When It Comes To Developing A Competitive Strategy, Intuition Alone Won't Cut It
Data analysis is a not-so-secret weapon for successful companies, author and consultant Tom Davenport tells InformationWeek Spring Conference attendees.
Most companies are performing data analysis somewhere, in some limited way. But author and consultant Tom Davenport, speaking Tuesday at the InformationWeek 2006 Spring Conference in Amelia Island, Fla., said market-leading companies are going beyond using analytics in a piecemeal fashion and making it a core element of their strategic planning process.
Data analysis has long been used for specific tasks by highly trained analysts, such as actuaries in insurance and six sigma quality analysts in manufacturing, noted Davenport, who holds the president's chair in Information Technology and Management at Babson College. "It existed, but it was not central to the business," and it remains largely invisible to top decision makers, he said.
But forward-thinking companies--maybe 10% of all businesses--have taken an aggressive approach to building their competitive strategy around analytics, Davenport estimated. That includes finding the right customers and charging them the right price, minimizing inventory while maximizing product availability in the supply chain, and accurately allocating costs and understanding what's driving financial performance.
The best-seller Blink argues that relying on intuition can be effective for decision making, but Davenport claims intuition is just "built-in analytics"--relying on pure intuition would be dangerous. Instead, he pointed to several successful companies that have relied on analytics for years, including Marriott and its revenue management analysis efforts and the use of supply chain analytics by Wal-Mart and Proctor & Gamble. Other companies, such as casino operator Harrah's, have turned themselves around through the effective use of customer analytics.
A recent study Davenport conducted on 32 companies found that about one-third were truly competing on analytics, while a half dozen or so each fell into the categories of clear intent, almost there; has the vision, but a long way to go; and possesses some local, nonstrategic analytical activity. A couple were still wrestling with the basics, he said.
Davenport outlined the five attributes that characterize data analysis efforts at companies that are successfully competing on analytics: a commitment to investing in analytics at the CEO level; widespread use of modeling and prediction; identification of a company's distinctive capabilities or processes (such as supply chain management at Wal-Mart) and the use of analytics to support it; management of analytics at the enterprise level; and large-scale ambitions for using analytical results.
Davenport suggested that companies pick a major focus and a secondary focus for their analytical efforts, pointing out Harrah's use of analytics for customer loyalty analysis and service performance, and UPS's use of operational analytics and customer data analysis. A competitive analytics program should have two primary user groups, such as product category managers and suppliers at Wal-Mart, logistics managers and hospitals at Owens & Minor, and actuaries and customers at Progressive Insurance.
Managing analytics at the enterprise level also requires that line-of-business managers give up their "fiefdoms of data," Davenport said, in favor of a more centralized data management model. And some level of centralized data analysis expertise, such as provided by a business intelligence competency center, is needed.
There's a wide range of technology available for collecting and analyzing transactional data. "It just requires money," Davenport said. The most difficult part of implementing a data analysis strategy includes such intangibles as the need for high-level analytical skills among employees and managers, and instilling a culture of testing and learning. "This stuff takes a while, so you'd better start now," he said.
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