- Research Feature
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Our new survey suggests that companies experienced in analytics use are increasingly gaining competitive advantage — but their approaches vary.
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Businesses’ ability to process numbers in “well-behaved rows and columns” goes back 40 years, notes K. Ananth Krishnan, chief technology officer of Tata Consultancy Services, one of the largest companies in India. Figuring out how to mine and process the information in text, video, and audio is the new frontier.
Almost all executives want more and faster information, and almost all companies are racing to provide it. What many of them overlook, though, is that the real aim should be not faster information but faster decision making — and those aren’t the same things.
Many think that the way to capture value through relationship marketing is to focus on the “good” customers and get rid of the “bad” ones. But there is more to best practice relationship management than maximizing revenues on individual customers and minimizing costs to serve. This article provides guidelines for companies that want to improve the value of customer relationships. For most companies, the transition to a relationship-based approach will require a significant shift in practice.
Companies have been trained to think about data all wrong, say Attivio’s Ali Riaz and Sid Probstein. “Analytics don't have to be based on super-precise data,” they say. “The report doesn't have to be perfect. It needs to capture the behavior, not the totality of it."
Managers must think about and manage data differently in order to take advantage of this underutilized resource.
Creating a business-driven IT infrastructure requires that executives thoroughly understand their firm's strategic context. By formulating a series of business and IT maxims -- short simple statements of the business's positions -- managers can identify the IT infrastructure service suited to their company. Organizational, political, cultural, and reward system issues, as well as a lack of IT leadership, may form implementation barriers.
Positioning products in a complex market is one of a company’s hardest decisions. In determining whether to combine or maintain separate product lines, Hewlett-Packard used strategic market modeling (SMM) to design “what if” scenarios and run simulations forecasting market behavior. SMM combines demographics, user needs and competitive-perception data into a database for testing alternative positioning strategies. The author describes SMM’s development and the lessons learned.
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