

Competing on AnalyticsBy Thomas H. Davenport Author, professor, lecturer, consultant Organizations have invested millions of dollars in systems that capture data from every conceivable source. Enterprise resource planning, customer relationship management, point-of-sale and other systems ensure that no transaction or other significant exchange occurs without leaving a mark. But to compete on that information, your organization must present it in standard formats, integrate it, store it in a data warehouse, and make it easily accessible to anyone and everyone. The popularity of competing on analytics is partly in response to the emergence of integrated packages of these tools. Using them, your organization can become an "analytics competitor" that is able to wring every last drop of value from your data. To identify characteristics shared by analytics competitors, I and two of my colleagues studied 32 organizations that have made a commitment to quantitative, fact-based analysis. We found three key attributes: 1. Widespread use of modeling and optimization. Any company can generate simple statistics about its business. Analytics competitors profile their customers, optimize their supply chains and create complex models of how their operational costs relate to their financial performance. 2. An enterprise approach. In traditional companies, "business intelligence" is generally managed by departments, each of which selects its own tools (often error-prone spreadsheets), controls its own data warehouses and trains its own people. Analytics competitors field centralized groups to ensure that critical data and other resources are well managed and that different parts of the organization can share data easily, with consistent formats, definitions and standards. 3. Senior executive advocates. A companywide embrace of analytics impels changes in culture, processes, behavior and skills for many employees. Like any major transition, it requires leadership from executives at the very top who have a passion for the quantitative approach. A background in statistics isn't necessary, but leaders must understand the theory behind various quantitative methods so that they recognize those methods' limitations — which factors are being weighed and which ones aren't. As Gary Loveman, CEO of Harrah's, frequently puts it, "Do we think this is true? Or do we know?" How Healthcare Organizations Can Use Metrics Healthcare organizations should follow the casino-giant's litmus test for making decisions. One healthcare organization, Cardinal Health System in East Central Indiana was faced with soaring costs, diminished reimbursement and vigorous industry competition. To fast-track improvements, the health system aggregated data from disparate sources and presented it in customized, metric-driven scorecards that were used by its service line managers for strategic planning and in guiding daily decisions. Within a year the organization improved clinical quality, patient volumes, revenues, and patient and employee satisfaction while also narrowing budget variances and lowering operating expenses. By identifying root causes of potential problems and immediately addressing them, managers can exert more control over their service lines. The scorecards also include volume and charge information, which helps managers understand trends over time and keeps everyone in sync with performance improvement goals. More than Simple Number-Crunching Certainly, analytics competitors apply technology. But they also direct their energies toward finding the right focus and hiring the right people to make optimal use of the data. Generally, they pick several functions or initiatives that together serve an overarching strategy. They also hire analytical people who have the ability to express complex ideas in simple terms and the relationship skills to interact well with decision makers. Existing employees, meanwhile, will require extensive training. They need to know what data are available and all the ways the information can be analyzed; and they must learn to recognize such shortcomings as missing data, duplication and quality problems. Thomas H. Davenport is the President's Distinguished Professor of Information Technology and Management at Babson College in Babson Park, Mass., the director of research at Babson Executive Education, and a fellow at Accenture. His latest book is Competing on Analytics: The New Science of Winning (Harvard Business School Press, 2007).
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