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Competing With Analytics by Tom Davenport Most executives would grant that business intelligence and related activities have a role to play in their businesses. But what's the role? For all too many organizations, the role has been as a supporting actor, or a backstage technician. An insurance company, for example, may have some analytical capabilities in the actuarial department, where pricing for policies is determined. A manufacturing company may use such tools for quality management. Marketing may have some capabilities for lifetime value analysis for customers. However valuable these activities are, they are generally invisible to senior executives, customers, and shareholders-and they aren't driving the company's competitive strategy. They are important to individual functions, but insignificant to competition overall. BI doesn't have to be a big player. In some companies, it is already playing a starring role, and it can do so in many more. In a recent study, I sought companies that have elevated data management, statistical analysis, experimentation, and fact-based decisions to a high art. I found more than a dozen across a variety of industries, including Capital One in consumer finance, Wal-Mart and Amazon in retail, Progressive in insurance, Marriott in hotels, and Harrah's in gaming. These organizations have analytical activities that are hardly invisible; they are touted to every stakeholder and interested party by CEOs. Instead of being hid behind the curtain, analytics in these companies are found in the annual report and in the press clippings. These organizations have taken a resource that is ostensibly available to all, and refined it to such a degree that their strategies are built around it. I call them analytical competitors. The idea of competing on analytics is not entirely new. A few organizations-mostly in financial services and particularly in financial investment and trading businesses-have competed on this basis for decades. The trading of stocks, bonds, currencies, and commodities has long been driven by analytics. What is new is the spreading of analytical competition to a variety of other industries. Even the most traditionally intuitive industries - professional sports teams, for example - are moving in this direction. Today such companies represent a small minority of organizations, but they are significant beyond their numbers. In fact, they represent the future of business intelligence. By studying what organizations do when they build their strategies around BI, we can learn how to take the concept to the next level in less ambitious organizations. I'm not sure that all organizations should strive to become analytical competitors, but we can all learn something from them. What Makes an Analytical Competitor? Knowledgeable and Committed Leadership The adoption of a broad analytical approach to business requires changes in culture, process, behavior, and skills for multiple employees. Such changes don't happen by accident. They must be led by senior executives with a passion for analytics and fact-based decision making. Ideally, the primary advocate should be the CEO, and indeed I found several chief executives who were driving the shift to analytics at their firms. These included Gary Loveman, CEO of Harrah's; Jeff Bezos, the founder and CEO of Amazon, Rich Fairbank, the founder and CEO of Capital One; and Barry Beracha, formerly CEO of Sara Lee Bakery Group. Each of these executives has stated both internally and publicly that their companies are engaged in some form of analytical competition. Use of Sophisticated Analytics Across the Organization The most aggressive analytical competitors go well beyond basic statistics in one function. They are using predictive modeling, for example, to identify not only the most profitable customers, but those with the most profit potential, or those most likely to defect. They are combining and pooling internal and external data to gain a more comprehensive picture and understanding of their customers than was ever thought possible. They are optimizing their supply chains to determine the impact of an unexpected constraint, simulating alternative supply chains, and routing shipments around problems. They are establishing prices in real time so as to provide the highest yield possible from a customer transaction. No matter what the business function, it's possible to improve performance through the use of sophisticated analytical techniques. Analytical competitors employ sophisticated analytics not just in one business function or process, but across multiple aspects of the business. UPS, for example, has traditionally focused on analytics for operations and logistics. More recently, it has developed a strong analytical focus on customers, assessing the likelihood of customer attrition, or identifying sources of problems for customers. However, there is a balance to be maintained in terms of broadening the focus on analytics, and employing them to address a specific business domain. Executives at several firms warned against losing a clear business purpose for analytics. Harrah's, for example, has targeted much of its analysis on increasing customer loyalty and improving customer service. Analytical competitors can broaden their focus beyond a narrow function, but they are careful not to become too diffuse in their analytical targeting so that they continue to support their primary strategies. An Enterprise-Level Management Approach BI applications often have been managed at the departmental level, with analytically oriented business functions selecting their own tools, managing their own data warehouses, and training their own people. Sometimes they are even managed at the individual spreadsheet level. However, if analytics are to be a company's basis for competition, and if they are to be broadly adopted across the firm, it makes more sense to manage them at an enterprise level. This ensures that there is a critical mass of skills, that critical data and other resources are protected, and that data from multiple business functions can be correlated. The enterprise approach may include both organizational and technical capabilities for business intelligence. At the organizational level, for example, Procter & Gamble recently consolidated its analytical organizations for operations and supply chain, marketing, and other functions. This will allow analytical expertise to be deployed to address P&G's most critical business issues. Firms that adopt these attributes will take their rightful positions at the center stage of business. Analytics and BI will then realize their long-term potential for organizational transformation. Tom Davenport is professor and director of research, Babson Executive Education, Babson College. Copyright Tom Davenport. All Rights Reserved. END

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