysts half a world away from the decisionmakers.

How Do You Know When You're There?

There are several indications that a company is competing on analytics:

THE CEO HAS AN ANALYTICAL BACKGROUND. Harrah's' Loveman was a business school professor and has an MIT PhD. Amazon's Bezos was an A-plus student in electrical engineering and computer science at Princeton. When the CEO or vice chair of a company is a rocket scientist, it's a good bet that there will be other scientists on the payroll.

NOBODY'S ASKING ABOUT THE ROI FOR EACH LITTLE INITIATIVE. What's at stake in analytical competition is not an application, but a corporate strategy. If the analytical activities are succeeding, they will be manifested not in ROI calculations, but in revenue and profits.

THE COMPANY IS VERY SUCCESSFUL. Certainly there are industries (for example, US domestic airlines) where a lot of analytics don't seem to be the critical success factor. It isn't with Southwest. But the great majority of highly analytical companies that we studied are leaders in their industries and making lots of money.

As more analytically trained managers enter the workforce, it's likely that analytical competition will become more common and intense. However, this capability can't be developed overnight. Most of the companies we interviewed took at least five years to develop their analytical capabilities sufficiently to compete on that basis, and a couple of very successful companies (including Procter & Gamble and Mars) had been pursuing analytics for several decades. Assembling the right data, finding and using the right tools, and developing the right relationships between analysts and decision makers all take time. Therefore, it makes sense to start pulling them together now. History seems to be on the side of the numbers.

Tom Davenport is professor of IT and management at Babson College and an Accenture Fellow