Data-Driven Location Choices Drive Latest Starbucks Surge

by   |   January 10, 2013 3:41 pm   |   0 Comments

Starbucks in Hong Kong by Jackie Cheu 2008 via Wikipedia crop Data Driven Location Choices Drive Latest Starbucks Surge

A Starbucks shop in Hong Kong. The coffee retailer plans to add hundreds of stores to China and other Asian countries as part of its expansion plan. Photo by Jackie Cheu via Wikipedia.

Starbucks began 2013 in style, announcing last week that it would be opening its first store in Vietnam next month, located in Ho Chi Minh City. But while the new store is the company’s first opening in Vietnam, it’s far from its first in Asia.

By the end of this year, said Starbucks management at the company’s biennial investors’ conference in December, the world’s largest coffee house company will have no fewer than 4,000 stores in the region—including around 1,000 in China, 1,000 in Japan, and 500 in South Korea. By 2014, in short, China will become Starbucks’ second-largest market outside of the United States—impressive for a market that it entered for the first time in 1999.

Predictably, investors and analysts have applauded such statistics as signs that the company’s heady expansion in recent times could be maintained: operating income has grown at a heady 32 percent compound annual growth rate over the last five years, prompting skeptics to believe that a slowdown in sales and income growth is all but inevitable.

“Starbucks will have more than 20,000 retail stores on six continents by 2014,” company chairman, president and chief executive officer Howard Schultz reassured investors. “We have challenges, we have issues, but we’ve never been in a better position in terms of the strength and power of the Starbucks brand.”

But the challenge, as Schultz noted, isn’t in penetrating new Asian markets, but delivering solid growth in more saturated markets. And saturated markets don’t come more laden with Starbucks stores than the United States, where investors were told that 1,500 new stores would be in place by 2017—just five years away.

The risks are obvious. Cannibalization of sales through existing stores, certainly. Brand fatigue, possibly. But also another episode of the sort of abrupt reversal and retrenchment that the company was forced to undergo in 2007 and 2008, when Schultz came out of retirement to close hundreds of stores and restore the company’s luster.

For with the benefit of hindsight, reckon both Starbucks officials and observers, it’s clear that many of those stores should never have been opened in the first place.

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“The majority of the stores that Starbucks closed in 2007 and 2008 were stores that it had opened in the previous eighteen months,” says Starbucks watcher Craig Garthwaite, assistant professor of management and strategy at Northwestern University’s Kellogg School of Management. “It seemed that they were opening stores just for the sake of opening them—even where there wasn’t a profitable opportunity.”

Geographic Data Directing Store Site Selection
This time it will be different, vowed Schultz, explaining that a more disciplined, data-driven approach to store opening had produced very different results over the past two years.

In short, he said, the store openings classes of 2011 and 2012 had produced some of the best unit economics in the history of the company, with a sales–to-investment ratio of 2:1, very strong compound growth, and average per-store volumes at record levels.

Figures highlighted by Cliff Burrows, Starbucks’ president of the Americas and United States, for instance, showed new U.S. stores delivering first year sales of $1,052,000, versus a target of $900,000—and costing on average $494,000 to build (the 2:1 sales-to-investment result).

“In 2007 and 2008, the growth of Starbucks was undisciplined, and growth was more of a strategy as opposed to an outcome,” acknowledged Schultz during the conference. “You’ll hear [us] talk today about accelerating the growth of our United States business, and opening up at least 1,500 new stores over the next five years in the United States alone. And we strongly believe that as a result of the demography, the data, the science and the experience we have, that these locations in the returns will mirror what we’ve been able to accomplish in 2011 and 2012.”

For “demography, data and science,” read the company’s investment in location analytics tools from market leader Esri.

A longtime user of Esri’s Geographic Information Systems (GIS) technology, Starbucks began using GIS technology and data in the late 1990s, Starbucks manager of global market planning Patrick O’Hagan told delegates to the 2011 Esri Business Summit, held in San Diego, and attended by 200 business executives from all over the world.

So unavoidably, GIS analytics technology is implicated in the 2006 and 2007 opening of stores that were subsequently closed—which O’Hagan acknowledged, referring to the then-practice of the company’s GIS staff flooding Starbucks staff members with data, especially those working with real estate.

“We put the buggy before the horse,” he said. For while Starbucks staff had access to massive amounts of data, they had no way to easily analyze it.

Different Approach: GIS Data in the Hands of the Right Users
At the 2011 Esri conference, O’Hagan said that a different approach prevails: instead of delivering a flood of data, the GIS team provides analytics and business support to its real estate section, using Esri’s ArcGIS for Server solution to create data‑rich applications that staff members can access from desktops, the Internet, and mobile devices in the field.

“Our people don’t want to know what GIS means or what it can do,” explained O’Hagan. “They care about functionality, speed, and convenience. ArcGIS allows us to create replicable consumer applications that are exactly what they need.”

So where exactly will Starbucks put its 1,500 new stores—and how will it avoid having them cannibalize sales of other existing stores? Starbucks declined repeated requests for an interview.

But CFO Troy Alstead, again speaking to investors, provided a clue, referring to a deliberate strategy of pinpointing stores—including drive-throughs and smaller stores—in locations that were more convenient for customers.

“We have more discipline and rigor around new store development and the monitoring of new store performance and returns, today, than we ever have before,” Alstead said. “The most recent class of [newly opened] stores, particularly in the Americas, have consistently produced great returns, exceeding our hurdle rates.”

And for Kellogg’s Starbucks watcher Garthwaite, statements like that are indication enough of a sea change in thinking, and of the proactive role played by analytics in determining store locations.

“This focus on the profitability of individual stores is a big step forward from 2007 and 2008,” he notes. “Management are adamant that they’re not growing for the sake of growing, and that they’re focusing on the individual profitability prospects of each newly-opened store, and not assuming that just because they’re Starbucks, stores should succeed anywhere.”

Freelance writer Malcolm Wheatley is old enough to remember analyzing punched card datasets in batch mode, using SPSS on mainframes. He lives in Devon, England, and can be reached at editor@malcolmwheatley.co.uk.





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