The key is to balance offense and defense.
Although the ability to manage torrents of data has become crucial to companies’ success, most organizations remain badly behind the curve. More than 70% of employees have access to data they should not. Data breaches are common, rogue data sets propagate in silos, and companies’ data technology often isn’t up to the demands put on it.
In this article, the authors describe a framework for building a robust data strategy that can be applied across industries and levels of data maturity. The framework will help managers clarify the primary purpose of their data, whether “defensive” or “offensive.” Data defense is about minimizing downside risk: ensuring compliance with regulations, using analytics to detect and limit fraud, and building systems to prevent theft. Data offense focuses on supporting business objectives such as increasing revenue, profitability, and customer satisfaction. Using this approach, managers can design their data-management activities to support their company’s overall strategy.
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