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| | Brought to you by Liz Hilton Segel, chief client officer and managing partner, global industry practices, & Homayoun Hatami, managing partner, global client capabilities
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| | | In the early days of the dot-com boom, many online businesses were unaware of the practical aspects of order fulfillment—and sometimes failed because of inefficient warehousing or inventory management practices. But even today’s more sophisticated organizations can endanger major initiatives by not paying attention to practical details. As more companies begin to implement new technologies, it’s important for leaders to examine whether their organizations have the tools, capabilities, and talent in place to ensure that operations run as planned. Here are some factors to consider.
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| | | Keeping the big picture in mind is essential when it comes to large-scale undertakings. But there are times when overlooking seemingly minor details can derail an entire project. To see how things really work in practice, prepare to invest both money and common sense, suggests McKinsey senior partner Rodney Zemmel. “Work with frontline people right from the beginning, before a line of code is written,” he says. It’s important to figure out if and how a technology will be used before adopting it. McKinsey senior partner Kate Smaje describes the case of a company that had developed an app for its warehouse operators to use on a tablet. “It was a beautiful front end, and they were so proud of it,” she says. “A member of my team very quietly, slightly timidly said, ‘Don’t the warehouse people wear gloves?’ And there was this sort of audible, ‘Oh, what on earth are we going to do now?’ moment.” | | |
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| “Whenever you develop a technology, there will be a secondary effect somewhere in the system that will prevent you from fully capturing the value,” observes McKinsey senior partner Eric Lamarre in an episode of our Inside the Strategy Room podcast. Lamarre cautions against deploying technology without identifying the business problem that needs to be solved. For example, an airline company found that a technology to calculate extra cargo space did not work as expected because of a problem on the ground: operators at the airport had not been trained to maximize pallet caseloads. Similarly, the technology creating the most buzz today, generative AI (gen AI), may not always be the best solution to a problem, says Lamarre. “It’s good to come back to the fundamentals—what are the pain points in the company?—then search broadly for the set of technologies that will address them,” he suggests. “Sometimes, that will be gen AI, but that doesn’t mean gen AI is the place to start.” | | |
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| | | | | | | — Edited by Rama Ramaswami, senior editor, New York
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