ANALYZING THE FINER POINTS of a profound question on the nature of freedom is one thing; analyzing a client’s financial future and advising them on what to do about it is another. This is the specialty of McKinsey & Company, the dominant name in the field of management consulting. Since its product is, above all, the intellect of its employees, the firm (better known in consulting circles as the Firm) prides itself on hiring not just top business school graduates, but anyone it considers very bright and teachable, such as Rhodes Scholars.
To some, McKinsey is the pinnacle of smart and useful analysis in the business world. To others, it is the primary symbol of a trend that sees more and more graduates from prestigious programs go into the private sector when they could be committing themselves to public service, research, or some other worthy pursuit. When I decided to attend an informational session about McKinsey for graduate students, I felt ambivalent but more sympathetic to the latter camp. My education to date, and my hopes of making an impact in the world, pointed to public service, inquiry, and the arts, not business. But I also knew that I would have to understand business if I wanted to make myself useful in practice. Despite all my education, I felt ignorant about how the private sector really worked. I would leave Oxford with a degree in economics, but knew little firsthand about the functions—from logistics to finance—that made the private sector operate. And the firm known best for its expertise on how the private sector works was actually willing to give me an interview for a post-MBA job, taking a chance on the idea that if I was prepared to learn, they could teach me all the things about business I didn’t know.
Also, crucially, they had a Chicago office. It was not the most glamorous office in the Firm—that title probably belonged in London, Dubai, New York, or Silicon Valley—but it was known for the diversity of industries it served, which would make it a good training ground. More importantly, it was a way for me to come back to the Midwest, a region whose role in shaping me had become more obvious the farther away I’d moved. When I finally saw the Chicago office for myself on the day of my final-round interview, I noticed not just the modern wood paneling, large abstract paintings, and big windows that signified an elegant corporate office space. I also saw, out the windows on the high floor of the Chase Tower where my interviewer received me, a view of Lake Michigan’s shoreline that you could trace, past Hyde Park and the South Side and the Skyway Bridge, all the way to the smokestacks marking the state line and the beginning of northern Indiana.
LET ME ASK YOU, for a moment, to imagine a list of the most interesting subjects in the world, ranked from one to infinity. The list is different for each of us. But some topics are fairly high on the list for almost everyone: topics such as television, religion, warfare, food, sports, space travel, the presidency, and sex. Now ask yourself where, on that list, you would put the subject on which I became an expert during the winter of 2010: North American grocery pricing.
Not in your top thousand? Me neither, at the time I was offered to join a team working on a client study on the subject. (For an associate, life at McKinsey mostly consists of months-long stints on a “team” of three or four people working on an engagement or “study” solving a problem for a client.) I was there because I had admired the partner in charge of the team since meeting him in the recruiting process. Jeff Helbling was low-key and clean-cut, with a sort of smart and unflappable discipline that melded the styles of his alma maters, West Point and Harvard Business School. A wise McKinsey alum had once told me that there were four things to think about when chasing assignments at the Firm: geography, industry, function, and people. Of these, she counseled, the most important is people. So when the chance came to work with Jeff, I jumped, even though I was uncertain how much professional fulfillment came from the prospect of commuting to Toronto every week to help a client in the grocery business figure out how to update its prices.
Soon I was spending my weekdays in a small, glass-walled conference room with three colleagues in a suburban office park, building models to compute how much it would cost to cut prices on various combinations of tens of thousands of items across hundreds of stores in every part of the country. The more I worked on the problem, the more complicated it seemed to become. Eventually the volume of data went beyond the capabilities of Microsoft Excel, and I began using a program called Microsoft Access. Access is designed to hold databases, but I was using it to do math, stretching its functionality to make it work partly like a computational spreadsheet on top of the data management program it was intended to be. As the data set grew to millions of lines, it started freezing my laptop computer. To make me more productive, the firm mailed a more powerful desktop computer to our team room. I hooked it up and spent the better part of many fourteen-hour days calculating at the machine, which my colleagues nicknamed Bertha.
Against all my expectations, it was fascinating. I wasn’t just learning about the retail business or about computer programs—I was also learning about the nature of data. By manipulating millions of data points, I could weave stories about possible futures, and gather insights on which ideas were good or bad. I could simulate millions of shoppers going up and down the aisles of thousands of stores, and in my mind I pictured their habits shifting as a well-placed price cut subtly changed their perceptions of our client as a better place to shop.
Even more fulfilling, I became a useful part of a team that I liked. My manager, a young Englishwoman named Hannah Brooks with a varsity-level cricket career at Oxford under her belt, took good care of our team—checking on how we were doing and trying to protect our weekends from unnecessary encroachments of work—and I wanted to do a good job for her. Jeff came in every week or so to check on progress, and I felt motivated by the task of presenting him and Hannah with interesting results that he could share with the senior leadership of the client.
The problem grew ever more complex as we were asked to analyze the data more and more deeply. As the deadline for implementing the price cuts loomed, pressure grew—and so did the hours. Soon we were working sixty, seventy, eighty hours a week. At one point, a glitch in a computer pricing tool threatened to give every item the wrong UPC code by one digit, meaning the system could give dog food the price for olive oil, or price a snow shovel as a box of cereal. Everyone involved in the project had to do nothing else for days as we raced to manually correct the problem before the deadline for a round of price changes. One night I stopped work at four in the morning, only to toss and turn in my hotel bed, dreaming in spreadsheets. Friends became Excel formulas, fears were expressed as charts in PowerPoint.
Occasionally, I had worked that hard on a campaign or on my studies, but it felt strange to put in those kinds of hours not for a cause but for a client. I wanted to do a good job for my team, my firm, and my client—but this wasn’t life-or-death stuff. And so it may have been inevitable that one afternoon, as I set Bertha to sleep mode to go out to the hallway for a cup of coffee, I realized with overwhelming clarity the reason this could not be a career for very long: I didn’t care.