09 Kellogg Insight IN RECENT YEARS, DATA SCIENCE has become an essential business tool. With access to incredible amounts of data—thanks to advanced comput - ing and the “Internet of things”—companies are now able to measure every aspect of their operations in granular detail. But many business leaders, overwhelmed by this constant blizzard of metrics, are hesitant to get involved in what they see as a technical process. For Florian Zettelmeyer, a profes - sor of marketing and faculty direc - tor of the program on advanced analytics and AI at the Kellogg School, managers should not view analytics as something that falls beyond their purview. “The most important skills in analytics are not technical skills,” he says. “They’re thinking skills.” Managing well with analytics and its close cousin AI does not require a math genius or master of computer science; instead, it requires what Zettelmeyer calls “a working knowledge” of data science. This means being able to separate good data from bad and knowing where precisely analytics and AI can add value. A working knowledge of data science can help leaders turn data into genuine insight. It can also save them from making decisions based on faulty assumptions. “When analytics goes bad, the number one reason is because data that did not result from an experiment are presented as if they did,” Zettelmeyer says. “If you don’t understand experiments,” he says, “you don’t understand analytics.” Based on insights from Florian Zettelmeyer Florian Zettelmeyer explains why analytics require managerial judgment.