| McKinsey Classics | June 2021 |
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| Hard-to-find, pricey data scientists are obviously important for data analytics, but they can’t tell a company how it should use their services. Much as the CEO and the top team must determine a company’s strategy, they must also determine how data analytics supports it.
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| In 2016, a team of McKinsey authors offered some rules for top teams struggling with analytics. Here are a few of the most important. Ask clear questions, such as “How can we speed time to market,” not “What patterns do the data show?” Embrace “soft” data. Use a variety of analytics techniques and combine them in a variety of ways. Build a team that includes not only data scientists but also engineers in fields such as distributed computing; cloud and data architects; “translators,” who connect IT and data analytics with business decisions and management; and developers of user interfaces, because an attractive one makes a data-analytics solution more usable than any computation, however sophisticated. Which brings us to the most important rule: analytics is nothing unless your company knows how to implement it.
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| These lessons still hold good. To learn more, read our classic “Making data analytics work for you—instead of the other way around.”
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| — Roger Draper, editor, New York |
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| Did You Miss Our Previous McKinsey Classics? |
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| Four powerful forces are transforming the world: urbanization in developing economies, faster technological change, aging, and a new kind of globalization. Learn about them in our 2015 book excerpt “The four global forces breaking all the trends.”
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