Technological innovation in cities is primarily a matter not of adopting new technology but of deploying technology in conjunction with nontechnical change and expertise. This requires data scientists to reach out beyond the realm of databases and analytics to access as much contextual knowledge as possible.

“You come in with your fancy machine learning algorithm in your pocket,” says Amen Ra Mashariki, former chief analytics officer at the Mayor’s Office of Data Analytics in New York City, “but what’s always going to be your ace in the hole is the knowledge of the people who actually do the real work.” Breaking down departmental silos, creating new practices to manage data repositories, and training staff in new skills—not finding the optimal machine learning algorithm—is the real pressing task at hand in cities such as New York, Seattle, and Boston.

Seattle, where the Human Services Department (HSD) improved local homeless services by restructuring contracts with local service providers and aligning other agencies behind a common purpose, illustrates the benefits of recognizing that innovation can mean more than just “use new technology.”

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Excerpted from The Smart Enough City: Putting Technology in Its Place to Reclaim Our Urban Future, published by the MIT Press.