Nitrogen is what gives Guinness its surge and its dome. Fifty-four years later, a food scientist in Portland put the same gas into cold coffee, and nitro cold brew became a category. Nobody had hidden the pattern. It sat in the beer trade press for half a century, in an industry no one in coffee had any reason to read. Coffee people read coffee reports. Beer people read beer reports.

We are taught to look for the future close to home: among our competitors, our customers, and the prevailing ideas within our own field. By the time a shift becomes visible inside a category, much of its strategic value has already been claimed. Your next advantage is probably taking shape somewhere you are not looking.

Latitudinal thinking is the practice of looking across fields to recognize patterns others miss. Rather than examining the world you already know more intently, you learn to identify the same need, behavior, or force taking shape elsewhere, and to consider what it could make possible in your own work.

Strategist Lara O’Shea has built her career on these connections. Drawing on geography, anthropology, photojournalism, and more than two decades of work across industries, she follows premiumization from spirits to skincare, coffee, and pet food, and now to fresh produce. She shows how two exhausted doctors at Great Ormond Street watched a Formula 1 pit stop on television and rebuilt the most dangerous minutes in pediatric heart surgery around what they saw, cutting technical errors per handover by roughly 40 percent. She traces how a self-taught carpenter’s son solved the longitude problem that Europe’s astronomers had claimed for two hundred years.

Recognizing a connection is only the beginning. At the center of the book is the Latitude Scan, a five-step method for finding promising patterns, uncovering the forces beneath them, translating them across boundaries, and testing whether they truly fit: Chart, Scan, Triangulate, Traverse, and Ground Truth. A chapter on failure names the six ways a borrowed pattern goes wrong, so a reader can tell a meaningful parallel from a superficial resemblance before betting on it.

The book arrives at the moment depth stopped paying. Your competitor’s AI has read the same reports as yours, and knowing your category better than anyone else is no longer an advantage you can hold. What remains is human work: deciding where to look, recognizing a structure when it turns up in an unfamiliar container, and judging whether it will survive the crossing.