With so much information at our fingertips, it’s tempting to rely on data to make important decisions. But don’t overlook other variables.
Consider the case of a big U.S. bank chief executive. Recently, he was deciding whether to pull out of Italy due to economic instability spreading across Western Europe.
Crunching the numbers, the CEO’s staff highlighted many perilous scenarios if the bank kept doing business in Italy. But the executive looked beyond the worrisome data. His bank has a long history of serving Italians, and he feared that they would view his firm unfavorably if it abandoned them in difficult times.
He concluded that it was better to remain in Italy despite short-term costs and uncertainties. The goodwill and trust he’d built with Italians, he felt, would advance his business interests more than pulling out.
The CEO’s thought process shows the limits of data analysis. Even with the capacity of computers to synthesize huge amounts of information, data cannot dish out easy answers to every dilemma.
Yet there’s a tendency to look to data to solve problems. Algorithms can seemingly make sense of complex situations. A leader can fall into the “Numbers don’t lie" trap.
Nassim Taleb, author of The Black Swan, notes the more information we gather, the more statistically significant correlations we find. But most of these cause-effect relationships are misleading.
Balance data analysis with other factors and assess intangibles such intuition, trust and long-term relationships.
— Adapted from “What Data Can’t Do,” David Brooks, The New York Times.
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